Publications of Amanda Randles
%% Books
@book{fds369994,
Author = {Vardhan, M and Shi, H and Gounley, J and Chen, SJ and Kahn, A and Leopold,
J and Randles, A},
Title = {Correction to: Investigating the Role of VR in a
Simulation-Based Medical Planning System for Coronary
Interventions (Medical Image Computing and Computer Assisted
Intervention – MICCAI 2019, LNCS 11768,
10.1007/978-3-030-32254-0_41)},
Volume = {11768 LNCS},
Pages = {C1},
Year = {2019},
Month = {January},
ISBN = {9783030322533},
Abstract = {The original version of this chapter was revised. The
spelling of the last author’s name was corrected to Amanda
Randles.},
Doi = {10.1007/978-3-030-32254-0_77},
Key = {fds369994}
}
%% Papers Published
@article{fds374024,
Author = {Pang, Y-P and Swartz, B and Smith, B and Mullins, T and Peters, A and Musselman, R},
Title = {Poster reception---Optimizing EUDOC for the IBM eServer Blue
Gene supercomputer},
Journal = {Proceedings of the 2006 ACM/IEEE conference on
Supercomputing - SC '06},
Publisher = {ACM Press},
Year = {2006},
Doi = {10.1145/1188455.1188635},
Key = {fds374024}
}
@article{fds314522,
Author = {Randles, A},
Title = {Parallel Genomic Sequence-Search on a Massively Parallel
System},
Publisher = {ACM},
Editor = {Thorsen, O and Jiang, K and Smith, B and Lin, H and Feng, W and Sosa,
CP},
Year = {2007},
Month = {May},
Key = {fds314522}
}
@article{fds314519,
Author = {Jiang, K and Thorsen, O and Peters, A and Smith, B and Sosa,
CP},
Title = {An Efficient Parallel Implementation of the Hidden Markov
Methods for Genomic Sequence-Search on a Massively Parallel
System},
Journal = {IEEE Transactions on Parallel and Distributed
Systems},
Volume = {19},
Number = {1},
Pages = {15-23},
Publisher = {Institute of Electrical and Electronics Engineers
(IEEE)},
Year = {2008},
Month = {January},
ISSN = {1045-9219},
Doi = {10.1109/tpds.2007.70712},
Key = {fds314519}
}
@article{fds314520,
Author = {Pang, Y-P and Mullins, TJ and Swartz, BA and McAllister, JS and Smith,
BE and Archer, CJ and Musselman, RG and Peters, AE and Wallenfelt, BP and Pinnow, KW},
Title = {EUDOC on the IBM Blue Gene/L system: Accelerating the
transfer of drug discoveries from laboratory to
patient},
Journal = {IBM Journal of Research and Development},
Volume = {52},
Number = {1.2},
Pages = {69-81},
Publisher = {IBM},
Year = {2008},
Month = {January},
ISSN = {0018-8646},
Doi = {10.1147/rd.521.0069},
Key = {fds314520}
}
@article{fds314518,
Author = {Randles, A and Melchionna, S and Kaxiras, E and Latt, J and Sircar, J and Bernaschi, M and Bisson, M and Succi, S},
Title = {Multiscale simulation of cardiovascular flows on the IBM
Bluegene/P: full heart-circulation system at red-blood cell
resolution},
Publisher = {ACM IEEE},
Year = {2010},
Month = {November},
Key = {fds314518}
}
@article{fds314517,
Author = {Robson, B and Li, J and Dettinger, R and Peters, A and Boyer,
SK},
Title = {Drug discovery using very large numbers of patents: general
strategy with extensive use of match and edit
operations.},
Journal = {Journal of computer-aided molecular design},
Volume = {25},
Number = {5},
Pages = {427-441},
Publisher = {Springer Science and Business Media LLC},
Year = {2011},
Month = {May},
ISSN = {0920-654X},
Abstract = {A patent data base of 6.7 million compounds generated by a
very high performance computer (Blue Gene) requires new
techniques for exploitation when extensive use of chemical
similarity is involved. Such exploitation includes the
taxonomic classification of chemical themes, and data mining
to assess mutual information between themes and companies.
Importantly, we also launch candidates that evolve by
"natural selection" as failure of partial match against the
patent data base and their ability to bind to the protein
target appropriately, by simulation on Blue Gene. An unusual
feature of our method is that algorithms and workflows rely
on dynamic interaction between match-and-edit instructions,
which in practice are regular expressions. Similarity
testing by these uses SMILES strings and, less frequently,
graph or connectivity representations. Examining how this
performs in high throughput, we note that chemical
similarity and novelty are human concepts that largely have
meaning by utility in specific contexts. For some purposes,
mutual information involving chemical themes might be a
better concept.},
Doi = {10.1007/s10822-011-9429-x},
Key = {fds314517}
}
@article{fds314516,
Author = {Randles, A and Zeger, L},
Title = {Efficient Resource Allocation for Broadcasting Multi-Slot
Messages With Random Access with Capture},
Publisher = {IEEE},
Year = {2011},
Month = {October},
url = {http://www.milcom.org/2011/},
Key = {fds314516}
}
@article{fds374023,
Author = {Peters, A and Zeger, L},
Title = {Efficient methods for broadcasting multi-slot messages with
random access with capture},
Journal = {2011 - MILCOM 2011 Military Communications
Conference},
Publisher = {IEEE},
Year = {2011},
Month = {November},
Doi = {10.1109/milcom.2011.6127580},
Key = {fds374023}
}
@article{fds314515,
Author = {Borkin, MA and Gajos, KZ and Peters, A and Mitsouras, D and Melchionna,
S and Rybicki, FJ and Feldman, CL and Pfister, H},
Title = {Evaluation of artery visualizations for heart disease
diagnosis.},
Journal = {IEEE transactions on visualization and computer
graphics},
Volume = {17},
Number = {12},
Pages = {2479-2488},
Year = {2011},
Month = {December},
ISSN = {1077-2626},
Abstract = {Heart disease is the number one killer in the United States,
and finding indicators of the disease at an early stage is
critical for treatment and prevention. In this paper we
evaluate visualization techniques that enable the diagnosis
of coronary artery disease. A key physical quantity of
medical interest is endothelial shear stress (ESS). Low ESS
has been associated with sites of lesion formation and rapid
progression of disease in the coronary arteries. Having
effective visualizations of a patient's ESS data is vital
for the quick and thorough non-invasive evaluation by a
cardiologist. We present a task taxonomy for hemodynamics
based on a formative user study with domain experts. Based
on the results of this study we developed HemoVis, an
interactive visualization application for heart disease
diagnosis that uses a novel 2D tree diagram representation
of coronary artery trees. We present the results of a formal
quantitative user study with domain experts that evaluates
the effect of 2D versus 3D artery representations and of
color maps on identifying regions of low ESS. We show
statistically significant results demonstrating that our 2D
visualizations are more accurate and efficient than 3D
representations, and that a perceptually appropriate color
map leads to fewer diagnostic mistakes than a rainbow color
map.},
Doi = {10.1109/tvcg.2011.192},
Key = {fds314515}
}
@article{fds315888,
Author = {Randles, A and Baecher, M and Pfister, H and Kaxiras,
EK},
Title = {A Lattice Boltzmann Simulation of Hemodynamics in a
Patient-Speci c Aortic Coarctation Model},
Journal = {Statistical Atlases and Computational Models of the Heart:
Imaging and Modelling Challenges:},
Volume = {7746},
Pages = {17-25},
Publisher = {Springer Berlin Heidelberg},
Editor = {Camara, O and Pop, M and Mansi, T and Sermesant, M and Young,
A},
Year = {2012},
Month = {October},
url = {http://link.springer.com/chapter/10.1007/978-3-642-36961-2_3},
Abstract = {In this paper, we propose a system to determine the pressure
gradient at rest in the aorta. We developed a technique to
efficiently initialize a regular simulation grid from a
patient-specific aortic triangulated model. On this grid we
employ the lattice Boltzmann method to resolve the
characteristic fluid flow through the vessel. The inflow
rates, as measured physiologically, are imposed providing
accurate pulsatile flow. The simulation required a
resolution of at least 20 microns to ensure a convergence of
the pressure calculation. HARVEY, a large-scale parallel
code, was run on the IBM Blue Gene/Q supercomputer to model
the flow at this high resolution. We analyze and evaluate
the strengths and weaknesses of our system.},
Doi = {10.1007/978-3-642-36961-2_3},
Key = {fds315888}
}
@article{fds314505,
Author = {Randles, AP},
Title = {Massively parallel model of evolutionary game
dynamics},
Journal = {Proceedings - 2012 SC Companion: High Performance Computing,
Networking Storage and Analysis, SCC 2012},
Pages = {1531},
Publisher = {IEEE},
Year = {2012},
Month = {December},
Abstract = {To study the emergence of cooperative behavior, we have
developed a scalable parallel framework. An important aspect
is the amount of history that each agent can keep. When six
memory steps are taken into account, the strategy space
spans 24096 potential strategies, requiring large
populations of agents. We introduce a multi-level
decomposition method that allows us to exploit both
multi-node and thread-level parallel scaling while
minimizing the communication overhead. We present the
following contributions: (1) A production run modeling up to
six memory steps for populations consisting of up to 1018
agents, making this study one of the largest yet undertaken.
(2) Results exhibiting near perfect weak scaling and 82%
strong scaling efficiency up to 262,144 processors of the
IBM Blue Gene/P supercomputer and 16,384 processors of the
Blue Gene/Q. Our framework marks an important step in the
study of game dynamics with potential applications in fields
ranging from biology to economics and sociology. © 2012
IEEE.},
Doi = {10.1109/SC.Companion.2012.307},
Key = {fds314505}
}
@article{fds314514,
Author = {Keyes, DE and McInnes, LC and Woodward, C and Gropp, W and Myra, E and Pernice, M and Bell, J and Brown, J and Clo, A and Connors, J and Constantinescu, E and Estep, D and Evans, K and Farhat, C and Hakim, A and Hammond, G and Hansen, G and Hill, J and Isaac, T and Jiao, X and Jordan,
K and Kaushik, D and Kaxiras, E and Koniges, A and Lee, K and Lott, A and Lu,
Q and Magerlein, J and Maxwell, R and McCourt, M and Mehl, M and Pawlowski,
R and Randles, AP and Reynolds, D and Rivière, B and Rüde, U and Scheibe,
T and Shadid, J and Sheehan, B and Shephard, M and Siegel, A and Smith, B and Tang, X and Wilson, C and Wohlmuth, B},
Title = {Multiphysics simulations: Challenges and
opportunities},
Journal = {International Journal of High Performance Computing
Applications},
Volume = {27},
Number = {1},
Pages = {4-83},
Publisher = {SAGE Publications},
Year = {2013},
Month = {February},
ISSN = {1094-3420},
Abstract = {We consider multiphysics applications from algorithmic and
architectural perspectives, where "algorithmic" includes
both mathematical analysis and computational complexity, and
"architectural" includes both software and hardware
environments. Many diverse multiphysics applications can be
reduced, en route to their computational simulation, to a
common algebraic coupling paradigm. Mathematical analysis of
multiphysics coupling in this form is not always practical
for realistic applications, but model problems
representative of applications discussed herein can provide
insight. A variety of software frameworks for multiphysics
applications have been constructed and refined within
disciplinary communities and executed on leading-edge
computer systems. We examine several of these, expose some
commonalities among them, and attempt to extrapolate best
practices to future systems. From our study, we summarize
challenges and forecast opportunities. © The Author(s)
2012.},
Doi = {10.1177/1094342012468181},
Key = {fds314514}
}
@article{fds314526,
Author = {Randles, A and Kale, V and Hammond, JR and Gropp, W and Kaxiras,
E},
Title = {Performance analysis of the lattice Boltzmann model beyond
Navier-Stokes},
Pages = {1063-1074},
Publisher = {IEEE},
Year = {2013},
Month = {October},
ISBN = {9781467360661},
Abstract = {The lattice Boltzmann method is increasingly important in
facilitating large-scale fluid dynamics simulations. To
date, these simulations have been built on discretized
velocity models of up to 27 neighbors. Recent work has shown
that higher order approximations of the continuum Boltzmann
equation enable not only recovery of the Navier-Stokes
hydro-dynamics, but also simulations for a wider range of
Knudsen numbers, which is especially important in micro- and
nano-scale flows. These higher-order models have significant
impact on both the communication and computational
complexity of the application. We present a performance
study of the higher-order models as compared to the
traditional ones, on both the IBM Blue Gene/P and Blue
Gene/Q architectures. We study the tradeoffs of many
optimizations methods such as the use of deep halo level
ghost cells that, alongside hybrid programming models,
reduce the impact of extended models and enable efficient
modeling of extreme regimes of computational fluid dynamics.
© 2013 IEEE.},
Doi = {10.1109/IPDPS.2013.109},
Key = {fds314526}
}
@article{fds314507,
Author = {Randles, A and Draeger, E and Michor, F},
Title = {Analysis of pressure gradient across aortic stenosis with
massively parallel computational simulations},
Journal = {Computing in Cardiology},
Volume = {41},
Number = {January},
Pages = {217-220},
Year = {2014},
Month = {January},
ISSN = {2325-8861},
Abstract = {Coarctation of the aorta (CoA) is one of the most common
congenital heart defects in the United States, and despite
treatment, patients have a decrease in life expectancy.
Computational fluid dynamics simulations can provide the
physician with a non-invasive method to measure the pressure
gradient. With HARVEY, a massively parallel hemodynamics
application, patient specific simulations can be conducted
of large regions of the vasculature. The pressure across the
stenosis is impacted by flow from nearby vessels. The
purpose of this study was to study the impact of including
these distal vessels in the simulation on the resulting
pressure measurements. Computational fluid dynamic
simulations were conducted in three subsets of one patient's
vasculature. We demonstrate up to a 29% difference in
calculated pressure gradient based on the number of vessels
included in the simulation. These initial results are
positive but need to be substantiated with further patient
studies.},
Key = {fds314507}
}
@article{fds344697,
Author = {Randles, A and Kaxiras, EK},
Title = {A Spatio-Temporal Coupling Method to Reduce the
Time-to-Solution of Cardiovascular Simulations},
Journal = {http://ieeexplore.ieee.org/abstract/document/6877292/},
Pages = {593-602},
Year = {2014},
Month = {January},
ISBN = {978-1-4799-3801-8},
Abstract = {We present a new parallel-in-time method designed to reduce
the overall time-to-solution of a patient-specific
cardiovascular flow simulation. Using a modified Para real
algorithm, our approach extends strong scalability beyond
spatial parallelism with fully controllable accuracy and no
decrease in stability. We discuss the coupling of spatial
and temporal domain decompositions used in our
implementation, and showcase the use of the method on a
study of blood flow through the aorta. We observe an
additional 40% reduction in overall wall clock time with no
significant loss of accuracy, in agreement with a predictive
performance model.},
Doi = {10.1109/IPDPS.2014.68},
Key = {fds344697}
}
@article{fds314525,
Author = {Randles, A},
Title = {MIC-SVM: Designing A Highly Efficient Support Vector Machine
for Advanced Modern Multi-Core and Many-Core
Architectures},
Journal = {http://ieeexplore.ieee.org/abstract/document/6877312/},
Pages = {809-818},
Year = {2014},
Month = {January},
ISBN = {9780769552071},
ISSN = {1530-2075},
Abstract = {Support Vector Machine (SVM) has been widely used in
data-mining and Big Data applications as modern commercial
databases start to attach an increasing importance to the
analytic capabilities. In recent years, SVM was adapted to
the field of High Performance Computing for
power/performance prediction, auto-tuning, and runtime
scheduling. However, even at the risk of losing prediction
accuracy due to insufficient runtime information,
researchers can only afford to apply offline model training
to avoid significant runtime training overhead. Advanced
multi- and many-core architectures offer massive parallelism
with complex memory hierarchies which can make runtime
training possible, but form a barrier to efficient parallel
SVM design. To address the challenges above, we designed and
implemented MIC-SVM, a highly efficient parallel SVM for x86
based multi-core and many-core architectures, such as the
Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC).
We propose various novel analysis methods and optimization
techniques to fully utilize the multilevel parallelism
provided by these architectures and serve as general
optimization methods for other machine learning tools.
