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Thangaraj PM, Benson SH, Oikonomou EK, Asselbergs FW, Khera R. Cardiovascular care with digital twin technology in the era of generative artificial intelligence. Eur Heart J 2024:ehae619. [PMID: 39322420 DOI: 10.1093/eurheartj/ehae619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2024] [Revised: 07/16/2024] [Accepted: 09/01/2024] [Indexed: 09/27/2024] Open
Abstract
Digital twins, which are in silico replications of an individual and its environment, have advanced clinical decision-making and prognostication in cardiovascular medicine. The technology enables personalized simulations of clinical scenarios, prediction of disease risk, and strategies for clinical trial augmentation. Current applications of cardiovascular digital twins have integrated multi-modal data into mechanistic and statistical models to build physiologically accurate cardiac replicas to enhance disease phenotyping, enrich diagnostic workflows, and optimize procedural planning. Digital twin technology is rapidly evolving in the setting of newly available data modalities and advances in generative artificial intelligence, enabling dynamic and comprehensive simulations unique to an individual. These twins fuse physiologic, environmental, and healthcare data into machine learning and generative models to build real-time patient predictions that can model interactions with the clinical environment to accelerate personalized patient care. This review summarizes digital twins in cardiovascular medicine and their potential future applications by incorporating new personalized data modalities. It examines the technical advances in deep learning and generative artificial intelligence that broaden the scope and predictive power of digital twins. Finally, it highlights the individual and societal challenges as well as ethical considerations that are essential to realizing the future vision of incorporating cardiology digital twins into personalized cardiovascular care.
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Affiliation(s)
- Phyllis M Thangaraj
- Section of Cardiology, Department of Internal Medicine, Yale School of Medicine, 789 Howard Ave., New Haven, CT, USA
| | - Sean H Benson
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Evangelos K Oikonomou
- Section of Cardiology, Department of Internal Medicine, Yale School of Medicine, 789 Howard Ave., New Haven, CT, USA
| | - Folkert W Asselbergs
- Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Center, University College London, London, UK
| | - Rohan Khera
- Section of Cardiology, Department of Internal Medicine, Yale School of Medicine, 789 Howard Ave., New Haven, CT, USA
- Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, 47 College St., New Haven, CT, USA
- Department of Biomedical Informatics and Data Science, Yale School of Medicine, 100 College St. Fl 9, New Haven, CT, USA
- Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, 195 Church St. Fl 6, New Haven, CT 06510, USA
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2
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Menon K, Zanoni A, Khan O, Geraci G, Nieman K, Schiavazzi DE, Marsden AL. Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification. ARXIV 2024:arXiv:2409.02247v1. [PMID: 39279834 PMCID: PMC11398544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
Background Non-invasive simulations of coronary hemodynamics have improved clinical risk stratification and treatment outcomes for coronary artery disease, compared to relying on anatomical imaging alone. However, simulations typically use empirical approaches to distribute total coronary flow amongst the arteries in the coronary tree, which ignores patient variability, the presence of disease, and other clinical factors. Further, uncertainty in the clinical data often remains unaccounted for in the modeling pipeline. Objective We present an end-to-end uncertainty-aware pipeline to (1) personalize coronary flow simulations by incorporating vessel-specific coronary flows as well as cardiac function; and (2) predict clinical and biomechanical quantities of interest with improved precision, while accounting for uncertainty in the clinical data. Methods We assimilate patient-specific measurements of myocardial blood flow from clinical CT myocardial perfusion imaging to estimate branch-specific coronary artery flows. Simulated noise in the clinical data is used to estimate the joint posterior distributions of the model parameters using adaptive Markov Chain Monte Carlo sampling. Additionally, the posterior predictive distribution for the relevant quantities of interest is determined using a new approach combining multi-fidelity Monte Carlo estimation with non-linear, data-driven dimensionality reduction. This leads to improved correlations between high- and low-fidelity model outputs. Results Our framework accurately recapitulates clinically measured cardiac function as well as branch-specific coronary flows under measurement noise uncertainty. We observe substantial reductions in confidence intervals for estimated quantities of interest compared to single-fidelity Monte Carlo estimation and state-of-the-art multi-fidelity Monte Carlo methods. This holds especially true for quantities of interest that showed limited correlation between the low- and high-fidelity model predictions. In addition, the proposed multi-fidelity Monte Carlo estimators are significantly cheaper to compute than traditional estimators, under a specified confidence level or variance. Conclusions The proposed pipeline for personalized and uncertainty-aware predictions of coronary hemodynamics is based on routine clinical measurements and recently developed techniques for CT myocardial perfusion imaging. The proposed pipeline offers significant improvements in precision and reduction in computational cost.
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Affiliation(s)
- Karthik Menon
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Andrea Zanoni
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Owais Khan
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON, Canada
| | - Gianluca Geraci
- Center for Computing Research, Sandia National Laboratories, Albuquerque, NM, USA
| | - Koen Nieman
- Division of Cardiovascular Medicine, Stanford School of Medicine, Stanford, CA, USA
- Department of Radiology, Stanford School of Medicine, Stanford, CA, USA
| | - Daniele E Schiavazzi
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA
| | - Alison L Marsden
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
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3
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Lucca A, Fraccarollo L, Fossan FE, Bråten AT, Pozzi S, Vergara C, Müller LO. Impact of Pressure Guidewire on Model-Based FFR Prediction. Cardiovasc Eng Technol 2024; 15:251-263. [PMID: 38438691 PMCID: PMC11239750 DOI: 10.1007/s13239-024-00710-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 01/02/2024] [Indexed: 03/06/2024]
Abstract
INTRODUCTION Fractional Flow Reserve (FFR) is used to characterize the functional significance of coronary artery stenoses. FFR is assessed under hyperemic conditions by invasive measurements of trans-stenotic pressure thanks to the insertion of a pressure guidewire across the coronary stenosis during catheterization. In order to overcome the potential risk related to the invasive procedure and to reduce the associated high costs, three-dimensional blood flow simulations that incorporate clinical imaging and patient-specific characteristics have been proposed. PURPOSE Most CCTA-derived FFR models neglect the potential influence of the guidewire on computed flow and pressure. Here we aim to quantify the impact of taking into account the presence of the guidewire in model-based FFR prediction. METHODS We adopt a CCTA-derived FFR model and perform simulations with and without the guidewire for 18 patients with suspected stable CAD. RESULTS Presented results show that the presence of the guidewire leads to a tendency to predict a lower FFR value. The FFR reduction is prominent in cases of severe stenoses, while the influence of the guidewire is less pronounced in cases of moderate stenoses. CONCLUSION From a clinical decision-making point of view, including of the pressure guidewire is potentially relevant only for intermediate stenosis cases.
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Affiliation(s)
- Alessia Lucca
- Department of Mathematics, University of Trento, Via Sommarive, 14, 38123, Trento, Italy.
| | | | - Fredrik E Fossan
- Department of Structural Engineering, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anders T Bråten
- Department of Cardiology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Silvia Pozzi
- MOX, Dipartimento di Matematica, Politecnico di Milano, Milan, Italy
| | - Christian Vergara
- LABS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Lucas O Müller
- Department of Mathematics, University of Trento, Via Sommarive, 14, 38123, Trento, Italy
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4
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Menon K, Khan MO, Sexton ZA, Richter J, Nguyen PK, Malik SB, Boyd J, Nieman K, Marsden AL. Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees. NPJ IMAGING 2024; 2:9. [PMID: 38706558 PMCID: PMC11062925 DOI: 10.1038/s44303-024-00014-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 02/25/2024] [Indexed: 05/07/2024]
Abstract
Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary anatomies combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. We propose an optimization-based method to personalize multiscale coronary flow simulations by assimilating clinical CT myocardial perfusion imaging and cardiac function measurements to yield patient-specific flow distributions and model parameters. Using this proof-of-concept study on a cohort of six patients, we reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based purely on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.
