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Zingaro A, Ahmad Z, Kholmovski E, Sakata K, Dede' L, Morris AK, Quarteroni A, Trayanova NA. A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data. Sci Rep 2024; 14:9515. [PMID: 38664464 PMCID: PMC11045804 DOI: 10.1038/s41598-024-59997-2] [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: 01/26/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like theCHA 2 DS 2 -VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.
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Affiliation(s)
- Alberto Zingaro
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA.
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.
- ELEM Biotech S.L., Pier07, Via Laietana, 26, 08003, Barcelona, Spain.
| | - Zan Ahmad
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA
- Department of Applied Mathematics and Statistics, Johns Hopkins University, 100 Wyman Park Dr, Baltimore, MD, 21211, USA
| | - Eugene Kholmovski
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA
- Department of Radiology, University of Utah, 30 N Mario Capecchi Dr., Salt Lake City, UT, 84112, USA
| | - Kensuke Sakata
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA
| | - Luca Dede'
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
| | - Alan K Morris
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr., Salt Lake City, UT, 84112, USA
| | - Alfio Quarteroni
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Station 8, Av. Piccard, 1015, Lausanne, Switzerland
| | - Natalia A Trayanova
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., Baltimore, MD, 21218, USA
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Zingaro A, Ahmad Z, Kholmovski E, Sakata K, Dede’ L, Morris AK, Quarteroni A, Trayanova NA. A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575156. [PMID: 38293150 PMCID: PMC10827064 DOI: 10.1101/2024.01.11.575156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA2DS2-VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.
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Affiliation(s)
- Alberto Zingaro
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
- ELEM Biotech S.L., Pier07, Via Laietana, 26, 08003, Barcelona, Spain
| | - Zan Ahmad
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA
- Department of Applied Mathematics and Statistics, Johns Hopkins University, 100 Wyman Park Dr, 21211, Baltimore, MD, USA
| | - Eugene Kholmovski
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA
- Department of Radiology, University of Utah, 30 N Mario Capecchi Dr., 84112, Salt Lake City, UT, USA
| | - Kensuke Sakata
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA
| | - Luca Dede’
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
| | - Alan K. Morris
- Scientific Computing and Imaging Institute, University of Utah, 72 Central Campus Dr., 84112, Salt Lake City, UT, USA
| | - Alfio Quarteroni
- MOX, Laboratory of Modeling and Scientific Computing, Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy
- Institute of Mathematics, École Polytechnique Fédérale de Lausanne, Station 8, Av. Piccard, CH-1015 Lausanne, Switzerland (Professor Emeritus)
| | - Natalia A. Trayanova
- ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA
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Zhang Z, Zhu J, Wu M, Neidlin M, Wu WT, Wu P. Computational modeling of hemodynamics and risk of thrombosis in the left atrial appendage using patient-specific blood viscosity and boundary conditions at the mitral valve. Biomech Model Mechanobiol 2023; 22:1447-1457. [PMID: 37389735 DOI: 10.1007/s10237-023-01731-4] [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: 12/06/2022] [Accepted: 05/23/2023] [Indexed: 07/01/2023]
Abstract
Hemodynamics play a vital role for the risk of thrombosis in the left atrial appendage (LAA) and left atrium (LA) for patients with atrial fibrillation. Accurate prediction of hemodynamics in the LA can provide important guidance for assessing the risk of thrombosis in the LAA. Patient specificity is a crucial factor in representing the true hemodynamic fields. In this study, we investigated the effects of blood rheology (as a function of hematocrit and shear rate), as well as patient-specific mitral valve (MV) boundary conditions (MV area and velocity profiles measured by ultrasound) on the hemodynamics and thrombosis potential of the LAA. Four scenarios were setup with different degrees of patient specificity. Though using a constant blood viscosity can classify the thrombus and non-thrombus patients for all the hemodynamic indicators, the risk of thrombosis was underestimated for all patients compared with patient-specific viscosities. The results with least patient specificities showed that patients prone to thrombosis predicted by three hemodynamic indicators were inconsistent with clinical observations. Moreover, though patients had the same MV inlet flow rate, different MV models lead to different trends in the risk of thrombosis in different patients. We also found that endothelial cell activation potential and relative residence time can effectively distinguish thrombus and non-thrombus patients for all the scenarios, relatively insensitive to patient specificities. Overall, the findings of this study provide useful insights on patients-specific hemodynamic simulations of the LA.
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Affiliation(s)
- Zijian Zhang
- Artificial Organ Technology Laboratory, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China
| | - Jiade Zhu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Min Wu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
| | - Michael Neidlin
- Department of Cardiovascular Engineering, Medical Faculty, Institute of Applied Medical Engineering, RWTH Aachen University, Aachen, Germany
| | - Wei-Tao Wu
- School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China
| | - Peng Wu
- Artificial Organ Technology Laboratory, School of Mechanical and Electrical Engineering, Soochow University, Suzhou, China.
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Fang R, Li Y, Wang J, Wang Z, Allen J, Ching CK, Zhong L, Li Z. Stroke risk evaluation for patients with atrial fibrillation: Insights from left atrial appendage. Front Cardiovasc Med 2022; 9:968630. [PMID: 36072865 PMCID: PMC9441763 DOI: 10.3389/fcvm.2022.968630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 07/27/2022] [Indexed: 11/13/2022] Open
Abstract
Left atrial appendage (LAA) is believed to be a common site of thrombus formation in patients with atrial fibrillation (AF). However, the commonly-applied stroke risk stratification model (such as. CHA2DS2-VASc score) does not include any structural or hemodynamic features of LAA. Recent studies have suggested that it is important to incorporate LAA geometrical and hemodynamic features to evaluate the risk of thrombus formation in LAA, which may better delineate the AF patients for anticoagulant administration and prevent strokes. This review focuses on the LAA-related factors that may be associated with thrombus formation and cardioembolic events.
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Affiliation(s)
- Runxin Fang
- School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
| | - Yang Li
- Zhongda Hospital, The Affiliated Hospital of Southeast University, Nanjing, China
| | - Jun Wang
- First Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - Zidun Wang
- First Affiliated Hospital, Nanjing Medical University, Nanjing, China
| | - John Allen
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Chi Keong Ching
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
- National Heart Centre Singapore, Singapore, Singapore
| | - Liang Zhong
- Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
- National Heart Centre Singapore, Singapore, Singapore
| | - Zhiyong Li
- School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, Australia
- *Correspondence: Zhiyong Li
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