MIC-SVM achieves 4.4-84x and 18-47x speedups against the
popular LIBSVM, on MIC and Ivy Bridge CPUs respectively, for
several real-world data-mining datasets. Even compared with
GPUSVM, run on a top of the line NVIDIA k20x GPU, the
performance of our MIC-SVM is competitive. We also conduct a
cross-platform performance comparison analysis, focusing on
Ivy Bridge CPUs, MIC and GPUs, and provide insights on how
to select the most suitable advanced architectures for
specific algorithms and input data patterns. © 2014
IEEE.},
Doi = {10.1109/IPDPS.2014.88},
Key = {fds314525}
}
@article{fds314513,
Author = {Almendro, V and Cheng, Y-K and Randles, A and Itzkovitz, S and Marusyk,
A and Ametller, E and Gonzalez-Farre, X and Muñoz, M and Russnes, HG and Helland, A and Rye, IH and Borresen-Dale, A-L and Maruyama, R and van
Oudenaarden, A and Dowsett, M and Jones, RL and Reis-Filho, J and Gascon, P and Gönen, M and Michor, F and Polyak,
K},
Title = {Inference of tumor evolution during chemotherapy by
computational modeling and in situ analysis of genetic and
phenotypic cellular diversity.},
Journal = {Cell reports},
Volume = {6},
Number = {3},
Pages = {514-527},
Year = {2014},
Month = {February},
ISSN = {2211-1247},
Abstract = {Cancer therapy exerts a strong selection pressure that
shapes tumor evolution, yet our knowledge of how tumors
change during treatment is limited. Here, we report the
analysis of cellular heterogeneity for genetic and
phenotypic features and their spatial distribution in breast
tumors pre- and post-neoadjuvant chemotherapy. We found that
intratumor genetic diversity was tumor-subtype specific, and
it did not change during treatment in tumors with partial or
no response. However, lower pretreatment genetic diversity
was significantly associated with pathologic complete
response. In contrast, phenotypic diversity was different
between pre- and posttreatment samples. We also observed
significant changes in the spatial distribution of cells
with distinct genetic and phenotypic features. We used these
experimental data to develop a stochastic computational
model to infer tumor growth patterns and evolutionary
dynamics. Our results highlight the importance of integrated
analysis of genotypes and phenotypes of single cells in
intact tissues to predict tumor evolution.},
Doi = {10.1016/j.celrep.2013.12.041},
Key = {fds314513}
}
@article{fds314512,
Author = {Randles, A and Rand, D and Lee, C and Morrisett, G and Pfister,
H},
Title = {Massively Parallel Model of Extended Memory Use In
Evolutionary Game Dynamics},
Pages = {1217-1228},
Publisher = {IEEE},
Year = {2014},
Month = {May},
ISBN = {9781467360661},
Abstract = {To study the emergence of cooperative behavior, we have
developed a scalable parallel framework for evolutionary
game dynamics. This is a critical computational tool
enabling large-scale agent simulation research. An important
aspect is the amount of history, or memory steps, that each
agent can keep. When six memory steps are taken into
account, the strategy space spans 2 4096 potential
strategies, requiring large populations of agents. We
introduce a multi-level decomposition method that allows us
to exploit both multi-node and thread-level parallel scaling
while minimizing communication overhead. We present the
results of a production run modeling up to six memory steps
for populations consisting of up to 1018 agents, making this
study one of the largest yet undertaken. The high rate of
mutation within the population results in a non-trivial
parallel implementation. The strong and weak scaling studies
provide insight into parallel scalability and
programmability trade-offs for large-scale simulations,
while exhibiting near perfect weak and strong scaling on
16,384 tasks on Blue Gene/Q. We further show 99% weak
scaling up to 294,912 processors 82% strong scaling
efficiency up to 262,144 processors of Blue Gene/P. Our
framework marks an important step in the study of game
dynamics with potential applications in fields ranging from
biology to economics and sociology. © 2013
IEEE.},
Doi = {10.1109/IPDPS.2013.102},
Key = {fds314512}
}
@article{fds314511,
Author = {Randles, A and Kaxiras, E},
Title = {Parallel in time approximation of the lattice Boltzmann
method for laminar flows},
Journal = {Journal of Computational Physics},
Volume = {270},
Pages = {577-586},
Publisher = {Elsevier BV},
Year = {2014},
Month = {August},
ISSN = {0021-9991},
Abstract = {Fluid dynamics simulations using grid-based methods, such as
the lattice Boltzmann equation, can benefit from
parallel-in-space computation. However, for a fixed-size
simulation of this type, the efficiency of larger processor
counts will saturate when the number of grid points per core
becomes too small. To overcome this fundamental strong
scaling limit in space-parallel approaches, we present a
novel time-parallel version of the lattice Boltzmann method
using the parareal algorithm. This method is based on a
predictor-corrector scheme combined with mesh refinement to
enable the simulation of larger number of time steps. We
present results of up to a 32× increase in speed for a
model system consisting of a cylinder with conditions for
laminar flow. The parallel gain obtainable is predicted with
strong accuracy, providing a quantitative understanding of
the potential impact of this method. © 2014 Elsevier
Inc.},
Doi = {10.1016/j.jcp.2014.04.006},
Key = {fds314511}
}
@article{fds322671,
Author = {Kale, V and Randles, A and Gropp, WD},
Title = {Locality-optimized mixed static/dynamic scheduling for
improving load balancing on SMPs},
Journal = {ACM International Conference Proceeding Series},
Volume = {09-12-September-2014},
Pages = {115-116},
Publisher = {ACM Press},
Year = {2014},
Month = {September},
ISBN = {9781450328753},
Abstract = {Application performance can be degraded significantly due to
node-local load imbalances during application execution.
Prior work suggested using a mixed static/dynamic scheduling
approach for handling this problem, specifically in the
context of fine-grained, transient load imbalances. Here, we
consider an alternate strategy for more general load
imbalances where fine-grained, transient load imbalance may
be coupled with coarse-grained load imbalance. Specifically,
we implement a scheduling scheme in which we modify the data
layout in mixed static/dynamic scheduling, and add an
additional tuned constraint in the dequeue function of our
scheduler. Through experimentation of an n-body particle
simulation code on modern multi-core architectures, our
technique gives a 19.4% performance gain over dynamic
scheduling, and an overall 48.6% performance gain over
standard static scheduling.},
Doi = {10.1145/2642769.2642788},
Key = {fds322671}
}
@article{fds314510,
Author = {You, Y and Fu, H and Song, SL and Randles, A and Kerbyson, D and Marquez,
A and Yang, G and Hoisie, A},
Title = {Scaling Support Vector Machines on modern HPC
platforms},
Journal = {Journal of Parallel and Distributed Computing},
Volume = {76},
Pages = {16-31},
Publisher = {Elsevier BV},
Year = {2015},
Month = {January},
ISSN = {0743-7315},
Abstract = {Support Vector Machines (SVM) have been widely used in
data-mining and Big Data applications as modern commercial
databases start to attach an increasing importance to the
analytic capabilities. In recent years, SVM was adapted to
the field of High Performance Computing for
power/performance prediction, auto-tuning, and runtime
scheduling. However, even at the risk of losing prediction
accuracy due to insufficient runtime information,
researchers can only afford to apply offline model training
to avoid significant runtime training overhead. Advanced
multi- and many-core architectures offer massive parallelism
with complex memory hierarchies which can make runtime
training possible, but form a barrier to efficient parallel
SVM design. To address the challenges above, we designed and
implemented MIC-SVM, a highly efficient parallel SVM for x86
based multi-core and many-core architectures, such as the
Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC).
We propose various novel analysis methods and optimization
techniques to fully utilize the multilevel parallelism
provided by these architectures and serve as general
optimization methods for other machine learning tools.
MIC-SVM achieves 4.4-84× and 18-47× speedups against the
popular LIBSVM, on MIC and Ivy Bridge CPUs respectively, for
several real-world data-mining datasets. Even compared with
GPUSVM, running on the NVIDIA k20x GPU, the performance of
our MIC-SVM is competitive. We also conduct a cross-platform
performance comparison analysis, focusing on Ivy Bridge
CPUs, MIC and GPUs, and provide insights on how to select
the most suitable advanced architectures for specific
algorithms and input data patterns.},
Doi = {10.1016/j.jpdc.2014.09.005},
Key = {fds314510}
}
@article{fds314509,
Author = {Whitley, HD and Scullard, CR and Benedict, LX and Castor, JI and Randles, A and Glosli, JN and Richards, DF and Desjarlais, MP and Graziani, FR},
Title = {Lenard-Balescu calculations and classical molecular dynamics
simulations of electrical and thermal conductivities of
hydrogen plasmas},
Journal = {Contributions to Plasma Physics},
Volume = {55},
Number = {2-3},
Pages = {192-202},
Publisher = {WILEY},
Year = {2015},
Month = {February},
ISSN = {0863-1042},
Abstract = {We present a discussion of kinetic theory treatments of
linear electrical and thermal transport in hydrogen plasmas,
for a regime of interest to inertial confinement fusion
applications. In order to assess the accuracy of one of the
more involved of these approaches, classical Lenard-Balescu
theory, we perform classical molecular dynamics simulations
of hydrogen plasmas using 2-body quantum statistical
potentials and compute both electrical and thermal
conductivity from our particle trajectories using the Kubo
approach. Our classical Lenard-Balescu results employing the
identical statistical potentials agree well with the
simulations. Comparison between quantum Lenard-Balescu and
classical Lenard-Balescu for conductivities then allows us
to both validate and critique the use of various statistical
potentials for the prediction of plasma transport
properties. These findings complement our earlier MD/kinetic
theory work on temperature equilibration [1], and reach
similar conclusions as to which forms of statistical
potentials best reproduce true quantum behavior.},
Doi = {10.1002/ctpp.201400066},
Key = {fds314509}
}
@article{fds314508,
Author = {Randles, A and Draeger, EW and Bailey, PE},
Title = {Massively parallel simulations of hemodynamics in the
primary large arteries of the human vasculature.},
Journal = {Journal of computational science},
Volume = {9},
Pages = {70-75},
Publisher = {Elsevier BV},
Year = {2015},
Month = {July},
ISSN = {1877-7503},
Abstract = {We present a computational model of three-dimensional and
unsteady hemodynamics within the primary large arteries in
the human on 1,572,864 cores of the IBM Blue Gene/Q. Models
of large regions of the circulatory system are needed to
study the impact of local factors on global hemodynamics and
to inform next generation drug delivery mechanisms. The
HARVEY code successfully addresses key challenges that can
hinder effective solution of image-based hemodynamics on
contemporary supercomputers, such as limited memory capacity
and bandwidth, flexible load balancing, and scalability.
This work is the first demonstration of large fluid dynamics
simulations of the aortofemoral region of the circulatory
system at resolutions as small as 10 μm.},
Doi = {10.1016/j.jocs.2015.04.003},
Key = {fds314508}
}
@article{fds314524,
Author = {Randles, A and Draeger, EW and Oppelstrup, T and Krauss, L and Gunnels,
J},
Title = {Massively Parallel Models of the Human Circulatory
System},
Journal = {http://dl.acm.org/citation.cfm?id=2807676},
Volume = {15-20-November-2015},
Publisher = {ACM},
Year = {2015},
Month = {November},
ISBN = {978-1-4503-3723-6},
ISSN = {2167-4329},
url = {http://dl.acm.org/citation.cfm?id=2807676},
Abstract = {The potential impact of blood flow simulations on the
diagnosis and treatment of patients suffering from vascular
disease is tremendous. Empowering models of the full
arterial tree can provide insight into diseases such as
arterial hypertension and enables the study of the influence
of local factors on global hemodynamics. We present a new,
highly scalable implementation of the lattice Boltzmann
method which addresses key challenges such as multiscale
coupling, limited memory capacity and bandwidth, and robust
load balancing in complex geometries. We demonstrate the
strong scaling of a three-dimensional, high-resolution
simulation of hemodynamics in the systemic arterial tree on
1,572,864 cores of Blue Gene/Q. Faster calculation of flow
in full arterial networks enables unprecedented risk
stratification on a perpatient basis. In pursuit of this
goal, we have introduced computational advances that
significantly reduce time-to-solution for biofluidic
simulations.},
Doi = {10.1145/2807591.2807676},
Key = {fds314524}
}
@article{fds323711,
Author = {Gounley, J and Chaudhury, R and Vardhan, M and Driscoll, M and Pathangey, G and Winarta, K and Ryan, J and Frakes, D and Randles,
A},
Title = {Does the degree of coarctation of the aorta influence wall
shear stress focal heterogeneity?},
Volume = {2016},
Number = {2016},
Pages = {3429-3432},
Publisher = {IEEE},
Year = {2016},
Month = {August},
ISBN = {9781457702204},
Abstract = {The development of atherosclerosis in the aorta is
associated with low and oscillatory wall shear stress for
normal patients. Moreover, localized differences in wall
shear stress heterogeneity have been correlated with the
presence of complex plaques in the descending aorta. While
it is known that coarctation of the aorta can influence
indices of wall shear stress, it is unclear how the degree
of narrowing influences resulting patterns. We hypothesized
that the degree of coarctation would have a strong influence
on focal heterogeneity of wall shear stress. To test this
hypothesis, we modeled the fluid dynamics in a
patient-specific aorta with varied degrees of coarctation.
We first validated a massively parallel computational model
against experimental results for the patient geometry and
then evaluated local shear stress patterns for a range of
degrees of coarctation. Wall shear stress patterns at two
cross sectional slices prone to develop atherosclerotic
plaques were evaluated. Levels at different focal regions
were compared to the conventional measure of average
circumferential shear stress to enable localized
quantification of coarctation-induced shear stress
alteration. We find that the coarctation degree causes
highly heterogeneous changes in wall shear
stress.},
Doi = {10.1109/embc.2016.7591465},
Key = {fds323711}
}
@article{fds328446,
Author = {Gounley, J and Draeger, EW and Randles, A},
Title = {Numerical simulation of a compound capsule in a constricted
microchannel.},
Journal = {Procedia computer science},
Volume = {108},
Pages = {175-184},
Year = {2017},
Month = {January},
Abstract = {Simulations of the passage of eukaryotic cells through a
constricted channel aid in studying the properties of cancer
cells and their transport in the bloodstream. Compound
capsules, which explicitly model the outer cell membrane and
nuclear lamina, have the potential to improve computational
model fidelity. However, general simulations of compound
capsules transiting a constricted microchannel have not been
conducted and the influence of the compound capsule model on
computational performance is not well known. In this study,
we extend a parallel hemodynamics application to simulate
the fluid-structure interaction between compound capsules
and fluid. With this framework, we compare the deformation
of simple and compound capsules in constricted
microchannels, and explore how deformation depends on the
capillary number and on the volume fraction of the inner
membrane. The computational framework's parallel performance
in this setting is evaluated and future development lessons
are discussed.},
Doi = {10.1016/j.procs.2017.05.209},
Key = {fds328446}
}
@article{fds326839,
Author = {Laurence, TA and Ly, S and Fong, E and Shusteff, M and Randles, A and Gounley, J and Draeger, E},
Title = {Using stroboscopic flow imaging to validate large-scale
computational fluid dynamics simulations},
Journal = {Progress in Biomedical Optics and Imaging - Proceedings of
SPIE},
Volume = {10076},
Publisher = {SPIE},
Year = {2017},
Month = {January},
ISBN = {9781510605930},
Abstract = {The utility and accuracy of computational modeling often
requires direct validation against experimental
measurements. The work presented here is motivated by taking
a combined experimental and computational approach to
determine the ability of large-scale computational fluid
dynamics (CFD) simulations to understand and predict the
dynamics of circulating tumor cells in clinically relevant
environments. We use stroboscopic light sheet fluorescence
imaging to track the paths and measure the velocities of
fluorescent microspheres throughout a human aorta model.
Performed over complex physiologicallyrealistic 3D
geometries, large data sets are acquired with microscopic
resolution over macroscopic distances.},
Doi = {10.1117/12.2253319},
Key = {fds326839}
}
@article{fds326715,
Author = {Dabagh, M and Jalali, P and Butler, PJ and Randles, A and Tarbell,
JM},
Title = {Mechanotransmission in endothelial cells subjected to
oscillatory and multi-directional shear flow.},
Journal = {Journal of the Royal Society, Interface},
Volume = {14},
Number = {130},
Pages = {20170185},
Year = {2017},
Month = {May},
Abstract = {Local haemodynamics are linked to the non-uniform
distribution of atherosclerosic lesions in arteries. Low and
oscillatory (reversing in the axial flow direction) wall
shear stress (WSS) induce inflammatory responses in
endothelial cells (ECs) mediating disease localization. The
objective of this study is to investigate computationally
how the flow direction (reflected in WSS variation on the EC
surface over time) influences the forces experienced by
structural components of ECs that are believed to play
important roles in mechanotransduction. A three-dimensional,
multi-scale, multi-component, viscoelastic model of focally
adhered ECs is developed, in which oscillatory WSS
(reversing or non-reversing) parallel to the principal flow
direction, or multi-directional oscillatory WSS with
reversing axial and transverse components are applied over
the EC surface. The computational model includes the
glycocalyx layer, actin cortical layer, nucleus,
cytoskeleton, focal adhesions (FAs), stress fibres and
adherens junctions (ADJs). We show the distinct effects of
atherogenic flow profiles (reversing unidirectional flow and
reversing multi-directional flow) on subcellular structures
relative to non-atherogenic flow (non-reversing flow).
Reversing flow lowers stresses and strains due to
viscoelastic effects, and multi-directional flow alters
stress on the ADJs perpendicular to the axial flow
direction. The simulations predict forces on integrins, ADJ
filaments and other substructures in the range that activate
mechanotransduction.},
Doi = {10.1098/rsif.2017.0185},
Key = {fds326715}
}
@article{fds328038,
Author = {Gounley, J and Vardhan, M and Randles, A},
Title = {A computational framework to assess the influence of changes
in vascular geometry on blood flow},
Journal = {PASC 2017 - Proceedings of the Platform for Advanced
Scientific Computing Conference},
Publisher = {ACM Press},
Year = {2017},
Month = {June},
ISBN = {9781450350624},
Abstract = {Many vascular abnormalities, such as aneurysms or stenoses,
develop gradually over time. In the early stages of their
development, they require monitoring but do not pose
sufficient risk to the patient for a clinician to recommend
invasive treatment. With a better understanding of the
interplay between hemodynamic factors and changes in blood
vessel geometry, there is an opportunity to improve clinical
care by earlier identification of aneurysms or stenoses with
significant potential for further development. Computational
fluid dynamics has shown great promise for investigating
this interplay and identifying the associated underlying
mechanisms, by using patient-derived geometries and
modifying them to represent potential evolution of the
vascular disease. However, a general, extensible framework
for comparing simulation results from different vascular
geometries in a direct, quantitative manner does not
currently exist. As a first step toward the development of
such a framework, we present a method for quantifying the
relationship between changes in vascular geometry and
hemodynamic factors, such as wall shear stress. We apply
this framework to study the correlation between wall shear
stress and geometric changes in two opposite settings: When
flow properties are associated with consequent changes in
the vascular geometry, as in a thoracic aortic aneurysm, and
when geometric changes alter the flow, as in a worsening
aortic stenosis.},
Doi = {10.1145/3093172.3093227},
Key = {fds328038}
}
@article{fds329286,
Author = {Randles, A and Frakes, DH and Leopold, JA},
Title = {Computational Fluid Dynamics and Additive Manufacturing to
Diagnose and Treat Cardiovascular Disease.},
Journal = {Trends in biotechnology},
Volume = {35},
Number = {11},
Pages = {1049-1061},
Year = {2017},
Month = {November},
Abstract = {Noninvasive engineering models are now being used for
diagnosing and planning the treatment of cardiovascular
disease. Techniques in computational modeling and additive
manufacturing have matured concurrently, and results from
simulations can inform and enable the design and
optimization of therapeutic devices and treatment
strategies. The emerging synergy between large-scale
simulations and 3D printing is having a two-fold benefit:
first, 3D printing can be used to validate the complex
simulations, and second, the flow models can be used to
improve treatment planning for cardiovascular disease. In
this review, we summarize and discuss recent methods and
findings for leveraging advances in both additive
manufacturing and patient-specific computational modeling,
with an emphasis on new directions in these fields and
remaining open questions.},
Doi = {10.1016/j.tibtech.2017.08.008},
Key = {fds329286}
}
@article{fds333543,
Author = {Rafat, M and Stone, HA and Auguste, DT and Dabagh, M and Randles, A and Heller, M and Rabinov, JD},
Title = {Impact of diversity of morphological characteristics and
Reynolds number on local hemodynamics in basilar
aneurysms},
Journal = {AIChE Journal},
Volume = {64},
Number = {7},
Pages = {2792-2802},
Publisher = {WILEY},
Year = {2018},
Month = {July},
Abstract = {Morphological and hemodynamic parameters have been suggested
to affect the rupture of cerebral aneurysms, but detailed
mechanisms of rupture are poorly understood. The purpose of
our study is to determine criteria for predicting the risk
of aneurysm rupture, which is critical for improved patient
management. Existing aneurysm hemodynamics studies generally
evaluate limited geometries or Reynolds numbers (Re), which
are difficult to apply to a wide range of patient-specific
cases. Association between hemodynamic characteristics and
morphology is focused. Several two-dimensional (2D) and
three-dimensional (3D) idealized and physiological
geometries is assessed to characterize the hemodynamic
landscape between flow patterns. The impact of morphology on
velocity and wall shear stress (WSS) profiles were
evaluated. Slight changes in aneurysm geometry is found or
Re result in significant changes in the hemodynamic and WSS
profiles. Our systematic mapping and nondimensional analysis
qualitatively identify hemodynamic conditions that may
predispose aneurysms to rupture. © 2018 American Institute
of Chemical Engineers AIChE J, 64: 2792–2802,
2018.},
Doi = {10.1002/aic.16091},
Key = {fds333543}
}
@article{fds342168,
Author = {Vardhan, M and Das, A and Gouruev, J and Randles,
A},
Title = {Computational fluid modeling to understand the role of
anatomy in bifurcation lesion disease},
Journal = {Proceedings - 25th IEEE International Conference on High
Performance Computing Workshops, HiPCW 2018},
Pages = {56-64},
Year = {2018},
Month = {July},
ISBN = {9781728101149},
Abstract = {Background: Treatment of bifurcation lesion disease is
complex with limited studies that describe the influence of
lesion anatomy on clinical outcomes. Hypothesis:
Computational simulations can be used to understand the
interplay between morphological characteristics of lesion
and clinical diagnostic metrics. Methods: Geometric
modifications along the bifurcation in a patient-derived
left coronary artery were made to incorporate unique
combination of anatomic features: curvature, length and
occlusion severity. The resulting geometries were used to
perform CFD simulations using physiological flow parameters.