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Affiliation(s)
- Karthik Menon
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA USA
| | - Muhammed Owais Khan
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON Canada
| | | | - Jakob Richter
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA USA
| | - Patricia K. Nguyen
- VA Palo Alto Healthcare System, Palo Alto, CA USA
- Division of Cardiovascular Medicine, Stanford School of Medicine, Stanford, CA USA
| | | | - Jack Boyd
- Department of Cardiothoracic Surgery, Stanford School of Medicine, Stanford, CA USA
| | - Koen Nieman
- Division of Cardiovascular Medicine, Stanford School of Medicine, Stanford, CA USA
- Department of Radiology, Stanford School of Medicine, Stanford, CA USA
| | - Alison L. Marsden
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA USA
- Department of Bioengineering, Stanford University, Stanford, CA USA
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5
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Szafron JM, Heng EE, Boyd J, Humphrey JD, Marsden AL. Hemodynamics and Wall Mechanics of Vascular Graft Failure. Arterioscler Thromb Vasc Biol 2024; 44:1065-1085. [PMID: 38572650 PMCID: PMC11043008 DOI: 10.1161/atvbaha.123.318239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 03/12/2024] [Indexed: 04/05/2024]
Abstract
Blood vessels are subjected to complex biomechanical loads, primarily from pressure-driven blood flow. Abnormal loading associated with vascular grafts, arising from altered hemodynamics or wall mechanics, can cause acute and progressive vascular failure and end-organ dysfunction. Perturbations to mechanobiological stimuli experienced by vascular cells contribute to remodeling of the vascular wall via activation of mechanosensitive signaling pathways and subsequent changes in gene expression and associated turnover of cells and extracellular matrix. In this review, we outline experimental and computational tools used to quantify metrics of biomechanical loading in vascular grafts and highlight those that show potential in predicting graft failure for diverse disease contexts. We include metrics derived from both fluid and solid mechanics that drive feedback loops between mechanobiological processes and changes in the biomechanical state that govern the natural history of vascular grafts. As illustrative examples, we consider application-specific coronary artery bypass grafts, peripheral vascular grafts, and tissue-engineered vascular grafts for congenital heart surgery as each of these involves unique circulatory environments, loading magnitudes, and graft materials.
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Affiliation(s)
- Jason M Szafron
- Departments of Pediatrics (J.M.S., A.L.M.), Stanford University, CA
| | - Elbert E Heng
- Cardiothoracic Surgery (E.E.H., J.B.), Stanford University, CA
| | - Jack Boyd
- Cardiothoracic Surgery (E.E.H., J.B.), Stanford University, CA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT (J.D.H.)
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6
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MacRaild M, Sarrami-Foroushani A, Lassila T, Frangi AF. Accelerated simulation methodologies for computational vascular flow modelling. J R Soc Interface 2024; 21:20230565. [PMID: 38350616 PMCID: PMC10864099 DOI: 10.1098/rsif.2023.0565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 01/12/2024] [Indexed: 02/15/2024] Open
Abstract
Vascular flow modelling can improve our understanding of vascular pathologies and aid in developing safe and effective medical devices. Vascular flow models typically involve solving the nonlinear Navier-Stokes equations in complex anatomies and using physiological boundary conditions, often presenting a multi-physics and multi-scale computational problem to be solved. This leads to highly complex and expensive models that require excessive computational time. This review explores accelerated simulation methodologies, specifically focusing on computational vascular flow modelling. We review reduced order modelling (ROM) techniques like zero-/one-dimensional and modal decomposition-based ROMs and machine learning (ML) methods including ML-augmented ROMs, ML-based ROMs and physics-informed ML models. We discuss the applicability of each method to vascular flow acceleration and the effectiveness of the method in addressing domain-specific challenges. When available, we provide statistics on accuracy and speed-up factors for various applications related to vascular flow simulation acceleration. Our findings indicate that each type of model has strengths and limitations depending on the context. To accelerate real-world vascular flow problems, we propose future research on developing multi-scale acceleration methods capable of handling the significant geometric variability inherent to such problems.
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Affiliation(s)
- Michael MacRaild
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), University of Leeds, Leeds, UK
- EPSRC Centre for Doctoral Training in Fluid Dynamics, University of Leeds, Leeds, UK
| | - Ali Sarrami-Foroushani
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), University of Leeds, Leeds, UK
- School of Health Science, University of Manchester, Manchester, UK
| | - Toni Lassila
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), University of Leeds, Leeds, UK
- School of Computing, University of Leeds, Leeds, UK
| | - Alejandro F. Frangi
- Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB), University of Leeds, Leeds, UK
- School of Computer Science, University of Manchester, Manchester, UK
- School of Health Science, University of Manchester, Manchester, UK
- Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
- Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
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7
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Samant S, Bakhos JJ, Wu W, Zhao S, Kassab GS, Khan B, Panagopoulos A, Makadia J, Oguz UM, Banga A, Fayaz M, Glass W, Chiastra C, Burzotta F, LaDisa JF, Iaizzo P, Murasato Y, Dubini G, Migliavacca F, Mickley T, Bicek A, Fontana J, West NEJ, Mortier P, Boyers PJ, Gold JP, Anderson DR, Tcheng JE, Windle JR, Samady H, Jaffer FA, Desai NR, Lansky A, Mena-Hurtado C, Abbott D, Brilakis ES, Lassen JF, Louvard Y, Stankovic G, Serruys PW, Velazquez E, Elias P, Bhatt DL, Dangas G, Chatzizisis YS. Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions. JACC Cardiovasc Interv 2023; 16:2479-2497. [PMID: 37879802 DOI: 10.1016/j.jcin.2023.07.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 07/11/2023] [Accepted: 07/13/2023] [Indexed: 10/27/2023]
Abstract
Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.
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Affiliation(s)
- Saurabhi Samant
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Jules Joel Bakhos
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Wei Wu
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Shijia Zhao
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Ghassan S Kassab
- California Medical Innovations Institute, San Diego, California, USA
| | - Behram Khan
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Anastasios Panagopoulos
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Janaki Makadia
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Usama M Oguz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Akshat Banga
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Muhammad Fayaz
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - William Glass
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Claudio Chiastra
- PoliTo(BIO)Med Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Francesco Burzotta
- Department of Cardiovascular Sciences, Università Cattolica Del Sacro Cuore, Rome, Italy
| | - John F LaDisa
- Departments of Biomedical Engineering and Pediatrics - Division of Cardiology, Herma Heart Institute, Children's Wisconsin and the Medical College of Wisconsin, and the MARquette Visualization Lab, Marquette University, Milwaukee, Wisconsin, USA
| | - Paul Iaizzo
- Visible Heart Laboratories, Department of Surgery, University of Minnesota, Minnesota, USA
| | - Yoshinobu Murasato
- Department of Cardiology, National Hospital Organization Kyushu Medical Center, Fukuoka, Japan
| | - Gabriele Dubini
- Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Milan, Italy
| | - Francesco Migliavacca
- Department of Chemistry, Materials and Chemical Engineering 'Giulio Natta', Politecnico di Milano, Milan, Italy
| | | | - Andrew Bicek
- Boston Scientific Inc, Marlborough, Massachusetts, USA
| | | | | | | | - Pamela J Boyers
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Jeffrey P Gold
- Interprofessional Experiential Center for Enduring Learning, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Daniel R Anderson
- Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - James E Tcheng
- Cardiovascular Division, Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina, USA
| | - John R Windle
- Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Habib Samady
- Georgia Heart Institute, Gainesville, Georgia, USA
| | - Farouc A Jaffer
- Cardiology Division, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Nihar R Desai
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Alexandra Lansky
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Carlos Mena-Hurtado
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Dawn Abbott
- Cardiovascular Institute, Warren Alpert Medical School at Brown University, Providence, Rhode Island, USA
| | - Emmanouil S Brilakis
- Center for Advanced Coronary Interventions, Minneapolis Heart Institute, Minneapolis, Minnesota, USA
| | - Jens Flensted Lassen
- Department of Cardiology B, Odense University Hospital, Odense, Syddanmark, Denmark
| | - Yves Louvard
- Institut Cardiovasculaire Paris Sud, Massy, France
| | - Goran Stankovic
- Department of Cardiology, Clinical Center of Serbia, Belgrade, Serbia
| | - Patrick W Serruys
- Department of Cardiology, National University of Ireland, Galway, Galway, Ireland
| | - Eric Velazquez
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Pierre Elias
- Seymour, Paul, and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, NewYork-Presbyterian Hospital, New York, New York, USA
| | - Deepak L Bhatt
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - George Dangas
- Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yiannis S Chatzizisis
- Center for Digital Cardiovascular Innovations, Division of Cardiovascular Medicine, University of Miami Miller School of Medicine, Miami, Florida, USA; Cardiovascular Biology and Biomechanics Laboratory (CBBL), Cardiovascular Division, University of Nebraska Medical Center, Omaha, Nebraska, USA.
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Menon K, Khan MO, Sexton ZA, Richter J, Nieman K, Marsden AL. Personalized coronary and myocardial blood flow models incorporating CT perfusion imaging and synthetic vascular trees. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.17.23294242. [PMID: 37645850 PMCID: PMC10462196 DOI: 10.1101/2023.08.17.23294242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Computational simulations of coronary artery blood flow, using anatomical models based on clinical imaging, are an emerging non-invasive tool for personalized treatment planning. However, current simulations contend with two related challenges - incomplete anatomies in image-based models due to the exclusion of arteries smaller than the imaging resolution, and the lack of personalized flow distributions informed by patient-specific imaging. We introduce a data-enabled, personalized and multi-scale flow simulation framework spanning large coronary arteries to myocardial microvasculature. It includes image-based coronary models combined with synthetic vasculature for arteries below the imaging resolution, myocardial blood flow simulated using Darcy models, and systemic circulation represented as lumped-parameter networks. Personalized flow distributions and model parameters are informed by clinical CT myocardial perfusion imaging and cardiac function using surrogate-based optimization. We reveal substantial differences in flow distributions and clinical diagnosis metrics between the proposed personalized framework and empirical methods based on anatomy; these errors cannot be predicted a priori. This suggests virtual treatment planning tools would benefit from increased personalization informed by emerging imaging methods.
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Affiliation(s)
- Karthik Menon
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Muhammed Owais Khan
- Department of Electrical, Computer, and Biomedical Engineering, Toronto Metropolitan University, Toronto, Ontario, Canada
| | - Zachary A Sexton
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Jakob Richter
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
| | - Koen Nieman
- Departments of Radiology and Medicine (Cardiovascular Medicine), Stanford School of Medicine, Stanford, CA, USA
| | - Alison L Marsden
- Department of Pediatrics (Cardiology), Stanford School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
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9
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Xenakis A, Ruiz-Soler A, Keshmiri A. Multi-Objective Optimisation of a Novel Bypass Graft with a Spiral Ridge. Bioengineering (Basel) 2023; 10:489. [PMID: 37106676 PMCID: PMC10136357 DOI: 10.3390/bioengineering10040489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/04/2023] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
The low long-term patency of bypass grafts is a major concern for cardiovascular treatments. Unfavourable haemodynamic conditions in the proximity of distal anastomosis are closely related to thrombus creation and lumen lesions. Modern graft designs address this unfavourable haemodynamic environment with the introduction of a helical component in the flow field, either by means of out-of-plane helicity graft geometry or a spiral ridge. While the latter has been found to lack in performance when compared to the out-of-plane helicity designs, recent findings support the idea that the existing spiral ridge grafts can be further improved in performance through optimising relevant design parameters. In the current study, robust multi-objective optimisation techniques are implemented, covering a wide range of possible designs coupled with proven and well validated computational fluid dynamics (CFD) algorithms. It is shown that the final set of suggested design parameters could significantly improve haemodynamic performance and therefore could be used to enhance the design of spiral ridge bypass grafts.
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Affiliation(s)
- Antonios Xenakis
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
| | - Andres Ruiz-Soler
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
| | - Amir Keshmiri
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
- Department of Cardiothoracic Surgery, Manchester University NHS Foundation Trust, Manchester M13 9WL, UK
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Tran-Nguyen N, Yan AT, Fremes S, Triverio P, Jimenez-Juan L. Abnormal Wall Shear Stress Area is Correlated to Coronary Artery Bypass Graft Remodeling 1 Year After Surgery. Ann Biomed Eng 2023:10.1007/s10439-023-03167-4. [PMID: 36871052 DOI: 10.1007/s10439-023-03167-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 02/12/2023] [Indexed: 03/06/2023]
Abstract
Coronary artery bypass graft surgery is a common intervention for coronary artery disease; however, it suffers from graft failure, and the underlying mechanisms are not fully understood. To better understand the relation between graft hemodynamics and surgical outcomes, we performed computational fluid dynamics simulations with deformable vessel walls in 10 study participants (24 bypass grafts) based on CT and 4D flow MRI one month after surgery to quantify lumen diameter, wall shear stress (WSS), and related hemodynamic measures. A second CT acquisition was performed one year after surgery to quantify lumen remodeling. Compared to venous grafts, left internal mammary artery grafts experienced lower abnormal WSS (< 1 Pa) area one month after surgery (13.8 vs. 70.1%, p = 0.001) and less inward lumen remodeling one year after surgery (- 2.4% vs. - 16.1%, p = 0.027). Abnormal WSS area one month post surgery correlated with percent change in graft lumen diameter one year post surgery (p = 0.030). This study shows for the first time prospectively a correlation between abnormal WSS area one month post surgery and graft lumen remodeling 1 year post surgery, suggesting that shear-related mechanisms may play a role in post-operative graft remodeling and might help explain differences in failure rates between arterial and venous grafts.
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Affiliation(s)
- Nhien Tran-Nguyen
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
| | - Andrew T Yan
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- St. Michael's Hospital, Toronto, ON, Canada
| | - Stephen Fremes
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Sunnybrook Research Institute, Toronto, ON, Canada
| | - Piero Triverio
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Laura Jimenez-Juan
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- St. Michael's Hospital, Toronto, ON, Canada
- Sunnybrook Research Institute, Toronto, ON, Canada
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11
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Schwarz EL, Pegolotti L, Pfaller MR, Marsden AL. Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease. BIOPHYSICS REVIEWS 2023; 4:011301. [PMID: 36686891 PMCID: PMC9846834 DOI: 10.1063/5.0109400] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/12/2022] [Indexed: 01/15/2023]
Abstract
Physics-based computational models of the cardiovascular system are increasingly used to simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and diseased states. While predictive models using computational fluid dynamics (CFD) originated primarily for use in surgical planning, their application now extends well beyond this purpose. In this review, we describe an increasingly wide range of modeling applications aimed at uncovering fundamental mechanisms of disease progression and development, performing model-guided design, and generating testable hypotheses to drive targeted experiments. Increasingly, models are incorporating multiple physical processes spanning a wide range of time and length scales in the heart and vasculature. With these expanded capabilities, clinical adoption of patient-specific modeling in congenital and acquired cardiovascular disease is also increasing, impacting clinical care and treatment decisions in complex congenital heart disease, coronary artery disease, vascular surgery, pulmonary artery disease, and medical device design. In support of these efforts, we discuss recent advances in modeling methodology, which are most impactful when driven by clinical needs. We describe pivotal recent developments in image processing, fluid-structure interaction, modeling under uncertainty, and reduced order modeling to enable simulations in clinically relevant timeframes. In all these areas, we argue that traditional CFD alone is insufficient to tackle increasingly complex clinical and biological problems across scales and systems. Rather, CFD should be coupled with appropriate multiscale biological, physical, and physiological models needed to produce comprehensive, impactful models of mechanobiological systems and complex clinical scenarios. With this perspective, we finally outline open problems and future challenges in the field.