Three diagnostic metrics, resting gradient, instantaneous
wave free ratio (iFR) and diastolic-systolic velocity ratio
(DSVR), were computed from the simulations. Results: We
report occlusion severity to be an independent predictor for
lower resting gradient and iFR values, whereas lesion length
and curvature did not yield dramatic changes in iFR and
resting gradient. Our results suggest that DSVR is more
sensitive to nuanced flow disturbances; however, it may be
complex to derive direct correspondence to disease severity
relative to resting gradient and iFR. Conclusion: Spatial
lesion characteristics can be used to determine diseased
bifurcation cases that may lead to interventional
complications.},
Doi = {10.1109/HiPCW.2018.8634225},
Key = {fds342168}
}
@article{fds337736,
Author = {Herschlag, G and Lee, S and Vetter, JS and Randles,
A},
Title = {GPU data access on complex geometries for D3Q19 lattice
boltzmann method},
Journal = {Proceedings - 2018 IEEE 32nd International Parallel and
Distributed Processing Symposium, IPDPS 2018},
Pages = {825-834},
Publisher = {IEEE},
Year = {2018},
Month = {August},
ISBN = {9781538643686},
Abstract = {GPU performance of the lattice Boltzmann method (LBM)
depends heavily on memory access patterns. When LBM is
advanced with GPUS on complex computational domains,
geometric data is typically accessed indirectly, and lattice
data is typically accessed lexicographically in the
Structure of Array (SoA) layout. Although there are a
variety of existing access patterns beyond the typical
choices, no study has yet examined the relative efficacy
between them. Here, we compare a suite of memory access
schemes via empirical testing and performance modeling. We
find strong evidence that semi-direct addressing is the
superior addressing scheme for the majority of cases
examined: Semi-direct addressing increases computational
speed and often reduces memory consumption. For lattice
layout, we find that the Collected Structure of Arrays
(CSoA) layout outperforms the SoA layout. When compared to
state-of-The-Art practices, our recommended addressing
modifications lead to performance gains between 10-40%
across different complex geometries, fluid volume fractions,
and resolutions. The modifications also lead to a decrease
in memory consumption by as much as 17%. Having discovered
these improvements, we examine a highly resolved arterial
geometry on a leadership class system. On this system we
present the first near-optimal strong results for LBM with
arterial geometries run on GPUS. We also demonstrate that
the above recommendations remain valid for large scale, many
device simulations, which leads to an increased
computational speed and average memory usage reductions. To
understand these observations, we employ performance
modeling which reveals that semi-direct methods outperform
indirect methods due to a reduced number of total
loads/stores in memory, and that CSoA outperforms SoA and
bundling due to improved caching behavior.},
Doi = {10.1109/IPDPS.2018.00092},
Key = {fds337736}
}
@article{fds339258,
Author = {Hegele, LA and Scagliarini, A and Sbragaglia, M and Mattila, KK and Philippi, PC and Puleri, DF and Gounley, J and Randles,
A},
Title = {High-Reynolds-number turbulent cavity flow using the lattice
Boltzmann method},
Journal = {Physical Review E},
Volume = {98},
Number = {4},
Publisher = {American Physical Society (APS)},
Year = {2018},
Month = {October},
Abstract = {We present a boundary condition scheme for the lattice
Boltzmann method that has significantly improved stability
for modeling turbulent flows while maintaining excellent
parallel scalability. Simulations of a three-dimensional
lid-driven cavity flow are found to be stable up to the
unprecedented Reynolds number Re=5×104 for this setup.
Excellent agreement with energy balance equations,
computational and experimental results are shown. We
quantify rises in the production of turbulence and turbulent
drag, and determine peak locations of turbulent
production.},
Doi = {10.1103/PhysRevE.98.043302},
Key = {fds339258}
}
@article{fds341923,
Author = {Dabagh, M and Randles, A},
Title = {Role of deformable cancer cells on wall shear
stress-associated-VEGF secretion by endothelium in
microvasculature.},
Journal = {PloS one},
Volume = {14},
Number = {2},
Pages = {e0211418},
Year = {2019},
Month = {January},
Abstract = {Endothelial surface layer (glycocalyx) is the major
physiological regulator of tumor cell adhesion to
endothelium. Cancer cells express vascular endothelial
growth factor (VEGF) which increases the permeability of a
microvessel wall by degrading glycocalyx. Endothelial cells
lining large arteries have also been reported, in vitro and
in vivo, to mediate VEGF expression significantly under
exposure to high wall shear stress (WSS) > 0.6 Pa. The
objective of the present study is to explore whether local
hemodynamic conditions in the vicinity of a migrating
deformable cancer cell can influence the function of
endothelial cells to express VEGF within the
microvasculature. A three-dimensional model of deformable
cancer cells (DCCs) migrating within a capillary is
developed by applying a massively parallel hemodynamics
application to simulate the fluid-structure interaction
between the DCC and fluid surrounding the DCC. We study how
dynamic interactions between the DCC and its local
microenvironment affect WSS exposed on endothelium, under
physiological conditions of capillaries with different
diameters and flow conditions. Moreover, we quantify the
area of endothelium affected by the DCC. Our results show
that the DCC alters local hemodynamics in its vicinity up to
an area as large as 40 times the cancer cell lateral
surface. In this area, endothelium experiences high WSS
values in the range of 0.6-12 Pa. Endothelial cells exposed
to this range of WSS have been reported to express VEGF.
Furthermore, we demonstrate that stiffer cancer cells expose
higher WSS on the endothelium. A strong impact of cell
stiffness on its local microenvironment is observed in
capillaries with diameters <16 μm. WSS-induced-VEGF by
endothelium represents an important potential mechanism for
cancer cell adhesion and metastasis in the microvasculature.
This work serves as an important first step in understanding
the mechanisms driving VEGF-expression by endothelium and
identifying the underlying mechanisms of glycocalyx
degradation by endothelium in microvasculature. The
identification of angiogenesis factors involved in early
stages of cancer cell-endothelium interactions and
understanding their regulation will help, first to develop
anti-angiogenic strategies applied to diagnostic studies and
therapeutic interventions, second to predict accurately
where different cancer cell types most likely adhere in
microvasculature, and third to establish accurate criteria
predisposing the cancer metastasis.},
Doi = {10.1371/journal.pone.0211418},
Key = {fds341923}
}
@article{fds339595,
Author = {Gounley, J and Draeger, EW and Oppelstrup, T and Krauss, WD and Gunnels,
JA and Chaudhury, R and Nair, P and Frakes, D and Leopold, JA and Randles,
A},
Title = {Computing the ankle-brachial index with parallel
computational fluid dynamics.},
Journal = {Journal of biomechanics},
Volume = {82},
Pages = {28-37},
Year = {2019},
Month = {January},
Abstract = {The ankle-brachial index (ABI), a ratio of arterial blood
pressure in the ankles and upper arms, is used to diagnose
and monitor circulatory conditions such as coarctation of
the aorta and peripheral artery disease. Computational
simulations of the ABI can potentially determine the
parameters that produce an ABI indicative of ischemia or
other abnormalities in blood flow. However, 0- and 1-D
computational methods are limited in describing a 3-D
patient-derived geometry. Thus, we present a massively
parallel framework for computational fluid dynamics (CFD)
simulations in the full arterial system. Using the lattice
Boltzmann method to solve the Navier-Stokes equations, we
employ highly parallelized and scalable methods to generate
the simulation domain and efficiently distribute the
computational load among processors. For the first time, we
compute an ABI with 3-D CFD. In this proof-of-concept study,
we investigate the dependence of ABI on the presence of
stenoses, or narrowed regions of the arteries, by directly
modifying the arterial geometry. As a result, our framework
enables the computation a hemodynamic factor characterizing
flow at the scale of the full arterial system, in a manner
that is extensible to patient-specific imaging data and
holds potential for treatment planning.},
Doi = {10.1016/j.jbiomech.2018.10.007},
Key = {fds339595}
}
@article{fds344696,
Author = {Gounley, J and Draeger, EW and Randles, A},
Title = {Immersed Boundary Method Halo Exchange in a Hemodynamics
Application},
Journal = {Lecture Notes in Computer Science (including subseries
Lecture Notes in Artificial Intelligence and Lecture Notes
in Bioinformatics)},
Volume = {11536 LNCS},
Pages = {441-455},
Year = {2019},
Month = {January},
ISBN = {9783030227333},
Abstract = {In recent years, highly parallelized simulations of blood
flow resolving individual blood cells have been
demonstrated. Simulating such dense suspensions of
deformable particles in flow often involves a partitioned
fluid-structure interaction (FSI) algorithm, with separate
solvers for Eulerian fluid and Lagrangian cell grids, plus a
solver - e.g., immersed boundary method - for their
interaction. Managing data motion in parallel FSI
implementations is increasingly important, particularly for
inhomogeneous systems like vascular geometries. In this
study, we evaluate the influence of Eulerian and Lagrangian
halo exchanges on efficiency and scalability of a
partitioned FSI algorithm for blood flow. We describe an
MPI+OpenMP implementation of the immersed boundary method
coupled with lattice Boltzmann and finite element methods.
We consider how communication and recomputation costs
influence the optimization of halo exchanges with respect to
three factors: immersed boundary interaction distance, cell
suspension density, and relative fluid/cell solver
costs.},
Doi = {10.1007/978-3-030-22734-0_32},
Key = {fds344696}
}
@article{fds337027,
Author = {Gounley, J and Vardhan, M and Randles, A},
Title = {A Framework for Comparing Vascular Hemodynamics at Different
Points in Time.},
Journal = {Computer physics communications},
Volume = {235},
Pages = {1-8},
Year = {2019},
Month = {February},
Abstract = {Computational simulations of blood flow contribute to our
understanding of the interplay between vascular geometry and
hemodynamics. With an improved understanding of this
interplay from computational fluid dynamics (CFD), there is
potential to improve basic research and the targeting of
clinical care. One avenue for further analysis concerns the
influence of time on the vascular geometries used in CFD
simulations. The shape of blood vessels changes frequently,
as in deformation within the cardiac cycle, and over long
periods of time, such as the development of a stenotic
plaque or an aneurysm. These changes in the vascular
geometry will, in turn, influence flow within these blood
vessels. By performing CFD simulations in geometries
representing the blood vessels at different points in time,
the interplay of these geometric changes with hemodynamics
can be quantified. However, performing CFD simulations on
different discrete grids leads to an additional challenge:
how does one directly and quantitatively compare simulation
results from different vascular geometries? In a previous
study, we began to address this problem by proposing a
method for the simplified case where the two geometries
share a common centerline. In this companion paper, we
generalize this method to address geometric changes which
alter the vessel centerline. We demonstrate applications of
this method to the study of wall shear stress in the left
coronary artery. First, we compute the difference in wall
shear stress between simulations using vascular geometries
derived from patient imaging data at two points in the
cardiac cycle. Second, we evaluate the relationship between
changes in wall shear stress and the progressive development
of a coronary aneurysm or stenosis.},
Doi = {10.1016/j.cpc.2018.05.014},
Key = {fds337027}
}
@article{fds343372,
Author = {Grigoryan, B and Paulsen, SJ and Corbett, DC and Sazer, DW and Fortin,
CL and Zaita, AJ and Greenfield, PT and Calafat, NJ and Gounley, JP and Ta,
AH and Johansson, F and Randles, A and Rosenkrantz, JE and Louis-Rosenberg, JD and Galie, PA and Stevens, KR and Miller,
JS},
Title = {Multivascular networks and functional intravascular
topologies within biocompatible hydrogels.},
Journal = {Science (New York, N.Y.)},
Volume = {364},
Number = {6439},
Pages = {458-464},
Year = {2019},
Month = {May},
Abstract = {Solid organs transport fluids through distinct vascular
networks that are biophysically and biochemically entangled,
creating complex three-dimensional (3D) transport regimes
that have remained difficult to produce and study. We
establish intravascular and multivascular design freedoms
with photopolymerizable hydrogels by using food dye
additives as biocompatible yet potent photoabsorbers for
projection stereolithography. We demonstrate monolithic
transparent hydrogels, produced in minutes, comprising
efficient intravascular 3D fluid mixers and functional
bicuspid valves. We further elaborate entangled vascular
networks from space-filling mathematical topologies and
explore the oxygenation and flow of human red blood cells
during tidal ventilation and distension of a proximate
airway. In addition, we deploy structured biodegradable
hydrogel carriers in a rodent model of chronic liver injury
to highlight the potential translational utility of this
materials innovation.},
Doi = {10.1126/science.aav9750},
Key = {fds343372}
}
@article{fds373480,
Author = {Chen, K and Breitner, S and Wolf, K and Hampel, R and Meisinger, C and Heier, M and von Scheidt, W and Kuch, B and Peters, A and Schneider, A and KORA Study Group},
Title = {Temporal variations in the triggering of myocardial
infarction by air temperature in Augsburg, Germany,
1987-2014.},
Journal = {European heart journal},
Volume = {40},
Number = {20},
Pages = {1600-1608},
Year = {2019},
Month = {May},
Abstract = {<h4>Aims</h4>The association between air temperature and
mortality has been shown to vary over time, but evidence of
temporal changes in the risk of myocardial infarction (MI)
is lacking. We aimed to estimate the temporal variations in
the association between short-term exposures to air
temperature and MI in the area of Augsburg,
Germany.<h4>Methods and results</h4>Over a 28-years period
from 1987 to 2014, a total of 27 310 cases of MI and
coronary deaths were recorded. Daily meteorological
parameters were measured in the study area. A
time-stratified case-crossover analysis with a distributed
lag non-linear model was used to estimate the risk of MI
associated with air temperature. Subgroup analyses were
performed to identify subpopulations with changing
susceptibility to air temperature. Results showed a
non-significant decline in cold-related MI risks.
Heat-related MI relative risk significantly increased from
0.93 [95% confidence interval (CI): 0.78-1.12] in 1987-2000
to 1.14 (95% CI: 1.00-1.29) in 2001-14. The same trend was
also observed for recurrent and non-ST-segment elevation MI
events. This increasing population susceptibility to heat
was more evident in patients with diabetes mellitus and
hyperlipidaemia. Future studies using multicentre MI
registries at different climatic, demographic, and
socioeconomic settings are warranted to confirm our
findings.<h4>Conclusion</h4>We found evidence of rising
population susceptibility to heat-related MI risk from 1987
to 2014, suggesting that exposure to heat should be
considered as an environmental trigger of MI, especially
under a warming climate.},
Doi = {10.1093/eurheartj/ehz116},
Key = {fds373480}
}
@article{fds343753,
Author = {Vardhan, M and Gounley, J and Chen, SJ and Kahn, AM and Leopold, JA and Randles, A},
Title = {The importance of side branches in modeling 3D hemodynamics
from angiograms for patients with coronary artery
disease.},
Journal = {Scientific reports},
Volume = {9},
Number = {1},
Pages = {8854},
Year = {2019},
Month = {June},
Abstract = {Genesis of atherosclerotic lesions in the human arterial
system is critically influenced by the fluid mechanics.
Applying computational fluid dynamic tools based on accurate
coronary physiology derived from conventional biplane
angiogram data may be useful in guiding percutaneous
coronary interventions. The primary objective of this study
is to build and validate a computational framework for
accurate personalized 3-dimensional hemodynamic simulation
across the complete coronary arterial tree and demonstrate
the influence of side branches on coronary hemodynamics by
comparing shear stress between coronary models with and
without these included. The proposed novel computational
framework based on biplane angiography enables significant
arterial circulation analysis. This study shows that models
that take into account flow through all side branches are
required for precise computation of shear stress and
pressure gradient whereas models that have only a subset of
side branches are inadequate for biomechanical studies as
they may overestimate volumetric outflow and shear stress.