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Affiliation(s)
- Erica L. Schwarz
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Luca Pegolotti
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Martin R. Pfaller
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Alison L. Marsden
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, California 94305, USA
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12
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Tran-Nguyen N, Condemi F, Yan A, Fremes S, Triverio P, Jimenez-Juan L. Wall Shear Stress Differences Between Arterial and Venous Coronary Artery Bypass Grafts One Month After Surgery. Ann Biomed Eng 2022; 50:1882-1894. [PMID: 35881267 DOI: 10.1007/s10439-022-03007-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 07/02/2022] [Indexed: 12/30/2022]
Abstract
Although coronary artery bypass graft (CABG) surgery is a well-established intervention, graft failure can occur, and the underlying mechanisms remain incompletely understood. The purpose of this prospective study is to utilize computational fluid dynamics (CFD) to investigate how graft hemodynamics one month post surgery may vary among graft types, which have different long-term patency rates. Twenty-four grafts from 10 participants (64.6 ± 8.5 years, 9 men) were scanned with coronary CT angiography and 4D flow MRI one month after CABG surgery. Grafts included 10 left internal mammary arteries (LIMA), 3 radial arteries (RA), and 11 saphenous vein grafts (SVG). Image-guided CFD was used to quantify blood flow rate and wall area exposed to abnormal wall shear stress (WSS). Arterial grafts had a lower abnormal WSS area than venous grafts (17.9% vs. 70.1%; p = 0.001), and a similar trend was observed for LIMA vs. SVG (13.8% vs. 70.1%; p = 0.001). Abnormal WSS area correlated positively to lumen diameter (p < 0.001) and negatively to flow rate (p = 0.001). This CFD study is the first of its kind to prospectively reveal differences in abnormal WSS area 1 month post surgery among CABG types, suggesting that WSS may influence the differential long-term graft failure rates observed among these groups.
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Affiliation(s)
- Nhien Tran-Nguyen
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
| | | | - Andrew Yan
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- St. Michael's Hospital, Toronto, ON, Canada
| | - Stephen Fremes
- Department of Surgery, University of Toronto, Toronto, ON, Canada
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Sunnybrook Research Institute, Toronto, ON, Canada
| | - Piero Triverio
- Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
- Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Laura Jimenez-Juan
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- St. Michael's Hospital, Toronto, ON, Canada
- Sunnybrook Research Institute, Toronto, ON, Canada
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13
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Sadeghi R, Tomka B, Khodaei S, Daeian M, Gandhi K, Garcia J, Keshavarz-Motamed Z. Impact of extra-anatomical bypass on coarctation fluid dynamics using patient-specific lumped parameter and Lattice Boltzmann modeling. Sci Rep 2022; 12:9718. [PMID: 35690596 PMCID: PMC9188592 DOI: 10.1038/s41598-022-12894-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 04/11/2022] [Indexed: 01/28/2023] Open
Abstract
Accurate hemodynamic analysis is not only crucial for successful diagnosis of coarctation of the aorta (COA), but intervention decisions also rely on the hemodynamics assessment in both pre and post intervention states to minimize patient risks. Despite ongoing advances in surgical techniques for COA treatments, the impacts of extra-anatomic bypass grafting, a surgical technique to treat COA, on the aorta are not always benign. Our objective was to investigate the impact of bypass grafting on aortic hemodynamics. We investigated the impact of bypass grafting on aortic hemodynamics using a patient-specific computational-mechanics framework in three patients with COA who underwent bypass grafting. Our results describe that bypass grafting improved some hemodynamic metrics while worsened the others: (1) Doppler pressure gradient improved (decreased) in all patients; (2) Bypass graft did not reduce the flow rate substantially through the COA; (3) Systemic arterial compliance increased in patients #1 and 3 and didn't change (improve) in patient 3; (4) Hypertension got worse in all patients; (5) The flow velocity magnitude improved (reduced) in patient 2 and 3 but did not improve significantly in patient 1; (6) There were elevated velocity magnitude, persistence of vortical flow structure, elevated turbulence characteristics, and elevated wall shear stress at the bypass graft junctions in all patients. We concluded that bypass graft may lead to pseudoaneurysm formation and potential aortic rupture as well as intimal hyperplasia due to the persistent abnormal and irregular aortic hemodynamics in some patients. Moreover, post-intervention, exposures of endothelial cells to high shear stress may lead to arterial remodeling, aneurysm, and rupture.
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Affiliation(s)
- Reza Sadeghi
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Benjamin Tomka
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Seyedvahid Khodaei
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - MohammadAli Daeian
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Krishna Gandhi
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON
| | - Julio Garcia
- grid.489011.50000 0004 0407 3514Stephenson Cardiac Imaging Centre, Libin Cardiovascular Institute of Alberta, Calgary, AB Canada ,grid.22072.350000 0004 1936 7697Department of Radiology, University of Calgary, Calgary, AB Canada ,grid.22072.350000 0004 1936 7697Department of Cardiac Sciences, University of Calgary, Calgary, AB Canada ,grid.413571.50000 0001 0684 7358Alberta Children’s Hospital Research Institute, Calgary, AB Canada
| | - Zahra Keshavarz-Motamed
- grid.25073.330000 0004 1936 8227Department of Mechanical Engineering, McMaster University, Hamilton, Canada ON ,grid.25073.330000 0004 1936 8227School of Biomedical Engineering, McMaster University, Hamilton, ON Canada ,grid.25073.330000 0004 1936 8227School of Computational Science and Engineering, McMaster University, Hamilton, ON Canada
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14
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Pfaller MR, Pham J, Wilson NM, Parker DW, Marsden AL. On the Periodicity of Cardiovascular Fluid Dynamics Simulations. Ann Biomed Eng 2021; 49:3574-3592. [PMID: 34169398 PMCID: PMC9831274 DOI: 10.1007/s10439-021-02796-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/12/2021] [Indexed: 01/12/2023]
Abstract
Three-dimensional cardiovascular fluid dynamics simulations typically require computation of several cardiac cycles before they reach a periodic solution, rendering them computationally expensive. Furthermore, there is currently no standardized method to determine whether a simulation has yet reached that periodic state. In this work, we propose the use of an asymptotic error measurement to quantify the difference between simulation results and their ideal periodic state using open-loop lumped-parameter modeling. We further show that initial conditions are crucial in reducing computational time and develop an automated framework to generate appropriate initial conditions from a one-dimensional model of blood flow. We demonstrate the performance of our initialization method using six patient-specific models from the Vascular Model Repository. In our examples, our initialization protocol achieves periodic convergence within one or two cardiac cycles, leading to a significant reduction in computational cost compared to standard methods. All computational tools used in this work are implemented in the open-source software platform SimVascular. Automatically generated initial conditions have the potential to significantly reduce computation time in cardiovascular fluid dynamics simulations.