This study extends the ongoing computational efforts and
demonstrates that models based on accurate coronary
physiology can improve overall fidelity of biomechanical
studies to compute hemodynamic risk-factors.},
Doi = {10.1038/s41598-019-45342-5},
Key = {fds343753}
}
@article{fds342379,
Author = {Feiger, B and Vardhan, M and Gounley, J and Mortensen, M and Nair, P and Chaudhury, R and Frakes, D and Randles, A},
Title = {Suitability of lattice Boltzmann inlet and outlet boundary
conditions for simulating flow in image-derived
vasculature.},
Journal = {International journal for numerical methods in biomedical
engineering},
Volume = {35},
Number = {6},
Pages = {e3198},
Year = {2019},
Month = {June},
Abstract = {The lattice Boltzmann method (LBM) is a popular alternative
to solving the Navier-Stokes equations for modeling blood
flow. When simulating flow using the LBM, several choices
for inlet and outlet boundary conditions exist. While
boundary conditions in the LBM have been evaluated in
idealized geometries, there have been no extensive
comparisons in image-derived vasculature, where the
geometries are highly complex. In this study, the Zou-He
(ZH) and finite difference (FD) boundary conditions were
evaluated in image-derived vascular geometries by comparing
their stability, accuracy, and run times. The boundary
conditions were compared in four arteries: a coarctation of
the aorta, dissected aorta, femoral artery, and left
coronary artery. The FD boundary condition was more stable
than ZH in all four geometries. In general, simulations
using the ZH and FD method showed similar convergence rates
within each geometry. However, the ZH method proved to be
slightly more accurate compared with experimental flow using
three-dimensional printed vasculature. The total run times
necessary for simulations using the ZH boundary condition
were significantly higher as the ZH method required a larger
relaxation time, grid resolution, and number of time steps
for a simulation representing the same physiological time.
Finally, a new inlet velocity profile algorithm is presented
for complex inlet geometries. Overall, results indicated
that the FD method should generally be used for large-scale
blood flow simulations in image-derived vasculature
geometries. This study can serve as a guide to researchers
interested in using the LBM to simulate blood
flow.},
Doi = {10.1002/cnm.3198},
Key = {fds342379}
}
@article{fds342167,
Author = {Lee, S and Gounley, J and Randles, A and Vetter, JS},
Title = {Performance portability study for massively parallel
computational fluid dynamics application on scalable
heterogeneous architectures},
Journal = {Journal of Parallel and Distributed Computing},
Volume = {129},
Pages = {1-13},
Year = {2019},
Month = {July},
Abstract = {Patient-specific hemodynamic simulations have the potential
to greatly improve both the diagnosis and treatment of a
variety of vascular diseases. Portability will enable wider
adoption of computational fluid dynamics (CFD) applications
in the biomedical research community and targeting to
platforms ideally suited to different vascular regions. In
this work, we present a case study in performance
portability that assesses (1) the ease of porting an MPI
application optimized for one specific architecture to new
platforms using variants of hybrid MPI+X programming
models; (2) performance portability seen when simulating
blood flow in three different vascular regions on diverse
heterogeneous architectures; (3) model-based performance
prediction for future architectures; and (4) performance
scaling of the hybrid MPI+X programming on parallel
heterogeneous systems. We discuss the lessons learned in
porting HARVEY, a massively parallel CFD application, from
traditional multicore CPUs to diverse heterogeneous
architectures ranging from NVIDIA/AMD GPUs to Intel MICs and
Altera FPGAs.},
Doi = {10.1016/j.jpdc.2019.02.005},
Key = {fds342167}
}
@article{fds345465,
Author = {Dabagh, M and Nair, P and Gounley, J and Frakes, D and Gonzalez, LF and Randles, A},
Title = {Hemodynamic and morphological characteristics of a growing
cerebral aneurysm.},
Journal = {Neurosurg Focus},
Volume = {47},
Number = {1},
Pages = {E13},
Year = {2019},
Month = {July},
Abstract = {The growth of cerebral aneurysms is linked to local
hemodynamic conditions, but the driving mechanisms of the
growth are poorly understood. The goal of this study was to
examine the association between intraaneurysmal hemodynamic
features and areas of aneurysm growth, to present the key
hemodynamic parameters essential for an accurate prediction
of the growth, and to gain a deeper understanding of the
underlying mechanisms. Patient-specific images of a growing
cerebral aneurysm in 3 different growth stages acquired over
a period of 40 months were segmented and reconstructed. A
unique aspect of this patient-specific case study was that
while one side of the aneurysm stayed stable, the other side
continued to grow. This unique case enabled the authors to
examine their aims in the same patient with parent and
daughter arteries under the same inlet flow conditions.
Pulsatile flow in the aneurysm models was simulated using
computational fluid dynamics and was validated with in vitro
experiments using particle image velocimetry measurements.
The authors' detailed analysis of intrasaccular hemodynamics
linked the growing regions of aneurysms to flow
instabilities and complex vortex structures. Extremely low
velocities were observed at or around the center of the
unstable vortex structure, which matched well with the
growing regions of the studied cerebral aneurysm.
Furthermore, the authors observed that the aneurysm wall
regions with a growth greater than 0.5 mm coincided with
wall regions of lower (< 0.5 Pa) time-averaged wall shear
stress (TAWSS), lower instantaneous (< 0.5 Pa) wall shear
stress (WSS), and high (> 0.1) oscillatory shear index
(OSI). To determine which set of parameters can best
identify growing and nongrowing aneurysms, the authors
performed statistical analysis for consecutive stages of the
growing CA. The results demonstrated that the combination of
TAWSS and the distance from the center of the vortical
structure has the highest sensitivity and positive
predictive value, and relatively high specificity and
negative predictive value. These findings suggest that an
unstable, recirculating flow structure within the aneurysm
sac created in the region adjacent to the aneurysm wall with
low TAWSS may be introduced as an accurate criterion to
explain the hemodynamic conditions predisposing the aneurysm
to growth. The authors' findings are based on one patient's
data set, but the study lays out the justification for
future large-scale verification. The authors' findings can
assist clinicians in differentiating stable and growing
aneurysms during preinterventional planning.},
Doi = {10.3171/2019.4.FOCUS19195},
Key = {fds345465}
}
@article{fds373479,
Author = {Chen, K and Breitner, S and Wolf, K and Rai, M and Meisinger, C and Heier,
M and Kuch, B and Peters, A and Schneider, A},
Title = {Projection of Temperature-Related Myocardial Infarction in
Augsburg, Germany: Moving on From the Paris Agreement on
Climate Change.},
Journal = {Deutsches Arzteblatt international},
Volume = {116},
Number = {31-32},
Pages = {521-527},
Year = {2019},
Month = {August},
Abstract = {<h4>Background</h4>Substantial efforts are required to limit
global warming to under 2 °C, with 1.5 °C as the target
(Paris Agreement goal). We set out to project future
temperature-related myocardial infarction (MI) events in
Augsburg, Germany, at increases in warming of 1.5 °C, 2
°C, and 3 °C.<h4>Methods</h4>Using daily time series of MI
cases and temperature projections under two climate
scenarios, we projected changes in temperature-related MIs
at different increases in warming, assuming no changes in
population structure or level of adaptation.<h4>Results</h4>In
a low-emission scenario that limits warming to below 2 °C
throughout the 21st century, temperature-related MI cases
will decrease slightly by -6 (confidence interval -60; 50)
per decade at 1.5 °C of warming. In a high-emission
scenario going beyond the Paris Agreement goals,
temperature-related MI cases will increase by 18 (-64; 117)
and 63 (-83; 257) per decade with warming of 2 °C and 3
°C, respectively.<h4>Conclusion</h4>The future burden of
temperature-related MI events in Augsburg at 2 °C and 3 °C
of warming will be greater than at 1.5 °C. Fulfilling the
Paris Agreement goal of limiting global warming to no more
than 1.5 °C is therefore essential to avoid additional MI
events due to climate change.},
Doi = {10.3238/arztebl.2019.0521},
Key = {fds373479}
}
@article{fds347207,
Author = {Herschlag, G and Gounley, J and Roychowdhury, S and Draeger, EW and Randles, A},
Title = {Multi-physics simulations of particle tracking in arterial
geometries with a scalable moving window
algorithm},
Journal = {Proceedings - IEEE International Conference on Cluster
Computing, ICCC},
Volume = {2019-September},
Year = {2019},
Month = {September},
ISBN = {9781728147345},
Abstract = {In arterial systems, cancer cell trajectories determine
metastatic cancer locations; similarly, particle
trajectories determine drug delivery distribution.
Predicting trajectories is challenging, as the dynamics are
affected by local interactions with red blood cells, complex
hemodynamic flow structure, and downstream factors such as
stenoses or blockages. Direct simulation is not possible, as
a single simulation of a large arterial domain with explicit
red blood cells is currently intractable on even the largest
supercomputers. To overcome this limitation, we present a
multi-physics adaptive window algorithm, in which individual
red blood cells are explicitly modeled in a small region of
interest moving through a coupled arterial fluid domain. We
describe the coupling between the window and fluid domains,
including automatic insertion and deletion of explicit cells
and dynamic tracking of cells of interest by the window. We
show that this algorithm scales efficiently on heterogeneous
architectures and enables us to perform large,
highly-resolved particle-tracking simulations that would
otherwise be intractable.},
Doi = {10.1109/CLUSTER.2019.8891041},
Key = {fds347207}
}
@article{fds349556,
Author = {Ames, J and Rizzi, S and Insley, J and Patel, S and Hernández, B and Draeger, EW and Randles, A},
Title = {Low-Overhead in Situ Visualization Using Halo
Replay},
Journal = {2019 IEEE 9th Symposium on Large Data Analysis and
Visualization, LDAV 2019},
Pages = {16-26},
Year = {2019},
Month = {October},
ISBN = {9781728126050},
Abstract = {In situ visualization and analysis is of increasing
importance as the compute and I/O gap further widens with
the advance to exascale capable computing. Yet, in situ
methods impose resource constraints leading to the difficult
task of balancing simulation code performance and the
quality of analysis. Applications with tightly-coupled in
situ visualization often achieve performance through spatial
and temporal downsampling, a tradeoff which risks not
capturing transient phenomena at sufficient fidelity.
Determining a priori visualization parameters such as
sampling rate is difficult without time and resource
intensive experimentation. We present a method for reducing
resource contention between in situ visualization and
stencil codes on heterogeneous systems. This method permits
full resolution replay through recording halos and the
communication-free reconstruction of interior values
uncoupled from the main simulation. We apply this method in
the computational fluid dynamics (CFD) code HARVEY [1] on
the Summit supercomputer. We demonstrate minimal-overhead,
in situ visualization relative to simulation alone, and
compare the Halo Replay performance to tightly-coupled in
situ approaches.},
Doi = {10.1109/LDAV48142.2019.8944265},
Key = {fds349556}
}
@article{fds347666,
Author = {Vardhan, M and Gounley, J and Hegele, L and Draeger, EW and Randles,
A},
Title = {Moment representation in the lattice Boltzmann method on
massively parallel hardware},
Journal = {International Conference for High Performance Computing,
Networking, Storage and Analysis, SC},
Year = {2019},
Month = {November},
ISBN = {9781450362290},
Abstract = {The widely-used lattice Boltzmann method (LBM) for
computational fluid dynamics is highly scalable, but also
significantly memory bandwidth-bound on current
architectures. This paper presents a new regularized LBM
implementation that reduces the memory footprint by only
storing macroscopic, moment-based data. We show that the
amount of data that must be stored in memory during a
simulation is reduced by up to 47%. We also present a
technique for cache-aware data re-utilization and show that
optimizing cache utilization to limit data motion results in
a similar improvement in time to solution. These new
algorithms are implemented in the hemodynamics solver HARVEY
and demonstrated using both idealized and realistic
biological geometries. We develop a performance model for
the moment representation algorithm and evaluate the
performance on Summit.},
Doi = {10.1145/3295500.3356204},
Key = {fds347666}
}
@article{fds358276,
Author = {Dabagh, M and Gounley, J and Randles, A},
Title = {Localization of Rolling and Firm-Adhesive Interactions
Between Circulating Tumor Cells and the Microvasculature
Wall.},
Journal = {Cellular and molecular bioengineering},
Volume = {13},
Number = {2},
Pages = {141-154},
Year = {2020},
Month = {April},
Abstract = {<h4>Introduction</h4>The adhesion of tumor cells to vessel
wall is a critical stage in cancer metastasis. Firm adhesion
of cancer cells is usually followed by their extravasation
through the endothelium. Despite previous studies
identifying the influential parameters in the adhesive
behavior of the cancer cell to a planer substrate, less is
known about the interactions between the cancer cell and
microvasculature wall and whether these interactions exhibit
organ specificity. The objective of our study is to
characterize sizes of microvasculature where a deformable
circulating cell (DCC) would firmly adhere or roll over the
wall, as well as to identify parameters that facilitate such
firm adherence and underlying mechanisms driving adhesive
interactions.<h4>Methods</h4>A three-dimensional model of
DCCs is applied to simulate the fluid-structure interaction
between the DCC and surrounding fluid. A dynamic adhesion
model, where an adhesion molecule is modeled as a spring, is
employed to represent the stochastic receptor-ligand
interactions using kinetic rate expressions.<h4>Results</h4>Our
results reveal that both the cell deformability and low
shear rate of flow promote the firm adhesion of DCC in small
vessels ( < 10 μ m ). Our findings suggest that
ligand-receptor bonds of PSGL-1-P-selectin may lead to firm
adherence of DCC in smaller vessels and rolling-adhesion of
DCC in larger ones where cell velocity drops to facilitate
the activation of integrin-ICAM-1 bonds.<h4>Conclusions</h4>Our
study provides a framework to predict accurately where
different DCC-types are likely to adhere firmly in
microvasculature and to establish the criteria predisposing
cancer cells to such firm adhesion.},
Doi = {10.1007/s12195-020-00610-7},
Key = {fds358276}
}
@article{fds348929,
Author = {Feiger, B and Kochar, A and Gounley, J and Bonadonna, D and Daneshmand,
M and Randles, A},
Title = {Determining the impacts of venoarterial extracorporeal
membrane oxygenation on cerebral oxygenation using a
one-dimensional blood flow simulator.},
Journal = {Journal of biomechanics},
Volume = {104},
Pages = {109707},
Year = {2020},
Month = {May},
Abstract = {Venoarterial extracorporeal membrane oxygenation (VA-ECMO)
is a mechanical system that provides rapid and short-term
support for patients with cardiac failure. In many patients,
pulmonary function is also impaired, resulting in
poorly-oxygenated cardiac outflow competing against
well-oxygenated VA-ECMO outflow, a condition known as
North-South syndrome. North-South syndrome is a primary
concern because of its potential to cause cerebral hypoxia,
which has a critical influence on neurological complications
often seen in this patient population. In order to reduce
ischemic neurological complications, it is important to
understand how clinical decisions regarding VA-ECMO
parameters influence blood oxygenation. Here, we studied the
impacts of flow rate and cannulation site on oxygenation
using a one-dimensional (1D) model to simulate blood flow.
Our model was initially tested by comparing blood flow
results to those observed from experimental work in VA-ECMO
patients. The 1D model was combined with a two-phase flow
model to simulate oxygenation. Additionally, the influence
of various other clinician-tunable parameters on oxygenation
in the common carotid arteries (CCAs) were tested,
including, blood viscosity, cannula position within the
insertion artery, heart rate, and systemic vascular
resistance (SVR), as well as geometrical changes such as
arterial radius and length. Our results indicated that blood
oxygenation to the brain strongly depended on the cannula
insertion site and the VA-ECMO flow rate with a weaker but
potentially significant dependence on arterial radius.
During femoral cannulation, VA-ECMO flow rates greater than
~4.9L/min were needed to perfuse the CCAs. However, axillary
and central cannulation began to perfuse the CCAs at
significantly lower flow (~1L/min). These results may help
explain the incidence of cerebral hypoxia in this patient
population and the common need to change cannulation
strategies during treatment to address this clinical
problem. While this work describes patient-averaged results,
determining these relationships between VA-ECMO parameters
and cerebral hypoxia is an important step towards future
work to develop patient-specific models that clinicians can
use to improve outcomes.},
Doi = {10.1016/j.jbiomech.2020.109707},
Key = {fds348929}
}
@article{fds349705,
Author = {Shi, H and Ames, J and Randles, A},
Title = {Harvis: an interactive virtual reality tool for hemodynamic
modification and simulation},
Journal = {Journal of Computational Science},
Volume = {43},
Year = {2020},
Month = {May},
Abstract = {Cardiovascular disease (CVD) affects more than 90 million
adults in the United States. In recent years, computational
hemodynamic models have helped improve our understanding of
CVD progression; however, such research workflows can be
challenging and unintuitive to operate. We thus developed
Harvis, a software platform with a flexible GUI for
performing vascular simulations and a VR-capable interface
for geometry modification and flow visualization. The aim of
Harvis is to streamline and integrate this process for
research use and future clinical applications. We also
present a user study (n=26) that evaluates interaction with
vascular modeling on 2D and VR displays.},
Doi = {10.1016/j.jocs.2020.101091},
Key = {fds349705}
}
@article{fds350121,
Author = {Feiger, B and Gounley, J and Adler, D and Leopold, JA and Draeger, EW and Chaudhury, R and Ryan, J and Pathangey, G and Winarta, K and Frakes, D and Michor, F and Randles, A},
Title = {Accelerating massively parallel hemodynamic models of
coarctation of the aorta using neural networks.},
Journal = {Scientific reports},
Volume = {10},
Number = {1},
Pages = {9508},
Year = {2020},
Month = {June},
Abstract = {Comorbidities such as anemia or hypertension and
physiological factors related to exertion can influence a
patient's hemodynamics and increase the severity of many
cardiovascular diseases. Observing and quantifying
associations between these factors and hemodynamics can be
difficult due to the multitude of co-existing conditions and
blood flow parameters in real patient data. Machine
learning-driven, physics-based simulations provide a means
to understand how potentially correlated conditions may
affect a particular patient. Here, we use a combination of
machine learning and massively parallel computing to predict
the effects of physiological factors on hemodynamics in
patients with coarctation of the aorta. We first validated
blood flow simulations against in vitro measurements in
3D-printed phantoms representing the patient's vasculature.
We then investigated the effects of varying the degree of
stenosis, blood flow rate, and viscosity on two diagnostic
metrics - pressure gradient across the stenosis (ΔP) and
wall shear stress (WSS) - by performing the largest
simulation study to date of coarctation of the aorta (over
70 million compute hours). Using machine learning models
trained on data from the simulations and validated on two
independent datasets, we developed a framework to identify
the minimal training set required to build a predictive
model on a per-patient basis. We then used this model to
accurately predict ΔP (mean absolute error within 1.18
mmHg) and WSS (mean absolute error within 0.99 Pa) for
patients with this disease.},
Doi = {10.1038/s41598-020-66225-0},
Key = {fds350121}
}
@article{fds352317,
Author = {Roychowdhury, S and Gounley, J and Randles, A},
Title = {Evaluating the Influence of Hemorheological Parameters on
Circulating Tumor Cell Trajectory and Simulation
Time},
Journal = {Proceedings of the Platform for Advanced Scientific
Computing Conference, PASC 2020},
Year = {2020},
Month = {June},
ISBN = {9781450379939},
Abstract = {Extravasation of circulating tumor cells (CTCs) occurs
primarily in the microvasculature, where flow and cell
interactions significantly affect the blood rheology.
Capturing cell trajectory at this scale requires the
coupling of several interaction models, leading to increased
computational cost that scales as more cells are added or
the domain size is increased. In this work, we focus on
micro-scale vessels and study the influence of certain
hemorheological factors, including the presence of red blood
cell aggregation, hematocrit level, microvessel size, and
shear rate, on the trajectory of a circulating tumor cell.
We determine which of the aforementioned factors
significantly affect CTC motion and identify those which can
potentially be disregarded, thus reducing simulation time.
We measure the effect of these elements by studying the
radial CTC movement and runtime at various combinations of
these hemorheological parameters. To accurately capture
blood flow dynamics and single cell movement, we perform
high-fidelity hemodynamic simulations at a sub-micron
resolution using our in-house fluid dynamics solver, HARVEY.
We find that increasing hematocrit increases the likelihood
of tumor cell margination, which is exacerbated by the
presence of red blood cell aggregation. As microvessel
diameter increases, there is no major CTC movement towards
the wall; however, including aggregation causes the CTC to
marginate quicker as the vessel size increases. Finally, as
the shear rate is increased, the presence of aggregation has
a diminished effect on tumor cell margination.},
Doi = {10.1145/3394277.3401848},
Key = {fds352317}
}
@article{fds350120,
Author = {Cherian, J and Dabagh, M and Srinivasan, VM and Chen, S and Johnson, J and Wakhloo, A and Gupta, V and Macho, J and Randles, A and Kan,
P},
Title = {Balloon-Mounted Stents for Treatment of Refractory Flow
Diverting Device Wall Malapposition.},
Journal = {Operative neurosurgery (Hagerstown, Md.)},
Volume = {19},
Number = {1},
Pages = {37-42},
Year = {2020},
Month = {July},
Abstract = {<h4>Background</h4>As indications for flow diversion (FD)
have expanded, new challenges in deployment of flow
diverting devices (FDDs) have been encountered. We present 4
cases with aneurysms in which deployment of FDDs were
complicated by device malapposition and compromised opening
in regions of parent vessel stenosis. In all 4 cases, a
balloon-mounted stent was ultimately deployed within the
FDD.<h4>Objective</h4>To describe the use of balloon-mounted
stents (BMS) within FDDs for correction of flow-limiting
stenosis and device malapposition.<h4>Methods</h4>Patients
undergoing FD for treatment of aneurysms complicated by
refractory flow-limiting stenosis were identified through
multi-center retrospective review. Those cases requiring use
of BMS were identified. Further investigation in one of the
cases was performed with a simulated pulsatile blood flow
model.<h4>Results</h4>After attempts to perform balloon
angioplasty proved unsuccessful, BMS deployment successfully
opened the stenotic parent artery and improved FDD wall
apposition in all 4 cases. Simulated pulsatile blood flow
modeling confirmed improvements in the distribution of
velocity, wall shear stress, oscillatory shear index, and
flow pattern structure after stent deployment. One case was
complicated by asymptomatic in-stent thrombosis.<h4>Conclusion</h4>In
cases of FDD deployment complicated by flow-limiting
stenosis refractory to conventional techniques, a BMS
deployed within the FD can provide radial support to open
both the stenotic device and parent artery. Resulting
improvements in device wall apposition may portend greater
long-term efficacy of FD. In-stent occlusion can occur and
may reflect a thrombogenic interaction between the
devices.},
Doi = {10.1093/ons/opz297},
Key = {fds350120}
}
@article{fds350231,
Author = {Ames, J and Puleri, DF and Balogh, P and Gounley, J and Draeger, EW and Randles, A},
Title = {Multi-GPU Immersed Boundary Method Hemodynamics
Simulations.},
Journal = {Journal of computational science},
Volume = {44},
Pages = {101153},
Year = {2020},
Month = {July},
Abstract = {Large-scale simulations of blood flow that resolve the 3D
deformation of each comprising cell are increasingly popular
owing to algorithmic developments in conjunction with
advances in compute capability. Among different approaches
for modeling cell-resolved hemodynamics, fluid structure
interaction (FSI) algorithms based on the immersed boundary
method are frequently employed for coupling separate solvers
for the background fluid and the cells within one framework.
GPUs can accelerate these simulations; however, both current
pre-exascale and future exascale CPU-GPU heterogeneous
systems face communication challenges critical to
performance and scalability. We describe, to our knowledge,
the largest distributed GPU-accelerated FSI simulations of
high hematocrit cell-resolved flows with over 17 million red
blood cells. We compare scaling on a fat node system with
six GPUs per node and on a system with a single GPU per
node. Through comparison between the CPU- and GPU-based
implementations, we identify the costs of data movement in
multiscale multi-grid FSI simulations on heterogeneous
systems and show it to be the greatest performance
bottleneck on the GPU.},
Doi = {10.1016/j.jocs.2020.101153},
Key = {fds350231}
}
@article{fds352402,
Author = {Puleri, DF and Roychowdhury, S and Ames, J and Randles,
A},
Title = {Computational Framework to Evaluate the Hydrodynamics of
Cell Scaffold Geometries.},
Journal = {Annual International Conference of the IEEE Engineering in
Medicine and Biology Society. IEEE Engineering in Medicine
and Biology Society. Annual International
Conference},
Volume = {2020},
Pages = {2299-2302},
Year = {2020},
Month = {July},
ISBN = {9781728119908},
Abstract = {The fluid dynamics of microporous materials are important to
many biomedical processes such as cell deposition in
scaffold materials, tissue engineering, and bioreactors.
Microporous scaffolds are frequently composed of suspensions
of beads that have varying topology which, in turn, informs
their hydrodynamic properties. Previous work has shown that
shear stress distributions can affect the response of cells
in microporous environments. Using computational fluid
dynamics, we characterize localized differences in fluid
flow attributes such wall shear stress and velocity to
better understand the fluid dynamics underpinning
microporous device function. We evaluated whether bead
packings with similar void fractions had different fluid
dynamics as characterized by the distribution of velocity
magnitudes and wall shear stress and found that there are
differences despite the similarities in void fraction. We
show that another metric, the average distance to the
nearest wall, can provide an additional variable to measure
the porosity and susceptibility of microporous materials to
high shear stress. By increasing our understanding of the
impact of bead size on cell scaffold fluid dynamics we aim
to increase the ability to predict important attributes such
as loading efficiency in these devices.},
Doi = {10.1109/embc44109.2020.9176313},
Key = {fds352402}
}
@article{fds352401,
Author = {Hynes, WF and Pepona, M and Robertson, C and Alvarado, J and Dubbin, K and Triplett, M and Adorno, JJ and Randles, A and Moya,
ML},
Title = {Examining metastatic behavior within 3D bioprinted
vasculature for the validation of a 3D computational flow
model.},
Journal = {Science advances},
Volume = {6},
Number = {35},
Pages = {eabb3308},
Year = {2020},
Month = {August},
Abstract = {Understanding the dynamics of circulating tumor cell (CTC)
behavior within the vasculature has remained an elusive goal
in cancer biology. To elucidate the contribution of
hydrodynamics in determining sites of CTC vascular
colonization, the physical forces affecting these cells must
be evaluated in a highly controlled manner. To this end, we
have bioprinted endothelialized vascular beds and perfused
these constructs with metastatic mammary gland cells under
physiological flow rates. By pairing these in vitro devices
with an advanced computational flow model, we found that the
bioprinted analog was readily capable of evaluating the
accuracy and integrated complexity of a computational flow
model, while also highlighting the discrete contribution of
hydrodynamics in vascular colonization. This intersection of
these two technologies, bioprinting and computational
simulation, is a key demonstration in the establishment of
an experimentation pipeline for the understanding of complex
biophysical events.},
Doi = {10.1126/sciadv.abb3308},
Key = {fds352401}
}
@article{fds374179,
Author = {Bishawi, M and Kaplan, M and Chidyagwai, S and Cappiello, J and Cherry,
A and MacLeod, D and Gall, K and Evans, N and Kim, M and Shaha, R and Whittle,
J and Hollidge, M and Truskey, G and Randles, A},
Title = {Rapid Ventilator Splitting During COVID-19 Pandemic Using 3D
Printed Devices and Numerical Modeling of 200 Million
Patient Specific Air Flow Scenarios.},
Journal = {Res Sq},
Year = {2020},
Month = {August},
Abstract = {There has been a pressing need for an expansion of the
ventilator capacity in response to the recent COVID19
pandemic. To address this need, we present a system to
enable rapid and efficacious splitting between two or more
patients with varying lung compliances and tidal volume
requirements. Reserved for dire situations, ventilator
splitting is complex, and has been limited to patients with
similar pulmonary compliances and tidal volume requirements.
Here, we report a 3D printed ventilator splitter and
resistor system (VSRS) that uses interchangeable airflow
resistors to deliver optimal tidal volumes to patients with
differing respiratory physiologies, thereby expanding the
applicability of ventilator splitting to a larger patient
pool. We demonstrate the capability of the VSRS using
benchtop test lungs and standard-of-care ventilators, which
produced data used to validate a complementary,
patient-specific airflow computational model. The
computational model allows clinicians to rapidly select
optimal resistor sizes and predict delivered pressures and
tidal volumes on-demand from different patient
characteristics and ventilator settings. Due to the inherent
need for rapid deployment, all simulations for the wide
range of clinically-relevant patient characteristics and
ventilator settings were pre-computed and compiled into an
easy to use mobile app. As a result, over 200 million
individual computational simulations were performed to
maximize the number of scenarios for which the VSRS can
provide assistance. The VSRS will help address the pressing
need for increased ventilator capacity by allowing
ventilator splitting to be used with patients with differing
pulmonary physiologies and respiratory requirements, which
will be particularly useful for developing countries and
rural communities with a limited ventilator
supply.},
Doi = {10.21203/rs.3.rs-48165/v1},
Key = {fds374179}
}
@article{fds352868,
Author = {Pepona, M and Balogh, P and Puleri, DF and Hynes, WF and Robertson, C and Dubbin, K and Alvarado, J and Moya, ML and Randles,
A},
Title = {Investigating the Interaction Between Circulating Tumor
Cells and Local Hydrodynamics via Experiment and
Simulations.},
Journal = {Cellular and molecular bioengineering},
Volume = {13},
Number = {5},
Pages = {527-540},
Year = {2020},
Month = {October},
Abstract = {<h4>Introduction</h4>The biological and mechanical
properties of circulating tumor cells (CTCs) in combination
with the hemodynamics affect the preference of metastatic
sites in the vasculature. Despite the extensive literature
on the effects of biological properties on cell adhesion,
the effects of hydrodynamic forces on primary attachment
remains an active area of research. Using simulations in
conjunction with experimentation, we provide new insight
into the interplay of CTCs dynamics and local
hydrodynamics.<h4>Methods</h4>A flow experiment of CTC
attachment was performed within a bioprinted, double
branching endothelialized vessel. Simulations of fluid flow
and CTC transport in the reconstructed and idealized
bifurcated vessel were respectively performed by HARVEY, our
in-house massively parallel computational fluid dynamics
solver. HARVEY is based on the lattice Boltzmann and finite
element methods to model the fluid and cells dynamics. The
immersed boundary method is employed for resolving the
fluid-structure interaction.<h4>Results</h4>CTC attachment
was quantified experimentally at all regions of the complex
vessel. The results demonstrate a clear preference for CTCs
to attach at the branch points. To elucidate the effect of
the vessel topology on the location of attachment, a
fluid-only simulation was performed assessing the
differences in the hydrodynamics along the vessel. CTC
transport in idealized bifurcated vessels was subsequently
studied to examine the effects of cell deformability on the
local hydrodynamics patterns and, thus, the preference of
attachment sites.<h4>Conclusions</h4>The current work
provides evidence on the correlation of the hydrodynamics
forces arising from the vessel topology and CTC properties
on the attachment regions.},
Doi = {10.1007/s12195-020-00656-7},
Key = {fds352868}
}
@article{fds353071,
Author = {Jang, LK and Alvarado, JA and Pepona, M and Wasson, EM and Nash, LD and Ortega, JM and Randles, A and Maitland, DJ and Moya, ML and Hynes,
WF},
Title = {Three-dimensional bioprinting of aneurysm-bearing tissue
structure for endovascular deployment of embolization
coils.},
Journal = {Biofabrication},
Volume = {13},
Number = {1},
Year = {2020},
Month = {October},
Abstract = {Various types of embolization devices have been developed
for the treatment of cerebral aneurysms. However, it is
challenging to properly evaluate device performance and
train medical personnel for device deployment without the
aid of functionally relevant models. Current<i>in
vitro</i>aneurysm models suffer from a lack of key
functional and morphological features of brain vasculature
that limit their applicability for these purposes. These
features include the physiologically relevant mechanical
properties and the dynamic cellular environment of blood
vessels subjected to constant fluid flow. Herein, we
developed three-dimensionally (3D) printed aneurysm-bearing
vascularized tissue structures using gelatin-fibrin hydrogel
of which the inner vessel walls were seeded with human
cerebral microvascular endothelial cells (hCMECs). The
hCMECs readily exhibited cellular attachment, spreading, and
confluency all around the vessel walls, including the
aneurysm walls. Additionally, the<i>in vitro</i>platform was
directly amenable to flow measurements via particle image
velocimetry, enabling the direct assessment of the vascular
flow dynamics for comparison to a 3D computational fluid
dynamics model. Detachable coils were delivered into the
printed aneurysm sac through the vessel using a
microcatheter and static blood plasma clotting was monitored
inside the aneurysm sac and around the coils. This
biomimetic<i>in vitro</i>aneurysm model is a promising
method for examining the biocompatibility and hemostatic
efficiency of embolization devices and for providing
hemodynamic information which would aid in predicting
aneurysm rupture or healing response after
treatment.},
Doi = {10.1088/1758-5090/abbb9b},
Key = {fds353071}
}
@article{fds352668,
Author = {Kaplan, M and Kneifel, C and Orlikowski, V and Dorff, J and Newton, M and Howard, A and Shinn, D and Bishawi, M and Chidyagwai, S and Balogh, P and Randles, A},
Title = {Cloud Computing for COVID-19: Lessons Learned From Massively
Parallel Models of Ventilator Splitting.},
Journal = {Computing in science & engineering},
Volume = {22},
Number = {6},
Pages = {37-47},
Year = {2020},
Month = {November},
Abstract = {A patient-specific airflow simulation was developed to help
address the pressing need for an expansion of the ventilator
capacity in response to the COVID-19 pandemic. The
computational model provides guidance regarding how to split
a ventilator between two or more patients with differing
respiratory physiologies. To address the need for fast
deployment and identification of optimal patient-specific
tuning, there was a need to simulate hundreds of millions of
different clinically relevant parameter combinations in a
short time. This task, driven by the dire circumstances,
presented unique computational and research challenges. We
present here the guiding principles and lessons learned as
to how a large-scale and robust cloud instance was designed
and deployed within 24 hours and 800 000 compute hours were
utilized in a 72-hour period. We discuss the design choices
to enable a quick turnaround of the model, execute the
simulation, and create an intuitive and interactive
interface.},
Doi = {10.1109/mcse.2020.3024062},
Key = {fds352668}
}
@article{fds361402,
Author = {Bardhan, J and Leung, MA and Martin, E and Randles,
A},
Title = {DOE Computational Science Graduate Fellowship Research
Showcase},
Journal = {Computing in Science and Engineering},
Volume = {23},
Number = {6},
Pages = {5-8},
Year = {2021},
Month = {January},
Doi = {10.1109/MCSE.2021.3124033},
Key = {fds361402}
}
@article{fds358704,
Author = {Feiger, B and Lorenzana, E and Ranney, D and Bishawi, M and Doberne, J and Vekstein, A and Voigt, S and Hughes, C and Randles,
A},
Title = {Predicting aneurysmal degeneration of type B aortic
dissection with computational fluid dynamics},
Journal = {Proceedings of the 12th ACM Conference on Bioinformatics,
Computational Biology, and Health Informatics, BCB
2021},
Year = {2021},
Month = {January},
ISBN = {9781450384506},
Abstract = {Stanford Type B aortic dissection (TBAD) is a deadly
cardiovascular disease with mortality rates as high as 50%
in complicated cases. Patients with TBAD are often medically
managed, but in ∼20-40% of cases, patients experience
aneurysmal degeneration in the dissected aorta, and surgical
intervention is required. In this work, we simulated blood
flow using computational fluid dynamics (CFD) to determine
relationships between hemodynamics and aneurysmal
degeneration, providing an important step towards predicting
the need for intervention prior to significant aneurysm
occurrence. Currently, surgeons intervene in TBAD cases
based on the aneurysms growth rate and overall size, as well
as a variety of other factors such as malperfusion,
thrombosis, and pain, but predicting future risk of
aneurysmal degeneration would allow earlier intervention
leading to improved patient outcomes. Here, we hypothesized
that hemodynamic metrics play an important role in the
formation of aneurysms and that these metrics could be used
to predict future aneurysmal degeneration in this patient
population. Our retrospective dataset consisted of 16
patients with TBAD where eight required intervention due to
aneurysmal degeneration and eight were medically managed.
The patients with surgical intervention were examined in our
study prior to the formation of an aneurysm. For each
patient, we segmented and reconstructed the aortic geometry
and simulated blood flow using the lattice Boltzmann method.