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Affiliation(s)
- Martin R Pfaller
- Department of Pediatrics (Cardiology), Institute for Computational and Mathematical Engineering, Bioengineering, Stanford University, Stanford, USA.
| | - Jonathan Pham
- Department of Mechanical Engineering, Stanford University, Stanford, USA
| | | | - David W Parker
- Stanford Research Computing, Stanford University, Stanford, USA
| | - Alison L Marsden
- Department of Pediatrics (Cardiology), Institute for Computational and Mathematical Engineering, Bioengineering, Stanford University, Stanford, USA
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15
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Khan MO, Tran JS, Zhu H, Boyd J, Packard RRS, Karlsberg RP, Kahn AM, Marsden AL. Low Wall Shear Stress Is Associated with Saphenous Vein Graft Stenosis in Patients with Coronary Artery Bypass Grafting. J Cardiovasc Transl Res 2021; 14:770-781. [PMID: 32240496 PMCID: PMC7529767 DOI: 10.1007/s12265-020-09982-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 02/28/2020] [Indexed: 12/21/2022]
Abstract
Biomechanical forces may play a key role in saphenous vein graft (SVG) disease after coronary artery bypass graft (CABG) surgery. Computed tomography angiography (CTA) of 430 post-CABG patients were evaluated and 15 patients were identified with both stenosed and healthy SVGs for paired analysis. The stenosis was virtually removed, and detailed 3D models were reconstructed to perform patient-specific computational fluid dynamic (CFD) simulations. Models were processed to compute anatomic parameters, and hemodynamic parameters such as local and vessel-averaged wall shear stress (WSS), normalized WSS (WSS*), low shear area (LSA), oscillatory shear index (OSI), and flow rate. WSS* was significantly lower in pre-diseased SVG segments compared to corresponding control segments without disease (1.22 vs. 1.73, p = 0.012) and the area under the ROC curve was 0.71. No differences were observed in vessel-averaged anatomic or hemodynamic parameters between pre-stenosed and control whole SVGs. There are currently no clinically available tools to predict SVG failure post-CABG. CFD modeling has the potential to identify high-risk CABG patients who may benefit from more aggressive medical therapy and closer surveillance. Graphical Abstract.
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Affiliation(s)
- Muhammad Owais Khan
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Justin S Tran
- Department of Mechanical Engineering, California State University Fullerton, Fullerton, CA, USA
| | - Han Zhu
- Department of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Jack Boyd
- Department of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA, USA
| | - René R Sevag Packard
- Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ronald P Karlsberg
- Cardiovascular Medical Group of Southern California, Beverly Hills, CA, USA
| | - Andrew M Kahn
- Division of Cardiovascular Medicine, University of California San Diego, La Jolla, CA, USA.
| | - Alison L Marsden
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA.
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
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16
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Seo J, Ramachandra AB, Boyd J, Marsden AL, Kahn AM. Computational Evaluation of Venous Graft Geometries in Coronary Artery Bypass Surgery. Semin Thorac Cardiovasc Surg 2021; 34:521-532. [PMID: 33711465 PMCID: PMC8429518 DOI: 10.1053/j.semtcvs.2021.03.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 03/04/2021] [Indexed: 11/11/2022]
Abstract
Cardiothoracic surgeons are faced with a choice of different revascularization techniques and diameters for saphenous vein grafts (SVG) in coronary artery bypass graft surgery . Using computational simulations, we virtually investigate the effect of SVG geometry on hemodynamics of both venous grafts and the target coronary arteries. We generated patient-specific 3-dimensional anatomic models of coronary artery bypass graft surgery patients and quantified mechanical stimuli. We performed virtual surgery on 3 patient-specific models by modifying the geometry vein grafts to reflect single, Y, and sequential surgical configurations with SVG diameters ranging from 2 mm to 5 mm. Our study demonstrates that the coronary artery runoffs are relatively insensitive to the choice of SVG revascularization geometry. We observe a 10% increase in runoff when the SVG diameter is changed from 2 mm to 5 mm. The wall shear stress of SVG increases dramatically when the diameter drops, following an inverse power scaling with diameter. For a fixed diameter, the average wall shear stress on the vein graft varies in ascending order as single, Y, and sequential graft in the patient cohort. The runoff to the target coronary arteries changes marginally due to the choice of graft configuration or diameter. The shear stress on the vein graft depends on both flow rate and diameter and follows an inverse power scaling consistent with a Poiseuille flow assumption. Given the similarity in runoff with different surgical configurations, choices of SVG geometries can be informed by propensity for graft failure using shear stress evaluations.
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Affiliation(s)
- Jongmin Seo
- Departments of Pediatrics (Cardiology), Stanford University, Stanford, California; Departments of Bioengineering, Stanford University, Stanford, California
| | - Abhay B Ramachandra
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - Jack Boyd
- Departments of Cardiothoracic Surgery, and Stanford University, Stanford, California
| | - Alison L Marsden
- Departments of Pediatrics (Cardiology), Stanford University, Stanford, California; Departments of Bioengineering, Stanford University, Stanford, California
| | - Andrew M Kahn
- Division of Cardiovascular Medicine, University of California San Diego, La Jolla, California.
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17
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Alizadehghobadi S, Biglari H, Niroomand-Oscuii H, Matin MH. Numerical study of hemodynamics in a complete coronary bypass with venous and arterial grafts and different degrees of stenosis. Comput Methods Biomech Biomed Engin 2020; 24:883-896. [PMID: 33307817 DOI: 10.1080/10255842.2020.1857744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Cardiovascular diseases are among the leading causes of death in the world. The coronary blockage is one of most common types of these diseases that in the majority of cases has been treated by bypass surgery. In the bypass surgery, a graft is implemented to alter the blocked coronary and allow the blood supply process. The hemodynamic characteristics of the bypass strongly depend on the geometry and mechanical properties of the graft. In the present study, the fluid-structure interaction (FSI) analysis is conducted to investigate the bypass performance for a thoracic artery as well as a saphenous vein graft. Blood flow introduces a pressure on the walls of the graft which behaves as a hyperelastic material. A complete coronary bypass with stenosis degrees of 70% and 100% is modeled. To consider the nonlinear stress-strain behavior of the grafts, a five parameter Mooney-Rivlin hyperplastic model is implemented for the structural analysis and blood is assumed to behave as a Newtonian fluid. The simulations are performed for a structured grid to solve the governing equations using finite element method (FEM). The results show that wall shear stress (WSS) for saphenous vein is larger than that of thoracic artery while the total deformation of the thoracic artery is larger compared to the saphenous vein. Also, for the venous grafts or lower stenosis degree, the oscillatory shear index (OSI) is higher at both left and right anastomoses meaning that venous grafts as well as lower degree of stenosis are more critical in terms of restenosis.