We then compared hemodynamic metrics between to the two
groups of patients, including time-averaged wall shear
stress, oscillatory shear index, relative residence time,
and flow fractions to the true and false lumen. We found
significant differences in each metric between the true and
false lumen. We also showed that flow fractions to the false
lumen was higher in patients with aneurysmal degeneration (p
= 0.02). These results are an important step towards
developing more precise methods to predict future aneurysmal
degeneration and the need for intervention in TBAD
patients.},
Doi = {10.1145/3459930.3469563},
Key = {fds358704}
}
@article{fds354240,
Author = {Feiger, B and Adebiyi, A and Randles, A},
Title = {Multiscale modeling of blood flow to assess neurological
complications in patients supported by venoarterial
extracorporeal membrane oxygenation.},
Journal = {Computers in biology and medicine},
Volume = {129},
Pages = {104155},
Year = {2021},
Month = {February},
Abstract = {Computational blood flow models in large arteries elucidate
valuable relationships between cardiovascular diseases and
hemodynamics, leading to improvements in treatment planning
and clinical decision making. One such application with
potential to benefit from simulation is venoarterial
extracorporeal membrane oxygenation (VA-ECMO), a support
system for patients with cardiopulmonary failure. VA-ECMO
patients develop high rates of neurological complications,
partially due to abnormal blood flow throughout the
vasculature from the VA-ECMO system. To better understand
these hemodynamic changes, it is important to resolve
complex local flow parameters derived from three-dimensional
(3D) fluid dynamics while also capturing the impact of
VA-ECMO support throughout the systemic arterial system. As
high-resolution 3D simulations of the arterial network
remain computationally expensive and intractable for large
studies, a validated, multiscale model is needed to compute
both global effects and high-fidelity local hemodynamics. In
this work, we developed and demonstrated a framework to
model hemodynamics in VA-ECMO patients using coupled 3D and
one-dimensional (1D) models (1D→3D). We demonstrated the
ability of these multiscale models to simulate complex flow
patterns in specific regions of interest while capturing
bulk flow throughout the systemic arterial system. We
compared 1D, 3D, and 1D→3D coupled models and found that
multiscale models were able to sufficiently capture both
global and local hemodynamics in the cerebral arteries and
aorta in VA-ECMO patients. This study is the first to
develop and compare 1D, 3D, and 1D→ 3D coupled models on
the larger arterial system scale in VA-ECMO patients, with
potential use for other large scale applications.},
Doi = {10.1016/j.compbiomed.2020.104155},
Key = {fds354240}
}
@article{fds373478,
Author = {Vardhan, M and Randles, A},
Title = {Application of physics-based flow models in cardiovascular
medicine: Current practices and challenges.},
Journal = {Biophysics reviews},
Volume = {2},
Number = {1},
Pages = {011302},
Year = {2021},
Month = {March},
Abstract = {Personalized physics-based flow models are becoming
increasingly important in cardiovascular medicine. They are
a powerful complement to traditional methods of clinical
decision-making and offer a wealth of physiological
information beyond conventional anatomic viewing using
medical imaging data. These models have been used to
identify key hemodynamic biomarkers, such as pressure
gradient and wall shear stress, which are associated with
determining the functional severity of cardiovascular
diseases. Importantly, simulation-driven diagnostics can
help researchers understand the complex interplay between
geometric and fluid dynamic parameters, which can ultimately
improve patient outcomes and treatment planning. The
possibility to compute and predict diagnostic variables and
hemodynamics biomarkers can therefore play a pivotal role in
reducing adverse treatment outcomes and accelerate
development of novel strategies for cardiovascular disease
management.},
Doi = {10.1063/5.0040315},
Key = {fds373478}
}
@article{fds355998,
Author = {Randles, A and Wirsching, H-G and Dean, JA and Cheng, Y-K and Emerson,
S and Pattwell, SS and Holland, EC and Michor, F},
Title = {Computational modelling of perivascular-niche dynamics for
the optimization of treatment schedules for
glioblastoma.},
Journal = {Nature biomedical engineering},
Volume = {5},
Number = {4},
Pages = {346-359},
Year = {2021},
Month = {April},
Abstract = {Glioblastoma stem-like cells dynamically transition between
a chemoradiation-resistant state and a chemoradiation-sensitive
state. However, physical barriers in the tumour
microenvironment restrict the delivery of chemotherapy to
tumour compartments that are distant from blood vessels.
Here, we show that a massively parallel computational model
of the spatiotemporal dynamics of the perivascular niche
that incorporates glioblastoma stem-like cells and
differentiated tumour cells as well as relevant tissue-level
phenomena can be used to optimize the administration
schedules of concurrent radiation and temozolomide-the
standard-of-care treatment for glioblastoma. In mice with
platelet-derived growth factor (PDGF)-driven glioblastoma,
the model-optimized treatment schedule increased the
survival of the animals. For standard radiation
fractionation in patients, the model predicts that
chemotherapy may be optimally administered about one hour
before radiation treatment. Computational models of the
spatiotemporal dynamics of the tumour microenvironment could
be used to predict tumour responses to a broader range of
treatments and to optimize treatment regimens.},
Doi = {10.1038/s41551-021-00710-3},
Key = {fds355998}
}
@article{fds355999,
Author = {Vardhan, M and Gounley, J and Chen, SJ and Chi, EC and Kahn, AM and Leopold, JA and Randles, A},
Title = {Non-invasive characterization of complex coronary
lesions.},
Journal = {Scientific reports},
Volume = {11},
Number = {1},
Pages = {8145},
Year = {2021},
Month = {April},
Abstract = {Conventional invasive diagnostic imaging techniques do not
adequately resolve complex Type B and C coronary lesions,
which present unique challenges, require personalized
treatment and result in worsened patient outcomes. These
lesions are often excluded from large-scale non-invasive
clinical trials and there does not exist a validated
approach to characterize hemodynamic quantities and guide
percutaneous intervention for such lesions. This work
identifies key biomarkers that differentiate complex Type B
and C lesions from simple Type A lesions by introducing and
validating a coronary angiography-based computational fluid
dynamic (CFD-CA) framework for intracoronary assessment in
complex lesions at ultrahigh resolution. Among 14 patients
selected in this study, 7 patients with Type B and C lesions
were included in the complex lesion group including ostial,
bifurcation, serial lesions and lesion where flow was
supplied by collateral bed. Simple lesion group included 7
patients with lesions that were discrete, [Formula: see
text] long and readily accessible. Intracoronary assessment
was performed using CFD-CA framework and validated by
comparing to clinically measured pressure-based index, such
as FFR. Local pressure, endothelial shear stress (ESS) and
velocity profiles were derived for all patients. We
validates the accuracy of our CFD-CA framework and report
excellent agreement with invasive measurements ([Formula:
see text]). Ultra-high resolution achieved by the model
enable physiological assessment in complex lesions and
quantify hemodynamic metrics in all vessels up to 1mm in
diameter. Importantly, we demonstrate that in contrast to
traditional pressure-based metrics, there is a significant
difference in the intracoronary hemodynamic forces, such as
ESS, in complex lesions compared to simple lesions at both
resting and hyperemic physiological states [n = 14,
[Formula: see text]]. Higher ESS was observed in the complex
lesion group ([Formula: see text] Pa) than in simple lesion
group ([Formula: see text] Pa). Complex coronary lesions
have higher ESS compared to simple lesions, such
differential hemodynamic evaluation can provide much the
needed insight into the increase in adverse outcomes for
such patients and has incremental prognostic value over
traditional pressure-based indices, such as
FFR.},
Doi = {10.1038/s41598-021-86360-6},
Key = {fds355999}
}
@article{fds358306,
Author = {Balogh, P and Gounley, J and Roychowdhury, S and Randles,
A},
Title = {A data-driven approach to modeling cancer cell mechanics
during microcirculatory transport.},
Journal = {Scientific reports},
Volume = {11},
Number = {1},
Pages = {15232},
Year = {2021},
Month = {July},
Abstract = {In order to understand the effect of cellular level features
on the transport of circulating cancer cells in the
microcirculation, there has been an increasing reliance on
high-resolution in silico models. Accurate simulation of
cancer cells flowing with blood cells requires resolving
cellular-scale interactions in 3D, which is a significant
computational undertaking warranting a cancer cell model
that is both computationally efficient yet sufficiently
complex to capture relevant behavior. Given that the
characteristics of metastatic spread are known to depend on
cancer type, it is crucial to account for mechanistic
behavior representative of a specific cancer's cells. To
address this gap, in the present work we develop and
validate a means by which an efficient and popular membrane
model-based approach can be used to simulate deformable
cancer cells and reproduce experimental data from specific
cell lines. Here, cells are modeled using the immersed
boundary method (IBM) within a lattice Boltzmann method
(LBM) fluid solver, and the finite element method (FEM) is
used to model cell membrane resistance to deformation.
Through detailed comparisons with experiments, we (i)
validate this model to represent cancer cells undergoing
large deformation, (ii) outline a systematic approach to
parameterize different cell lines to optimally fit
experimental data over a range of deformations, and (iii)
provide new insight into nucleated vs. non-nucleated cell
models and their ability to match experiments. While many
works have used the membrane-model based method employed
here to model generic cancer cells, no quantitative
comparisons with experiments exist in the literature for
specific cell lines undergoing large deformation. Here, we
describe a phenomenological, data-driven approach that can
not only yield good agreement for large deformations, but
explicitly detail how it can be used to represent different
cancer cell lines. This model is readily incorporated into
cell-resolved hemodynamic transport simulations, and thus
offers significant potential to complement experiments
towards providing new insights into various aspects of
cancer progression.},
Doi = {10.1038/s41598-021-94445-5},
Key = {fds358306}
}
@article{fds355624,
Author = {Puleri, DF and Balogh, P and Randles, A},
Title = {Computational models of cancer cell transport through the
microcirculation.},
Journal = {Biomechanics and modeling in mechanobiology},
Volume = {20},
Number = {4},
Pages = {1209-1230},
Year = {2021},
Month = {August},
Abstract = {The transport of cancerous cells through the
microcirculation during metastatic spread encompasses
several interdependent steps that are not fully understood.
Computational models which resolve the cellular-scale
dynamics of complex microcirculatory flows offer
considerable potential to yield needed insights into the
spread of cancer as a result of the level of detail that can
be captured. In recent years, in silico methods have been
developed that can accurately and efficiently model the
circulatory flows of cancer and other biological cells.
These computational methods are capable of resolving
detailed fluid flow fields which transport cells through
tortuous physiological geometries, as well as the
deformation and interactions between cells,
cell-to-endothelium interactions, and tumor cell aggregates,
all of which play important roles in metastatic spread. Such
models can provide a powerful complement to experimental
works, and a promising approach to recapitulating the
endogenous setting while maintaining control over parameters
such as shear rate, cell deformability, and the strength of
adhesive binding to better understand tumor cell transport.
In this review, we present an overview of computational
models that have been developed for modeling cancer cells in
the microcirculation, including insights they have provided
into cell transport phenomena.},
Doi = {10.1007/s10237-021-01452-6},
Key = {fds355624}
}
@article{fds355570,
Author = {Herschlag, G and Lee, S and Vetter, JS and Randles,
A},
Title = {Analysis of GPU Data Access Patterns on Complex Geometries
for the D3Q19 Lattice Boltzmann Algorithm},
Journal = {IEEE Transactions on Parallel and Distributed
Systems},
Volume = {32},
Number = {10},
Pages = {2400-2414},
Year = {2021},
Month = {October},
Abstract = {GPU performance of the lattice Boltzmann method (LBM)
depends heavily on memory access patterns. When implemented
with GPUs on complex domains, typically, geometric data is
accessed indirectly and lattice data is accessed
lexicographically. Although there are a variety of other
options, no study has examined the relative efficacy between
them. Here, we examine a suite of memory access schemes via
empirical testing and performance modeling. We find strong
evidence that semi-direct is often better suited than the
more common indirect addressing, providing increased
computational speed and reducing memory consumption. For the
layout, we find that the Collected Structure of Arrays
(CSoA) and bundling layouts outperform the common Structure
of Array layout; on V100 and P100 devices, CSoA consistently
outperforms bundling, however the relationship is more
complicated on K40 devices. When compared to
state-of-the-art practices, our recommendations lead to
speedups of 10-40 percent and reduce memory consumption up
to 17 percent. Using performance modeling and computational
experimentation, we determine the mechanisms behind the
accelerations. We demonstrate that our results hold across
multiple GPUs on two leadership class systems, and present
the first near-optimal strong results for LBM with arterial
geometries run on GPUs.},
Doi = {10.1109/TPDS.2021.3061895},
Key = {fds355570}
}
@article{fds361777,
Author = {Liu, X and Vardhan, M and Wen, Q and Das, A and Randles, A and Chi,
EC},
Title = {An Interpretable Machine Learning Model to Classify Coronary
Bifurcation Lesions.},
Journal = {Annual International Conference of the IEEE Engineering in
Medicine and Biology Society. IEEE Engineering in Medicine
and Biology Society. Annual International
Conference},
Volume = {2021},
Pages = {4432-4435},
Year = {2021},
Month = {November},
Abstract = {Coronary bifurcation lesions are a leading cause of Coronary
Artery Disease (CAD). Despite its prevalence, coronary
bifurcation lesions remain difficult to treat due to our
incomplete understanding of how various features of lesion
anatomy synergistically disrupt normal hemodynamic flow. In
this work, we employ an interpretable machine learning
algorithm, the Classification and Regression Tree (CART), to
model the impact of these geometric features on local
hemodynamic quantities. We generate a synthetic arterial
database via computational fluid dynamic simulations and
apply the CART approach to predict the time averaged wall
shear stress (TAWSS) at two different locations within the
cardiac vasculature. Our experimental results show that CART
can estimate a simple, interpretable, yet accurately
predictive nonlinear model of TAWSS as a function of such
features.Clinical relevance- The fitted tree models have the
potential to refine predictions of disturbed hemodynamic
flow based on an individual's cardiac and lesion anatomy and
consequently makes progress towards personalized treatment
planning for CAD patients.},
Doi = {10.1109/embc46164.2021.9631082},
Key = {fds361777}
}
@article{fds361778,
Author = {Tanade, C and Feiger, B and Vardhan, M and Chen, SJ and Leopold, JA and Randles, A},
Title = {Global Sensitivity Analysis For Clinically Validated 1D
Models of Fractional Flow Reserve.},
Journal = {Annual International Conference of the IEEE Engineering in
Medicine and Biology Society. IEEE Engineering in Medicine
and Biology Society. Annual International
Conference},
Volume = {2021},
Pages = {4395-4398},
Year = {2021},
Month = {November},
Abstract = {Computation of Fractional Flow Reserve (FFR) through
computational fluid dynamics (CFD) is used to guide
intervention and often uses a number of clinically-derived
metrics, but these patient-specific data could be costly and
difficult to obtain. Understanding which parameters can be
approximated from population averages and which parameters
need to be patient-specific is important and remains largely
unexplored. In this study, we performed a global sensitivity
study on two 1D models of FFR to identify the most
influential patient parameters. Our results indicated that
vessel compliance, cardiac cycle period, flow rate, density,
viscosity, and elastic modulus contributed minimally to the
variance in FFR and may be approximated from population
averages. On the other hand, outlet resistance (i.e.,
microvascular resistance), stenosis degree, and percent
stenosis length contributed the most to FFR computation and
needed to be tuned to the patient of interest. Selective
measuring of patient-specific parameters may significantly
reduce costs and streamline the simulation pipeline without
reducing accuracy.},
Doi = {10.1109/embc46164.2021.9629890},
Key = {fds361778}
}
@article{fds359250,
Author = {Bazarin, RLM and Philippi, PC and Randles, A and Hegele,
LA},
Title = {Moments-based method for boundary conditions in the lattice
Boltzmann framework: A comparative analysis for the lid
driven cavity flow},
Journal = {Computers and Fluids},
Volume = {230},
Year = {2021},
Month = {November},
Abstract = {Dealing with boundary conditions (BC) was ever considered a
puzzling question in the lattice Boltzmann (LB) method. The
most popular BC models are based on Ad-Hoc rules and,
although these BC models were shown to be suitable for
low-order LB equations, their extension to high-order LB was
shown to be a very difficult problem and, at authors
knowledge, never solved with satisfaction. The main question
to be solved is how to deal with a problem when the number
of unknowns (the particle populations coming from the
outside part of the numerical domain) is greater than the
number of equations at our disposal at each boundary site.
Recently, BC models based on the regularization of the LB
equation, or moments-based models, were proposed. These
moments replace the discrete populations as unknowns,
independently of the number of discrete velocities that are
needed for solving a given problem. The full set of
moments-based BC leads, nevertheless, to an overdetermined
system of equations, and what distinguishes one model from
another is the way this system is solved. In contrast with
previous work, we base our approach on second-order moments.
Four versions of this model are compared with previous
moments-based models considering, in addition to the
accuracy, some main model attributes such as global and
local mass conservation, rates of convergence, and
stability. For this purpose, the complex flow patterns
displayed in a two-dimensional lid-driven cavity are
investigated.},
Doi = {10.1016/j.compfluid.2021.105142},
Key = {fds359250}
}
@article{fds362492,
Author = {Feiger, B and Lorenzana-Saldivar, E and Cooke, C and Horstmeyer, R and Bishawi, M and Doberne, J and Hughes, GC and Ranney, D and Voigt, S and Randles, A},
Title = {Evaluation of U-Net Based Architectures for Automatic Aortic
Dissection Segmentation},
Journal = {ACM Transactions on Computing for Healthcare},
Volume = {3},
Number = {1},
Year = {2022},
Month = {January},
Abstract = {Segmentation and reconstruction of arteries is important for
a variety of medical and engineering fields, such as
surgical planning and physiological modeling. However,
manual methods can be laborious and subject to a high degree
of human variability. In this work, we developed various
convolutional neural network (CNN) architectures to segment
Stanford type B aortic dissections (TBADs), characterized by
a tear in the descending aortic wall creating a normal
channel of blood flow called a true lumen and a pathologic
channel within the wall called a false lumen. We introduced
several variations to the two-dimensional (2D) and
three-dimensional (3D) U-Net, where small stacks of slices
were inputted into the networks instead of individual slices
or whole geometries. We compared these variations with a
variety of CNN segmentation architectures and found that
stacking the input data slices in the upward direction with
2D U-Net improved segmentation accuracy, as measured by the
Dice similarity coefficient (DC) and point-by-point average
distance (AVD), by more than . Our optimal architecture
produced DC scores of 0.94, 0.88, and 0.90 and AVD values of
0.074, 0.22, and 0.11 in the whole aorta, true lumen, and
false lumen, respectively. Altogether, the predicted
reconstructions closely matched manual reconstructions.},
Doi = {10.1145/3472302},
Key = {fds362492}
}
@article{fds371518,
Author = {Tanade, C and Chen, SJ and Leopold, JA and Randles,
A},
Title = {Analysis identifying minimal governing parameters for
clinically accurate in silico fractional flow
reserve.},
Journal = {Frontiers in medical technology},
Volume = {4},
Pages = {1034801},
Year = {2022},
Month = {January},
Abstract = {<h4>Background</h4>Personalized hemodynamic models can
accurately compute fractional flow reserve (FFR) from
coronary angiograms and clinical measurements (FFR baseline
), but obtaining patient-specific data could be challenging
and sometimes not feasible. Understanding which measurements
need to be patient-tuned vs. patient-generalized would
inform models with minimal inputs that could expedite data
collection and simulation pipelines.<h4>Aims</h4>To
determine the minimum set of patient-specific inputs to
compute FFR using invasive measurement of FFR (FFR invasive
) as gold standard.<h4>Materials and methods</h4>Personalized
coronary geometries ( N = 50 ) were derived from patient
coronary angiograms. A computational fluid dynamics
framework, FFR baseline , was parameterized with
patient-specific inputs: coronary geometry, stenosis
geometry, mean arterial pressure, cardiac output, heart
rate, hematocrit, and distal pressure location. FFR baseline
was validated against FFR invasive and used as the baseline
to elucidate the impact of uncertainty on personalized
inputs through global uncertainty analysis. FFR streamlined
was created by only incorporating the most sensitive inputs
and FFR semi-streamlined additionally included
patient-specific distal location.<h4>Results</h4>FFR
baseline was validated against FFR invasive via correlation
( r = 0.714 , p < 0.001 ), agreement (mean difference: 0.01
± 0.09 ), and diagnostic performance (sensitivity: 89.5%,
specificity: 93.6%, PPV: 89.5%, NPV: 93.6%, AUC: 0.95). FFR
semi-streamlined provided identical diagnostic performance
with FFR baseline . Compared to FFR baseline vs. FFR
invasive , FFR streamlined vs. FFR invasive had decreased
correlation ( r = 0.64 , p < 0.001 ), improved agreement
(mean difference: 0.01 ± 0.08 ), and comparable diagnostic
performance (sensitivity: 79.0%, specificity: 90.3%, PPV:
83.3%, NPV: 87.5%, AUC: 0.90).<h4>Conclusion</h4>Streamlined
models could match the diagnostic performance of the
baseline with a full gamut of patient-specific measurements.
Capturing coronary hemodynamics depended most on accurate
geometry reconstruction and cardiac output
measurement.},
Doi = {10.3389/fmedt.2022.1034801},
Key = {fds371518}
}
@article{fds373984,
Author = {Roychowdhury, S and Mahmud, ST and Puleri, DF and Lai, A and Rex, R and Li,
B and Sohn, LL and Randles, A},
Title = {DEVELOPING A DIGITAL TWIN FOR SINGLE-CELL MECHANICAL
PHENOTYPING MICROFLUIDIC DEVICES},
Journal = {MicroTAS 2022 - 26th International Conference on
Miniaturized Systems for Chemistry and Life
Sciences},
Pages = {831-832},
Year = {2022},
Month = {January},
ISBN = {9781733419048},
Abstract = {Microfluidics can be used to characterize individual cells
in a population based on their mechanical traits. In this
work, we digitally replicate the microfluidic device
developed by Li et al. [1] and perform simulations of a
representative AP-1060 cell. We show that the numerical
model is able to recover whole-cell deformability index, a
metric used to quantify the resistance of cells to
compressive deformation, within 3% of the experimental
average. These results pave the way for future studies which
utilize experimental and computational approaches to
optimize geometric design parameters, complement signal
analysis, and enhance the acquisition of mechanical
information.},
Key = {fds373984}
}
@article{fds364293,
Author = {Bishawi, M and Kaplan, M and Chidyagwai, S and Cappiello, J and Cherry,
A and MacLeod, D and Gall, K and Evans, N and Kim, M and Shaha, R and Whittle,
J and Hollidge, M and Truskey, G and Randles, A},
Title = {Patient- and Ventilator-Specific Modeling to Drive the Use
and Development of 3D Printed Devices for Rapid
Ventilator Splitting During the COVID-19
Pandemic},
Journal = {Lecture Notes in Computer Science (including subseries
Lecture Notes in Artificial Intelligence and Lecture Notes
in Bioinformatics)},
Volume = {13352 LNCS},
Pages = {137-149},
Year = {2022},
Month = {January},
ISBN = {9783031087561},
Abstract = {In the early days of the COVID-19 pandemic, there was a
pressing need for an expansion of the ventilator capacity in
response to the COVID19 pandemic. Reserved for dire
situations, ventilator splitting is complex, and has
previously been limited to patients with similar pulmonary
compliances and tidal volume requirements. To address this
need, we developed a system to enable rapid and efficacious
splitting between two or more patients with varying lung
compliances and tidal volume requirements. We present here a
computational framework to both drive device design and
inform patient-specific device tuning. By creating a
patient- and ventilator-specific airflow model, we were able
to identify pressure-controlled splitting as preferable to
volume-controlled as well create a simulation-guided
framework to identify the optimal airflow resistor for a
given patient pairing. In this work, we present the
computational model, validation of the model against
benchtop test lungs and standard-of-care ventilators, and
the methods that enabled simulation of over 200 million
patient scenarios using 800,000 compute hours in a 72 h
period.},
Doi = {10.1007/978-3-031-08757-8_13},
Key = {fds364293}
}
@article{fds364341,
Author = {Tanade, C and Putney, S and Randles, A},
Title = {Developing a Scalable Cellular Automaton Model of 3D Tumor
Growth},
Journal = {Lecture Notes in Computer Science (including subseries
Lecture Notes in Artificial Intelligence and Lecture Notes
in Bioinformatics)},
Volume = {13350 LNCS},
Pages = {3-16},
Year = {2022},
Month = {January},
ISBN = {9783031087509},
Abstract = {Parallel three-dimensional (3D) cellular automaton models of
tumor growth can efficiently model tumor morphology over
many length and time scales. Here, we extended an existing
two-dimensional (2D) model of tumor growth to study how
tumor morphology could change over time and verified the 3D
model with the initial 2D model on a per-slice level.
However, increasing the dimensionality of the model imposes
constraints on memory and time-to-solution that could
quickly become intractable when simulating long temporal
durations. Parallelizing such models would enable larger
tumors to be investigated and also pave the way for coupling
with treatment models. We parallelized the 3D growth model
using N-body and lattice halo exchange schemes and further
optimized the implementation to adaptively exchange
information based on the state of cell expansion. We
demonstrated a factor of 20x speedup compared to the serial
model when running on 340 cores of Stampede2’s Knight’s
Landing compute nodes. This proof-of-concept study
highlighted that parallel 3D models could enable the
exploration of large problem and parameter spaces at
tractable run times.},
Doi = {10.1007/978-3-031-08751-6_1},
Key = {fds364341}
}
@article{fds364342,
Author = {Roychowdhury, S and Draeger, EW and Randles, A},
Title = {Establishing Metrics to Quantify Underlying Structure
in Vascular Red Blood Cell Distributions},
Journal = {Lecture Notes in Computer Science (including subseries
Lecture Notes in Artificial Intelligence and Lecture Notes
in Bioinformatics)},
Volume = {13350 LNCS},
Pages = {89-102},
Year = {2022},
Month = {January},
ISBN = {9783031087509},
Abstract = {Simulations of the microvasculature can elucidate the
effects of various blood flow parameters on micro-scale
cellular and fluid phenomena. At this scale, the
non-Newtonian behavior of blood requires the use of explicit
cell models, which are necessary for capturing the full
dynamics of cell motion and interactions. Over the last few
decades, fluid-structure interaction models have emerged as
a method to accurately capture the behavior of deformable
cells in the blood. However, as computational power
increases and systems with millions of red blood cells can
be simulated, it is important to note that varying spatial
distributions of cells may affect simulation outcomes. Since
a single simulation may not represent the ensemble behavior,
many different configurations may need to be sampled to
adequately assess the entire collection of potential cell
arrangements. In order to determine both the number of
distributions needed and which ones to run, we must first
establish methods to identify well-generated,
randomly-placed cell distributions and to quantify distinct
cell configurations. In this work, we utilize metrics to
assess 1) the presence of any underlying structure to the
initial cell distribution and 2) similarity between cell
configurations. We propose the use of the radial
distribution function to identify long-range structure in a
cell configuration and apply it to a randomly-distributed
and structured set of red blood cells. To quantify spatial
similarity between two configurations, we make use of the
Jaccard index, and characterize sets of red blood cell and
sphere initializations.},
Doi = {10.1007/978-3-031-08751-6_7},
Key = {fds364342}
}
@article{fds368930,
Author = {Vardhan, M and Shi, H and Urick, D and Patel, M and Leopold, JA and Randles, A},
Title = {The role of extended reality for planning coronary artery
bypass graft surgery},
Journal = {Proceedings - 2022 IEEE Visualization Conference - Short
Papers, VIS 2022},
Pages = {115-119},
Year = {2022},
Month = {January},
ISBN = {9781665488129},
Abstract = {Immersive visual displays are becoming more common in the
diagnostic imaging and pre-procedural planning of complex
cardiology revascularization surgeries. One such procedure
is coronary artery bypass grafting (CABG) surgery, which is
a gold standard treat-ment for patients with advanced
coronary heart disease. Treatment planning of the CABG
surgery can be aided by extended reality (XR) displays as
they are known for offering advantageous visual-ization of
spatially heterogeneous and complex tasks. Despite the
benefits of XR, it remains unknown whether clinicians will
benefit from higher visual immersion offered by XR. In order
to assess the impact of increased immersion as well as the
latent factor of geometrical complexity, a quantitative user
evaluation (n=14) was performed with clinicians of advanced
cardiology training simulating CABG placement on sixteen 3D
arterial tree models derived from 6 patients two levels of
anatomic complexity. These arterial models were rendered on
3D/XR and 2D display modes with the same tactile interaction
input device. The findings of this study reveal that
compared to a monoscopic 2D display, the greater visual
immersion of 3D/XR does not significantly alter clinician
accuracy in the task of bypass graft placement. Latent
factors such as arterial complexity and clinical experience
both influence the accuracy of graft placement. In addition,
an anatomically less complex model},
Doi = {10.1109/VIS54862.2022.00032},
Key = {fds368930}
}
@article{fds361776,
Author = {Chidyagwai, SG and Vardhan, M and Kaplan, M and Chamberlain, R and Barker, P and Randles, A},
Title = {Characterization of hemodynamics in anomalous aortic origin
of coronary arteries using patient-specific
modeling.},
Journal = {J Biomech},
Volume = {132},
Pages = {110919},
Year = {2022},
Month = {February},
Abstract = {The anomalous aortic origin of coronary arteries (AAOCA) is
a congenital disease that can lead to sudden cardiac death
(SCD) during strenuous physical activity. Despite AAOCA
being the second leading cause of SCD among young athletes,
the mechanism behind sudden cardiac death remains mostly
unknown. Computational fluid dynamics provides a powerful
tool for studying how pathologic anatomy can affect
different hemodynamic states. The present study investigates
the effect of AAOCA on patient hemodynamics. We performed
patient-specific hemodynamic simulations of interarterial
AAOCA at baseline and in the exercise state using our
massively parallel flow solver. Additionally, we investigate
how surgical correction via coronary unroofing impacts
patient blood flow. Results show that patient-specific AAOCA
models exhibited higher interarterial time-averaged wall
shear stress (TAWSS) values compared to the control
patients. The oscillatory shear index had no impact on
AAOCA. Finally, the coronary unroofing procedure normalized
the elevated TAWSS by decreasing TAWSS in the postoperative
patient. The present study provides a proof of concept for
the potential hemodynamic factors underlying coronary
ischemia in AAOCA during exercise state.},
Doi = {10.1016/j.jbiomech.2021.110919},
Key = {fds361776}
}
@article{fds358307,
Author = {Gounley, J and Vardhan, M and Draeger, EW and Valero-Lara, P and Moore,
SV and Randles, A},
Title = {Propagation pattern for moment representation of the lattice
Boltzmann method.},
Journal = {IEEE transactions on parallel and distributed systems : a
publication of the IEEE Computer Society},
Volume = {33},
Number = {3},
Pages = {642-653},
Year = {2022},
Month = {March},
Abstract = {A propagation pattern for the moment representation of the
regularized lattice Boltzmann method (LBM) in three
dimensions is presented. Using effectively lossless
compression, the simulation state is stored as a set of
moments of the lattice Boltzmann distribution function,
instead of the distribution function itself. An efficient
cache-aware propagation pattern for this moment
representation has the effect of substantially reducing both
the storage and memory bandwidth required for LBM
simulations. This paper extends recent work with the moment
representation by expanding the performance analysis on
central processing unit (CPU) architectures, considering how
boundary conditions are implemented, and demonstrating the
effectiveness of the moment representation on a graphics
processing unit (GPU) architecture.},
Doi = {10.1109/tpds.2021.3098456},
Key = {fds358307}
}
@article{fds363205,
Author = {Puleri, DF and Randles, A},
Title = {The role of adhesive receptor patterns on cell transport in
complex microvessels.},
Journal = {Biomechanics and modeling in mechanobiology},
Volume = {21},
Number = {4},
Pages = {1079-1098},
Year = {2022},
Month = {August},
Abstract = {Cell transport is governed by the interaction of fluid
dynamic forces and biochemical factors such as adhesion
receptor expression and concentration. Although the effect
of endothelial receptor density is well understood, it is
not clear how the spacing and local spatial distribution of
receptors affect cell adhesion in three-dimensional
microvessels. To elucidate the effect of vessel shape on
cell trajectory and the arrangement of endothelial receptors
on cell adhesion, we employed a three-dimensional deformable
cell model that incorporates microscale interactions between
the cell and the endothelium. Computational cellular
adhesion models are systematically altered to assess the
influence of receptor spacing. We demonstrate that the
patterns of receptors on the vessel walls are a key factor
guiding cell movement. In straight microvessels, we show a
relationship between cell velocity and the spatial
distribution of adhesive endothelial receptors, with larger
receptor patches producing lower translational velocities.
The joint effect of the complex vessel topology seen in
microvessel shapes such as curved and bifurcated vessels
when compared to straight tubes is explored with results
which showed the spatial distribution of receptors affecting
cell trajectory. Our findings here represent demonstration
of the previously undescribed relationship between receptor
pattern and geometry that guides cellular movement in
complex microenvironments.},
Doi = {10.1007/s10237-022-01575-4},
Key = {fds363205}
}
@article{fds367381,
Author = {Puleri, DF and Martin, AX and Randles, A},
Title = {Distributed Acceleration of Adhesive Dynamics
Simulations.},
Journal = {Proceedings of 2022 29th European MPI Users' Group Meeting
(EuroMPI/USA'2022) : September 26-28, 2022, Chattanooga, TN.
European MPI Users' Group Meeting (29th : 2022 :
Chattanooga, Tenn.)},
Volume = {2022},
Pages = {37-45},
Year = {2022},
Month = {September},
ISBN = {9781450397995},
Abstract = {Cell adhesion plays a critical role in processes ranging
from leukocyte migration to cancer cell transport during
metastasis. Adhesive cell interactions can occur over large
distances in microvessel networks with cells traveling over
distances much greater than the length scale of their own
diameter. Therefore, biologically relevant investigations
necessitate efficient modeling of large field-of-view
domains, but current models are limited by simulating such
geometries at the sub-micron scale required to model
adhesive interactions which greatly increases the
computational requirements for even small domain sizes. In
this study we introduce a hybrid scheme reliant on both
on-node and distributed parallelism to accelerate a fully
deformable adhesive dynamics cell model. This scheme leads
to performant system usage of modern supercomputers which
use a many-core per-node architecture. On-node acceleration
is augmented by a combination of spatial data structures and
algorithmic changes to lessen the need for atomic
operations. This deformable adhesive cell model accelerated
with hybrid parallelization allows us to bridge the gap
between high-resolution cell models which can capture the
sub-micron adhesive interactions between the cell and its
microenvironment, and large-scale fluid-structure
interaction (FSI) models which can track cells over
considerable distances. By integrating the sub-micron
simulation environment into a distributed FSI simulation we
enable the study of previously unfeasible research questions
involving numerous adhesive cells in microvessel networks
such as cancer cell transport through the
microcirculation.},
Doi = {10.1145/3555819.3555832},
Key = {fds367381}
}
@article{fds367621,
Author = {Puleri, DF and Roychowdhury, S and Balogh, P and Gounley, J and Draeger,
EW and Ames, J and Adebiyi, A and Chidyagwai, S and Hernández, B and Lee,
S and Moore, SV and Vetter, JS and Randles, A},
Title = {High Performance Adaptive Physics Refinement to Enable
Large-Scale Tracking of Cancer Cell Trajectory.},
Journal = {Proceedings. IEEE International Conference on Cluster
Computing},
Volume = {2022},
Pages = {230-242},
Year = {2022},
Month = {September},
ISBN = {9781665498562},
Abstract = {The ability to track simulated cancer cells through the
circulatory system, important for developing a mechanistic
understanding of metastatic spread, pushes the limits of
today's supercomputers by requiring the simulation of large
fluid volumes at cellular-scale resolution. To overcome this
challenge, we introduce a new adaptive physics refinement
(APR) method that captures cellular-scale interaction across
large domains and leverages a hybrid CPU-GPU approach to
maximize performance. Through algorithmic advances that
integrate multi-physics and multi-resolution models, we
establish a finely resolved window with explicitly modeled
cells coupled to a coarsely resolved bulk fluid domain. In
this work we present multiple validations of the APR
framework by comparing against fully resolved
fluid-structure interaction methods and employ techniques,
such as latency hiding and maximizing memory bandwidth, to
effectively utilize heterogeneous node architectures.