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Affiliation(s)
| | - Hasan Biglari
- Department of Mechanical Engineering, University of Tabriz, Tabriz, Iran
| | | | - Meisam H Matin
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA
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18
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Seo J, Schiavazzi DE, Kahn AM, Marsden AL. The effects of clinically-derived parametric data uncertainty in patient-specific coronary simulations with deformable walls. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2020; 36:e3351. [PMID: 32419369 PMCID: PMC8211426 DOI: 10.1002/cnm.3351] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 02/20/2020] [Accepted: 05/09/2020] [Indexed: 05/31/2023]
Abstract
Cardiovascular simulations are increasingly used for noninvasive diagnosis of cardiovascular disease, to guide treatment decisions, and in the design of medical devices. Quantitative assessment of the variability of simulation outputs due to input uncertainty is a key step toward further integration of cardiovascular simulations in the clinical workflow. In this study, we present uncertainty quantification in computational models of the coronary circulation to investigate the effect of uncertain parameters, including coronary pressure waveform, intramyocardial pressure, morphometry exponent, and the vascular wall Young's modulus. We employ a left coronary artery model with deformable vessel walls, simulated via an Arbitrary-Lagrangian-Eulerian framework for fluid-structure interaction, with a prescribed inlet pressure and open-loop lumped parameter network outlet boundary conditions. Stochastic modeling of the uncertain inputs is determined from intra-coronary catheterization data or gathered from the literature. Uncertainty propagation is performed using several approaches including Monte Carlo, Quasi Monte Carlo sampling, stochastic collocation, and multi-wavelet stochastic expansion. Variabilities in the quantities of interest, including branch pressure, flow, wall shear stress, and wall deformation are assessed. We find that uncertainty in inlet pressures and intramyocardial pressures significantly affect all resulting QoIs, while uncertainty in elastic modulus only affects the mechanical response of the vascular wall. Variability in the morphometry exponent used to distribute the total downstream vascular resistance to the single outlets, has little effect on coronary hemodynamics or wall mechanics. Finally, we compare convergence behaviors of statistics of QoIs using several uncertainty propagation methods on three model benchmark problems and the left coronary simulations. From the simulation results, we conclude that the multi-wavelet stochastic expansion shows superior accuracy and performance against Quasi Monte Carlo and stochastic collocation methods.
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Affiliation(s)
- Jongmin Seo
- Department of Pediatrics (Cardiology), Bioengineering and ICME, Stanford University, Stanford, California
| | - Daniele E. Schiavazzi
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Indiana
| | - Andrew M. Kahn
- Department of Medicine, University of California San Diego, La Jolla, California
| | - Alison L. Marsden
- Department of Pediatrics (Cardiology), Bioengineering and ICME, Stanford University, Stanford, California
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19
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Fleeter CM, Geraci G, Schiavazzi DE, Kahn AM, Marsden AL. Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2020; 365:113030. [PMID: 32336811 PMCID: PMC7182133 DOI: 10.1016/j.cma.2020.113030] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. We propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reductions than diseased models. In all cases, our workflow coupling Dakota's MLMF estimators with the SimVascular cardiovascular modeling framework makes uncertainty quantification feasible for constrained computational budgets.
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Affiliation(s)
- Casey M. Fleeter
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
| | - Gianluca Geraci
- Center for Computing Research, Sandia National Laboratories, Albuquerque, NM, USA
| | - Daniele E. Schiavazzi
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA
| | - Andrew M. Kahn
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Alison L. Marsden
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Departments of Pediatrics and Bioengineering, Stanford University, Stanford, CA, USA
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20
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Donadoni F, Bonfanti M, Pichardo-Almarza C, Homer-Vanniasinkam S, Dardik A, Díaz-Zuccarini V. An in silico study of the influence of vessel wall deformation on neointimal hyperplasia progression in peripheral bypass grafts. Med Eng Phys 2019; 74:137-145. [PMID: 31540730 DOI: 10.1016/j.medengphy.2019.09.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 08/08/2019] [Accepted: 09/08/2019] [Indexed: 10/26/2022]
Abstract
Neointimal hyperplasia (NIH) is a major obstacle to graft patency in the peripheral arteries. A complex interaction of biomechanical factors contribute to NIH development and progression, and although haemodynamic markers such as wall shear stress have been linked to the disease, these have so far been insufficient to fully capture its behaviour. Using a computational model linking computational fluid dynamics (CFD) simulations of blood flow with a biochemical model representing NIH growth mechanisms, we analyse the effect of compliance mismatch, due to the presence of surgical stitches and/or to the change in distensibility between artery and vein graft, on the haemodynamics in the lumen and, subsequently, on NIH progression. The model enabled to simulate NIH at proximal and distal anastomoses of three patient-specific end-to-side saphenous vein grafts under two compliance-mismatch configurations, and a rigid wall case for comparison, obtaining values of stenosis similar to those observed in the computed tomography (CT) scans. The maximum difference in time-averaged wall shear stress between the rigid and compliant models was 3.4 Pa, and differences in estimation of NIH progression were only observed in one patient. The impact of compliance on the haemodynamic-driven development of NIH was small in the patient-specific cases considered.
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Affiliation(s)
- Francesca Donadoni
- Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
| | - Mirko Bonfanti
- Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), Department of Medical Physics and Biomedical Engineering, University College London, W1W 7TS, UK
| | - Cesar Pichardo-Almarza
- Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK
| | - Shervanthi Homer-Vanniasinkam
- Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK; Leeds Teaching Hospitals NHS Trust, LS1 3EX, UK; Division of Surgery, University of Warwick, Warwick, UK
| | - Alan Dardik
- The Department of Surgery, Yale University School of Medicine, New Haven, CT, USA; Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Vanessa Díaz-Zuccarini
- Department of Mechanical Engineering, University College London, Torrington Place, London WC1E 7JE, UK; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), Department of Medical Physics and Biomedical Engineering, University College London, W1W 7TS, UK.
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21
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Seo J, Schiavazzi DE, Marsden AL. Performance of preconditioned iterative linear solvers for cardiovascular simulations in rigid and deformable vessels. COMPUTATIONAL MECHANICS 2019; 64:717-739. [PMID: 31827310 PMCID: PMC6905469 DOI: 10.1007/s00466-019-01678-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 01/21/2019] [Indexed: 05/31/2023]
Abstract
Computing the solution of linear systems of equations is invariably the most time consuming task in the numerical solutions of PDEs in many fields of computational science. In this study, we focus on the numerical simulation of cardiovascular hemodynamics with rigid and deformable walls, discretized in space and time through the variational multiscale finite element method. We focus on three approaches: the problem agnostic generalized minimum residual (GMRES) and stabilized bi-conjugate gradient (BICGS) methods, and a recently proposed, problem specific, bi-partitioned (BIPN) method. We also perform a comparative analysis of several preconditioners, including diagonal, block-diagonal, incomplete factorization, multigrid, and resistance based methods. Solver performance and matrix characteristics (diagonal dominance, symmetry, sparsity, bandwidth and spectral properties) are first examined for an idealized cylindrical geometry with physiologic boundary conditions and then successively tested on several patient-specific anatomies representative of realistic cardiovascular simulation problems. Incomplete factorization preconditioners provide the best performance and results in terms of both strong and weak scalability. The BIPN method was found to outperform other methods in patient-specific models with rigid walls. In models with deformable walls, BIPN was outperformed by BICG with diagonal and Incomplete LU preconditioners.
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Affiliation(s)
- Jongmin Seo
- Department of Pediatrics and Institute for Computational and Mathematical Engineering(ICME), Stanford University, Stanford, CA, USA,
| | - Daniele E Schiavazzi
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, IN, USA,
| | - Alison L Marsden
- Department of Pediatrics, Bioengineering and ICME, Stanford University, Stanford, CA, USA,
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22
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Lan H, Updegrove A, Wilson NM, Maher GD, Shadden SC, Marsden AL. A Re-Engineered Software Interface and Workflow for the Open-Source SimVascular Cardiovascular Modeling Package. J Biomech Eng 2019; 140:2666622. [PMID: 29238826 DOI: 10.1115/1.4038751] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Indexed: 11/08/2022]
Abstract
Patient-specific simulation plays an important role in cardiovascular disease research, diagnosis, surgical planning and medical device design, as well as education in cardiovascular biomechanics. simvascular is an open-source software package encompassing an entire cardiovascular modeling and simulation pipeline from image segmentation, three-dimensional (3D) solid modeling, and mesh generation, to patient-specific simulation and analysis. SimVascular is widely used for cardiovascular basic science and clinical research as well as education, following increased adoption by users and development of a GATEWAY web portal to facilitate educational access. Initial efforts of the project focused on replacing commercial packages with open-source alternatives and adding increased functionality for multiscale modeling, fluid-structure interaction (FSI), and solid modeling operations. In this paper, we introduce a major SimVascular (SV) release that includes a new graphical user interface (GUI) designed to improve user experience. Additional improvements include enhanced data/project management, interactive tools to facilitate user interaction, new boundary condition (BC) functionality, plug-in mechanism to increase modularity, a new 3D segmentation tool, and new computer-aided design (CAD)-based solid modeling capabilities. Here, we focus on major changes to the software platform and outline features added in this new release. We also briefly describe our recent experiences using SimVascular in the classroom for bioengineering education.