Collectively, these computational developments and
performance optimizations provide a robust and scalable
framework to enable system-level simulations of cancer cell
transport.},
Doi = {10.1109/cluster51413.2022.00036},
Key = {fds367621}
}
@article{fds372232,
Author = {Ladd, W and Jensen, C and Vardhan, M and Ames, J and Hammond, JR and Draeger, EW and Randles, A},
Title = {Optimizing Cloud Computing Resource Usage for Hemodynamic
Simulation},
Journal = {Proceedings - 2023 IEEE International Parallel and
Distributed Processing Symposium, IPDPS 2023},
Pages = {568-578},
Year = {2023},
Month = {January},
ISBN = {9798350337662},
Abstract = {Cloud computing resources are becoming an increasingly
attractive option for simulation workflows but require users
to assess a wider variety of hardware options and associated
costs than required by traditional in-house hardware or
fixed allocations at leadership computing facilities. The
pay-as-you-go model used by cloud providers gives users the
opportunity to make more nuanced cost-benefit decisions at
runtime by choosing hardware that best matches a given
workload, but creates the risk of suboptimal allocation
strategies or inadvertent cost overruns. In this work, we
propose the use of an iteratively-refined performance model
to optimize cloud simulation campaigns against overall cost,
throughput, or maximum time to solution. Hemodynamic
simulations represent an excellent use case for these
assessments, as the relative costs and dominant terms in the
performance model can vary widely with hardware, numerical
parameters and physics models. Performance and scaling
behavior of hemodynamic simulations on multiple cloud
services as well as a traditional compute cluster are
collected and evaluated, and an initial performance model is
proposed along with a strategy for dynamically refining it
with additional experimental data.},
Doi = {10.1109/IPDPS54959.2023.00063},
Key = {fds372232}
}
@article{fds368929,
Author = {Pepona, M and Gounley, J and Randles, A},
Title = {Effect of constitutive law on the erythrocyte membrane
response to large strains.},
Journal = {Computers & mathematics with applications (Oxford, England :
1987)},
Volume = {132},
Pages = {145-160},
Year = {2023},
Month = {February},
Abstract = {Three constitutive laws, that is the Skalak, neo-Hookean and
Yeoh laws, commonly employed for describing the erythrocyte
membrane mechanics are theoretically analyzed and
numerically investigated to assess their accuracy for
capturing erythrocyte deformation characteristics and
morphology. Particular emphasis is given to the nonlinear
deformation regime, where it is known that the discrepancies
between constitutive laws are most prominent. Hence, the
experiments of optical tweezers and micropipette aspiration
are considered here, for which relationships between the
individual shear elastic moduli of the constitutive laws can
also be established through analysis of the
tension-deformation relationship. All constitutive laws were
found to adequately predict the axial and transverse
deformations of a red blood cell subjected to stretching
with optical tweezers for a constant shear elastic modulus
value. As opposed to Skalak law, the neo-Hookean and Yeoh
laws replicated the erythrocyte membrane folding, that has
been experimentally observed, with the trade-off of
sustaining significant area variations. For the micropipette
aspiration, the suction pressure-aspiration length
relationship could be excellently predicted for a fixed
shear elastic modulus value only when Yeoh law was
considered. Importantly, the neo-Hookean and Yeoh laws
reproduced the membrane wrinkling at suction pressures close
to those experimentally measured. None of the constitutive
laws suffered from membrane area compressibility in the
micropipette aspiration case.},
Doi = {10.1016/j.camwa.2022.12.009},
Key = {fds368929}
}
@article{fds367820,
Author = {Shi, H and Vardhan, M and Randles, A},
Title = {The Role of Immersion for Improving Extended Reality
Analysis of Personalized Flow Simulations.},
Journal = {Cardiovascular engineering and technology},
Volume = {14},
Number = {2},
Pages = {194-203},
Year = {2023},
Month = {April},
Abstract = {<h4>Purpose</h4>Computational models of flow in
patient-derived arterial geometries have become a key
paradigm of biomedical research. These fluid models are
often challenging to visualize due to high spatial
heterogeneity and visual complexity. Virtual immersive
environments can offer advantageous visualization of
spatially heterogeneous and complex systems. However, as
different VR devices offer varying levels of immersion,
there remains a crucial lack of understanding regarding what
level of immersion is best suited for interactions with
patient-specific flow models.<h4>Methods</h4>We conducted a
quantitative user evaluation with multiple VR devices
testing an important use of hemodynamic simulations-analysis
of surface parameters within complex patient-specific
geometries. This task was compared for the semi-immersive
zSpace 3D monitor and the fully immersive HTC Vive
system.<h4>Results</h4>The semi-immersive device was more
accurate than the fully immersive device. The two devices
showed similar results for task duration and performance
(accuracy/duration). The accuracy of the semi-immersive
device was also higher for arterial geometries of greater
complexity and branching.<h4>Conclusion</h4>This assessment
demonstrates that the level of immersion plays a significant
role in the accuracy of assessing arterial flow models. We
found that the semi-immersive VR device was a generally
optimal choice for arterial visualization.},
Doi = {10.1007/s13239-022-00646-y},
Key = {fds367820}
}
@article{fds371136,
Author = {Roychowdhury, S and Draeger, EW and Randles, A},
Title = {Establishing metrics to quantify spatial similarity in
spherical and red blood cell distributions},
Journal = {Journal of Computational Science},
Volume = {71},
Year = {2023},
Month = {July},
Abstract = {As computational power increases and systems with millions
of red blood cells can be simulated, it is important to note
that varying spatial distributions of cells may affect
simulation outcomes. Since a single simulation may not
represent the ensemble behavior, many different
configurations may need to be sampled to adequately assess
the entire collection of potential cell arrangements. In
order to determine both the number of distributions needed
and which ones to run, we must first establish methods to
identify well-generated, randomly placed cell distributions
and to quantify distinct cell configurations. We utilize
metrics to assess (1) the presence of any underlying
structure to the initial cell distribution and (2)
similarity between cell configurations. We propose the use
of the radial distribution function to identify long-range
structure in a cell configuration and apply it to a randomly
distributed and structured set of red blood cells. To
quantify spatial similarity between two configurations, we
make use of the Jaccard index, and characterize sets of red
blood cell and sphere initializations. As an extension to
our work submitted to the International Conference on
Computational Science (Roychowdhury et al., 2022), we
significantly increase our data set size from 72 to 1048
cells, include a similar set of studies using spheres,
compare the effects of varying sphere size, and utilize the
Jaccard index distribution to probe sets of extremely
similar configurations. Our results show that the radial
distribution function can be used as a metric to determine
long-range structure in both distributions of spheres and
RBCs. We determine that the ideal case of spheres within a
cube versus bi-concave shaped cells within a cylinder
affects the shape of the Jaccard index distributions, as
well as the range of Jaccard values, showing that both the
shape of particle and the domain may play a role. We also
find that the distribution is able to capture very similar
configurations through Jaccard index values greater than 95%
when appending several nearly identical configurations into
the data set.},
Doi = {10.1016/j.jocs.2023.102060},
Key = {fds371136}
}
@article{fds371517,
Author = {Tanade, C and Putney, S and Randles, A},
Title = {Establishing massively parallel models to examine the
influence of cell heterogeneity on tumor
growth},
Journal = {Journal of Computational Science},
Volume = {71},
Year = {2023},
Month = {July},
Abstract = {Parallel 3D cellular automaton models of tumor growth can
efficiently capture emergent morphology. We extended a 2D
growth model to 3D to examine the influence of symmetric
division in heterogeneous tumors on growth dynamics. As
extending to 3D severely increased time-to-solution, we
parallelized the model using N-body, lattice halo exchange,
and adaptive communication schemes. Supplementing prior work
from Tanade et al. (2022), we demonstrated over 55x speedup
and evaluated performance on ≤30 nodes of Stampede2. This
work established a framework to parametrically study 3D
growth dynamics, and of the cancer phenotypes we studied,
the parallel model better scaled when tumor boundaries were
radially symmetric.},
Doi = {10.1016/j.jocs.2023.102059},
Key = {fds371517}
}
@article{fds371671,
Author = {Feiger, B and Jensen, CW and Bryner, BS and Segars, WP and Randles,
A},
Title = {Modeling the effect of patient size on cerebral perfusion
during veno-arterial extracorporeal membrane
oxygenation.},
Journal = {Perfusion},
Pages = {2676591231187962},
Year = {2023},
Month = {July},
Abstract = {INTRODUCTION: A well-known complication of veno-arterial
extracorporeal membrane oxygenation (VA ECMO) is
differential hypoxia, in which poorly-oxygenated blood
ejected from the left ventricle mixes with and displaces
well-oxygenated blood from the circuit, thereby causing
cerebral hypoxia and ischemia. We sought to characterize the
impact of patient size and anatomy on cerebral perfusion
under a range of different VA ECMO flow conditions. METHODS:
We use one-dimensional (1D) flow simulations to investigate
mixing zone location and cerebral perfusion across 10
different levels of VA ECMO support in eight semi-idealized
patient geometries, for a total of 80 scenarios. Measured
outcomes included mixing zone location and cerebral blood
flow (CBF). RESULTS: Depending on patient anatomy, we found
that a VA ECMO support ranging between 67-97% of a patient's
ideal cardiac output was needed to perfuse the brain. In
some cases, VA ECMO flows exceeding 90% of the patient's
ideal cardiac output are needed for adequate cerebral
perfusion. CONCLUSIONS: Individual patient anatomy markedly
affects mixing zone location and cerebral perfusion in VA
ECMO. Future fluid simulations of VA ECMO physiology should
incorporate varied patient sizes and geometries in order to
best provide insights toward reducing neurologic injury and
improved outcomes in this patient population.},
Doi = {10.1177/02676591231187962},
Key = {fds371671}
}
@article{fds374022,
Author = {Roychowdhury, S and Balogh, P and Mahmud, ST and Puleri, DF and Martin,
A and Gounley, J and Draeger, EW and Randles, A},
Title = {Enhancing Adaptive Physics Refinement Simulations Through
the Addition of Realistic Red Blood Cell
Counts.},
Journal = {International Conference for High Performance Computing,
Networking, Storage and Analysis : [proceedings]. SC
(Conference : Supercomputing)},
Volume = {2023},
Pages = {41},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400701092},
Abstract = {Simulations of cancer cell transport require accurately
modeling mm-scale and longer trajectories through a
circulatory system containing trillions of deformable red
blood cells, whose intercellular interactions require
submicron fidelity. Using a hybrid CPU-GPU approach, we
extend the advanced physics refinement (APR) method to
couple a finely-resolved region of explicitly-modeled red
blood cells to a coarsely-resolved bulk fluid domain. We
further develop algorithms that: capture the dynamics at the
interface of differing viscosities, maintain hematocrit
within the cell-filled volume, and move the finely-resolved
region and encapsulated cells while tracking an individual
cancer cell. Comparison to a fully-resolved fluid-structure
interaction model is presented for verification. Finally, we
use the advanced APR method to simulate cancer cell
transport over a mm-scale distance while maintaining a local
region of RBCs, using a fraction of the computational power
required to run a fully-resolved model.},
Doi = {10.1145/3581784.3607105},
Key = {fds374022}
}
@article{fds374019,
Author = {Martin, A and Liu, G and Ladd, W and Lee, S and Gounley, J and Vetter, J and Patel, S and Rizzi, S and Mateevitsi, V and Insley, J and Randles,
A},
Title = {Performance Evaluation of Heterogeneous GPU Programming
Frameworks for Hemodynamic Simulations},
Journal = {ACM International Conference Proceeding Series},
Pages = {1126-1137},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400707858},
Abstract = {Preparing for the deployment of large scientific and
engineering codes on upcoming exascale systems with
GPU-dense nodes is made challenging by the unprecedented
diversity of device architectures and heterogeneous
programming models. In this work, we evaluate the process of
porting a massively parallel, fluid dynamics code written in
CUDA to SYCL, HIP, and Kokkos with a range of backends,
using a combination of automated tools and manual tuning. We
use a proxy application along with a custom performance
model to inform the results and identify additional
optimization strategies. At scale performance of the
programming model implementations are evaluated on
pre-production GPU node architectures for Frontier and
Aurora, as well as on current NVIDIA device-based systems
Summit and Polaris. Real-world workloads representing 3D
blood flow calculations in complex vasculature are assessed.
Our analysis highlights critical trade-offs between code
performance, portability, and development
time.},
Doi = {10.1145/3624062.3624188},
Key = {fds374019}
}
@article{fds374020,
Author = {Valero-Lara, P and Vetter, J and Gounley, J and Randles,
A},
Title = {Moment Representation of Regularized Lattice Boltzmann
Methods on NVIDIA and AMD GPUs},
Journal = {ACM International Conference Proceeding Series},
Pages = {1697-1704},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400707858},
Abstract = {The lattice Boltzmann method is a highly scalable
Navier-Stokes solver that has been applied to flow problems
in a wide array of domains. However, the method is
bandwidth-bound on modern GPU accelerators and has a large
memory footprint. In this paper, we present new 2D and 3D
GPU implementations of two different regularized lattice
Boltzmann methods, which are not only able to achieve an
acceleration of ~1.4 × w.r.t. reference lattice Boltzmann
implementations but also reduce the memory requirements by
up to 35% and 47% in 2D and 3D simulations respectively.
These new approaches are evaluated on NVIDIA and AMD GPU
architectures.},
Doi = {10.1145/3624062.3624250},
Key = {fds374020}
}
@article{fds374021,
Author = {Tanade, C and Rakestraw, E and Ladd, W and Draeger, E and Randles,
A},
Title = {Cloud Computing to Enable Wearable-Driven Longitudinal
Hemodynamic Maps},
Journal = {Proceedings of the International Conference for High
Performance Computing, Networking, Storage and Analysis, SC
2023},
Publisher = {ACM},
Year = {2023},
Month = {November},
ISBN = {9798400701092},
Abstract = {Tracking hemodynamic responses to treatment and stimuli over
long periods remains a grand challenge. Moving from
established single-heartbeat technology to longitudinal
profiles would require continuous data describing how the
patient's state evolves, new methods to extend the temporal
domain over which flow is sampled, and high-throughput
computing resources. While personalized digital twins can
accurately measure 3D hemodynamics over several heartbeats,
state-of-the-art methods would require hundreds of years of
wallclock time on leadership scale systems to simulate one
day of activity. To address these challenges, we propose a
cloud-based, parallel-in-time framework leveraging
continuous data from wearable devices to capture the first
3D patient-specific, longitudinal hemodynamic maps. We
demonstrate the validity of our method by establishing
ground truth data for 750 beats and comparing the results.
Our cloud-based framework is based on an initial fixed set
of simulations to enable the wearable-informed creation of
personalized longitudinal hemodynamic maps.},
Doi = {10.1145/3581784.3607101},
Key = {fds374021}
}
@article{fds374414,
Author = {Nan, J and Roychowdhury, S and Randles, A},
Title = {Investigating the Influence of Heterogeneity Within Cell
Types on Microvessel Network Transport.},
Journal = {Cellular and molecular bioengineering},
Volume = {16},
Number = {5-6},
Pages = {497-507},
Year = {2023},
Month = {December},
Abstract = {<h4>Background</h4>Current research on the biophysics of
circulating tumor cells often overlooks the heterogeneity of
cell populations, focusing instead on average cellular
properties. This study aims to address the gap by
considering the diversity of cell biophysical
characteristics and their implications on cancer
spread.<h4>Methods</h4>We utilized computer simulations to
assess the influence of variations in cell size and membrane
elasticity on the behavior of cells within fluid
environments. The study controlled cell and fluid properties
to systematically investigate the transport of tumor cells
through a simulated network of branching
channels.<h4>Results</h4>The simulations revealed that even
minor differences in cellular properties, such as slight
changes in cell radius or shear elastic modulus, lead to
significant changes in the fluid conditions that cells
experience, including velocity and wall shear stress
(p < 0.001).<h4>Conclusion</h4>The findings underscore
the importance of considering cell heterogeneity in
biophysical studies and suggest that small variations in
cellular characteristics can profoundly impact the dynamics
of tumor cell circulation. This has potential implications
for understanding the mechanisms of cancer metastasis and
the development of therapeutic strategies.},
Doi = {10.1007/s12195-023-00790-y},
Key = {fds374414}
}
@article{fds376265,
Author = {Chidyagwai, SG and Kaplan, MS and Jensen, CW and Chen, JS and Chamberlain, RC and Hill, KD and Barker, PCA and Slesnick, TC and Randles, A},
Title = {Surgical Modulation of Pulmonary Artery Shear Stress: A
Patient-Specific CFD Analysis of the Norwood
Procedure.},
Journal = {Cardiovasc Eng Technol},
Year = {2024},
Month = {March},
Abstract = {PURPOSR: This study created 3D CFD models of the Norwood
procedure for hypoplastic left heart syndrome (HLHS) using
standard angiography and echocardiogram data to investigate
the impact of shunt characteristics on pulmonary artery (PA)
hemodynamics. Leveraging routine clinical data offers
advantages such as availability and cost-effectiveness
without subjecting patients to additional invasive
procedures. METHODS: Patient-specific geometries of the
intrathoracic arteries of two Norwood patients were
generated from biplane cineangiograms. "Virtual surgery" was
then performed to simulate the hemodynamics of alternative
PA shunt configurations, including shunt type (modified
Blalock-Thomas-Taussig shunt (mBTTS) vs. right
ventricle-to-pulmonary artery shunt (RVPAS)), shunt
diameter, and pulmonary artery anastomosis angle. Left-right
pulmonary flow differential, Qp/Qs, time-averaged wall shear
stress (TAWSS), and oscillatory shear index (OSI) were
evaluated. RESULTS: There was strong agreement between
clinically measured data and CFD model output throughout the
patient-specific models. Geometries with a RVPAS tended
toward more balanced left-right pulmonary flow, lower Qp/Qs,
and greater TAWSS and OSI than models with a mBTTS. For both
shunt types, larger shunts resulted in a higher Qp/Qs and
higher TAWSS, with minimal effect on OSI. Low TAWSS areas
correlated with regions of low flow and changing the
PA-shunt anastomosis angle to face toward low TAWSS regions
increased TAWSS. CONCLUSION: Excellent correlation between
clinically measured and CFD model data shows that 3D CFD
models of HLHS Norwood can be developed using standard
angiography and echocardiographic data. The CFD analysis
also revealed consistent changes in PA TAWSS, flow
differential, and OSI as a function of shunt
characteristics.},
Doi = {10.1007/s13239-024-00724-3},
Key = {fds376265}
}