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Affiliation(s)
- Hongzhi Lan
- Department of Pediatrics, Stanford University, Stanford, CA 94305
| | - Adam Updegrove
- Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA 94720
| | - Nathan M Wilson
- Open Source Medical Software Corporation, Santa Monica, CA 90403
| | | | - Shawn C Shadden
- Department of Mechanical Engineering, University of California, Berkeley, Berkeley, CA 94720
| | - Alison L Marsden
- Department of Pediatrics, Stanford University, , Stanford, CA 94305-5428.,ICME, Stanford University, Stanford, CA 94305.,Department of Bioengineering, Stanford University, Stanford, CA 94305 e-mail:
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23
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Tran JS, Schiavazzi DE, Kahn AM, Marsden AL. Uncertainty quantification of simulated biomechanical stimuli in coronary artery bypass grafts. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2019; 345:402-428. [PMID: 31223175 PMCID: PMC6586227 DOI: 10.1016/j.cma.2018.10.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Coronary artery bypass graft surgery (CABG) is performed on more than 400,000 patients annually in the U.S. However, saphenous vein grafts (SVGs) implanted during CABG exhibit poor patency compared to arterial grafts, with failure rates up to 40% within 10 years after surgery. Differences in mechanical stimuli are known to play a role in driving maladaptation and have been correlated with endothelial damage and thrombus formation. As these quantities are difficult to measure in vivo, multi-scale coronary models offer a way to quantify them, while accounting for complex coronary physiology. However, prior studies have primarily focused on deterministic evaluations, without reporting variability in the model parameters due to uncertainty. This study aims to assess confidence in multi-scale predictions of wall shear stress and wall strain while accounting for uncertainty in peripheral hemodynamics and material properties. Boundary condition distributions are computed by assimilating uncertain clinical data, while spatial variations of vessel wall stiffness are obtained through approximation by a random field. We developed a stochastic submodeling approach to mitigate the computational burden of repeated multi-scale model evaluations to focus exclusively on the bypass grafts. This produces a two-level decomposition of quantities of interest into submodel contributions and full model/submodel discrepancies. We leverage these two levels in the context of forward uncertainty propagation using a previously proposed multi-resolution approach. The time- and space-averaged wall shear stress is well estimated with a coefficient of variation of <35%, but ignorance about the spatial distribution on the wall elastic modulus and thickness lead to large variations in an objective measure of wall strain, with coefficients of variation up to 100%. Sensitivity analysis reveals how the interactions between the flow and material parameters contribute to output variability.
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Affiliation(s)
- Justin S Tran
- Department of Mechanical Engineering, Stanford University, Stanford, CA, USA
| | | | - Andrew M Kahn
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Alison L Marsden
- Department of Pediatrics (Cardiology), Bioengineering and ICME, Stanford University, Stanford, CA, USA
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24
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Grande Gutierrez N, Mathew M, McCrindle BW, Tran JS, Kahn AM, Burns JC, Marsden AL. Hemodynamic variables in aneurysms are associated with thrombotic risk in children with Kawasaki disease. Int J Cardiol 2019; 281:15-21. [PMID: 30728104 DOI: 10.1016/j.ijcard.2019.01.092] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 12/22/2018] [Accepted: 01/25/2019] [Indexed: 12/18/2022]
Abstract
BACKGROUND Thrombosis is a major adverse outcome associated with coronary artery aneurysms (CAAs) resulting from Kawasaki disease (KD). Clinical guidelines recommend initiation of anticoagulation therapy with maximum CAA diameter (Dmax) ≥8 mm or Z-score ≥ 10. Here, we investigate the role of aneurysm hemodynamics as a superior method for thrombotic risk stratification in KD patients. METHODS AND RESULTS We retrospectively studied ten KD patients with CAAs, including five patients who developed thrombosis. We constructed patient-specific anatomic models from cardiac magnetic resonance images and performed computational hemodynamic simulations using SimVascular. Our simulations incorporated pulsatile flow, deformable arterial walls and boundary conditions automatically tuned to match patient-specific arterial pressure and cardiac output. From simulation results, we derived local hemodynamic variables including time-averaged wall shear stress (TAWSS), low wall shear stress exposure, and oscillatory shear index (OSI). Local TAWSS was significantly lower in CAAs that developed thrombosis (1.2 ± 0.94 vs. 7.28 ± 9.77 dynes/cm2, p = 0.006) and the fraction of CAA surface area exposed to low wall shear stress was larger (0.69 ± 0.17 vs. 0.25 ± 0.26%, p = 0.005). Similarly, longer residence times were obtained in branches where thrombosis was confirmed (9.07 ± 6.26 vs. 2.05 ± 2.91 cycles, p = 0.004). No significant differences were found for OSI or anatomical measurements such us Dmax and Z-score. Assessment of thrombotic risk according to hemodynamic variables had higher sensitivity and specificity compared to standard clinical metrics (Dmax, Z-score). CONCLUSIONS Hemodynamic variables can be obtained non-invasively via simulation and may provide improved thrombotic risk stratification compared to current diameter-based metrics, facilitating long-term clinical management of KD patients with persistent CAAs.
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Affiliation(s)
| | - Mathew Mathew
- The Hospital for Sick Children, University of Toronto, Canada
| | | | - Justin S Tran
- Department of Mechanical Engineering, Stanford University, USA
| | - Andrew M Kahn
- Department of Medicine, University of California San Diego School of Medicine, USA
| | - Jane C Burns
- Department of Pediatrics, University of California San Diego School of Medicine, USA
| | - Alison L Marsden
- Departments of Pediatrics, Bioengineering and Institute for Computational and Mathematical Engineering, Stanford University, USA.
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25
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Liu J, Marsden AL. A unified continuum and variational multiscale formulation for fluids, solids, and fluid-structure interaction. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2018; 337:549-597. [PMID: 30505038 PMCID: PMC6261472 DOI: 10.1016/j.cma.2018.03.045] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
We develop a unified continuum modeling framework using the Gibbs free energy as the thermodynamic potential. This framework naturally leads to a pressure primitive variable formulation for the continuum body, which is well-behaved in both compressible and incompressible regimes. Our derivation also provides a rational justification of the isochoric-volumetric additive split of free energies in nonlinear elasticity. The variational multiscale analysis is performed for the continuum model to construct a foundation for numerical discretization. We first consider the continuum body instantiated as a hyperelastic material and develop a variational multiscale formulation for the hyper-elastodynamic problem. The generalized-α method is applied for temporal discretization. A segregated algorithm for the nonlinear solver, based on the original idea introduced in [107], is carefully analyzed. Second, we apply the new formulation to construct a novel unified formulation for fluid-solid coupled problems. The variational multiscale formulation is utilized for spatial discretization in both fluid and solid subdomains. The generalized-α method is applied for the whole continuum body, and optimal high-frequency dissipation is achieved in both fluid and solid subproblems. A new predictor multi-corrector algorithm is developed based on the segregated algorithm. The efficacy of the new formulations is examined in several benchmark problems. The results indicate that the proposed modeling and numerical methodologies constitute a promising technology for biomedical and engineering applications, particularly those necessitating incompressible models.
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Affiliation(s)
- Ju Liu
- Department of Pediatrics (Cardiology), Bioengineering, and Institute for Computational and Mathematical Engineering, Stanford University, Clark Center E1.3, 318 Campus Drive, Stanford, CA 94305, USA
| | - Alison L Marsden
- Department of Pediatrics (Cardiology), Bioengineering, and Institute for Computational and Mathematical Engineering, Stanford University, Clark Center E1.3, 318 Campus Drive, Stanford, CA 94305, USA
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26
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Ramachandra AB, Humphrey JD, Marsden AL. Gradual loading ameliorates maladaptation in computational simulations of vein graft growth and remodelling. J R Soc Interface 2018; 14:rsif.2016.0995. [PMID: 28566510 DOI: 10.1098/rsif.2016.0995] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2016] [Accepted: 04/28/2017] [Indexed: 12/21/2022] Open
Abstract
Vein graft failure is a prevalent problem in vascular surgeries, including bypass grafting and arteriovenous fistula procedures in which veins are subjected to severe changes in pressure and flow. Animal and clinical studies provide significant insight, but understanding the complex underlying coupled mechanisms can be advanced using computational models. Towards this end, we propose a new model of venous growth and remodelling (G&R) based on a constrained mixture theory. First, we identify constitutive relations and parameters that enable venous adaptations to moderate perturbations in haemodynamics. We then fix these relations and parameters, and subject the vein to a range of combined loads (pressure and flow), from moderate to severe, and identify plausible mechanisms of adaptation versus maladaptation. We also explore the beneficial effects of gradual increases in load on adaptation. A gradual change in flow over 3 days plus an initial step change in pressure results in fewer maladaptations compared with step changes in both flow and pressure, or even a gradual change in pressure and flow over 3 days. A gradual change in flow and pressure over 8 days also enabled a successful venous adaptation for loads as severe as the arterial loads. Optimization is used to accelerate parameter estimation and the proposed framework is general enough to provide a good starting point for parameter estimations in G&R simulations.
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Affiliation(s)
- Abhay B Ramachandra
- Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA, USA.,Department of Pediatrics, Institute for Computational and Mathematical Engineering, Stanford, CA, USA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Alison L Marsden
- Department of Pediatrics, Institute for Computational and Mathematical Engineering, Stanford, CA, USA .,Department of Bioengineering, Stanford University, Stanford, CA, USA
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27
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Grande Gutierrez N, Kahn A, Burns JC, Marsden AL. Computational blood flow simulations in Kawasaki disease patients: Insight into coronary artery aneurysm hemodynamics. Glob Cardiol Sci Pract 2017; 2017:e201729. [PMID: 29564350 PMCID: PMC5856960 DOI: 10.21542/gcsp.2017.29] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Affiliation(s)
- Noelia Grande Gutierrez
- Cardiovascular Biomechanics Computation Lab, Stanford University, Stanford CA 94305-5428, USA
| | - Andrew Kahn
- Cardiovascular Biomechanics Computation Lab, Stanford University, Stanford CA 94305-5428, USA
| | - Jane C Burns
- Cardiovascular Biomechanics Computation Lab, Stanford University, Stanford CA 94305-5428, USA
| | - Alison L Marsden
- Cardiovascular Biomechanics Computation Lab, Stanford University, Stanford CA 94305-5428, USA
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28
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Guerciotti B, Vergara C, Ippolito S, Quarteroni A, Antona C, Scrofani R. A computational fluid–structure interaction analysis of coronary Y-grafts. Med Eng Phys 2017; 47:117-127. [DOI: 10.1016/j.medengphy.2017.05.008] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Revised: 04/12/2017] [Accepted: 05/16/2017] [Indexed: 10/19/2022]
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29
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Quanyu W, Xiaojie L, Lingjiao P, Weige T, Chunqi Q. SIMULATION ANALYSIS OF BLOOD FLOW IN ARTERIES OF THE HUMAN ARM. BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS 2017; 29. [PMID: 29290664 DOI: 10.4015/s1016237217500314] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Arteries in the upper limb play important roles in the circulation system of the human body. In particular, the radial artery has received considerable attention in traditional Chinese medicine for thousands of years. Here, a 3D model for the arm arteries has been created uncomplicated, in a Chinese adult's left hand, from the magnetic resonance imaging data, using professional modeling software to restore the basic structure of the arm artery in human body, before being imported to Ansys software for simulation. Blood model has been only simulated, and using the blood density of constant parameter and viscosity using the Carreau fluid model, and using viscous-laminar model of Fluent to obtain the velocity profile, static pressure and shear stress in the brachial, interosseous, ulnar, radial and palmar arch arteries. In particular, the brachial and bifurcations have the high pressure and velocity profiles. The simulation results obtained here are also validated by those published in the literature and proved the ulnar artery prevails over the radial artery as a blood supplier to the vessels in the wrist and hand.
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Affiliation(s)
- Wu Quanyu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, P. R. China
| | - Liu Xiaojie
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, P. R. China
| | - Pan Lingjiao
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, P. R. China
| | - Tao Weige
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, P. R. China
| | - Qian Chunqi
- Department of Radiology, Michigan State University, East Lansing, MI 48864, USA
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30
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Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts. Biomech Model Mechanobiol 2017; 16:1373-1399. [DOI: 10.1007/s10237-017-0893-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 02/27/2017] [Indexed: 11/26/2022]
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31
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Updegrove A, Wilson NM, Merkow J, Lan H, Marsden AL, Shadden SC. SimVascular: An Open Source Pipeline for Cardiovascular Simulation. Ann Biomed Eng 2016; 45:525-541. [PMID: 27933407 DOI: 10.1007/s10439-016-1762-8] [Citation(s) in RCA: 258] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Accepted: 11/10/2016] [Indexed: 12/19/2022]
Abstract
Patient-specific cardiovascular simulation has become a paradigm in cardiovascular research and is emerging as a powerful tool in basic, translational and clinical research. In this paper we discuss the recent development of a fully open-source SimVascular software package, which provides a complete pipeline from medical image data segmentation to patient-specific blood flow simulation and analysis. This package serves as a research tool for cardiovascular modeling and simulation, and has contributed to numerous advances in personalized medicine, surgical planning and medical device design. The SimVascular software has recently been refactored and expanded to enhance functionality, usability, efficiency and accuracy of image-based patient-specific modeling tools. Moreover, SimVascular previously required several licensed components that hindered new user adoption and code management and our recent developments have replaced these commercial components to create a fully open source pipeline. These developments foster advances in cardiovascular modeling research, increased collaboration, standardization of methods, and a growing developer community.
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Affiliation(s)
- Adam Updegrove
- Department of Mechanical Engineering, University of California, Berkeley, CA, USA
| | - Nathan M Wilson
- Open Source Medical Software Corporation, Santa Monica, CA, USA
| | - Jameson Merkow
- Department of Electrical and Computer Engineering, University of California, San Diego, CA, USA
| | - Hongzhi Lan
- Department of Bioengineering, Stanford University, Palo Alto, CA, USA
| | - Alison L Marsden
- Department of Bioengineering, Stanford University, Palo Alto, CA, USA.,Department of Pediatrics, Stanford University, Palo Alto, CA, USA
| | - Shawn C Shadden
- Department of Mechanical Engineering, University of California, Berkeley, CA, USA. .,University of California, Berkeley, CA, 94720-1740, USA.
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