1
|
Fandaros M, Kwok C, Wolf Z, Labropoulos N, Yin W. Patient-Specific Numerical Simulations of Coronary Artery Hemodynamics and Biomechanics: A Pathway to Clinical Use. Cardiovasc Eng Technol 2024:10.1007/s13239-024-00731-4. [PMID: 38710896 DOI: 10.1007/s13239-024-00731-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 04/29/2024] [Indexed: 05/08/2024]
Abstract
PURPOSE Numerical models that simulate the behaviors of the coronary arteries have been greatly improved by the addition of fluid-structure interaction (FSI) methods. Although computationally demanding, FSI models account for the movement of the arterial wall and more adequately describe the biomechanical conditions at and within the arterial wall. This offers greater physiological relevance over Computational Fluid Dynamics (CFD) models, which assume the walls do not move or deform. Numerical simulations of patient-specific cases have been greatly bolstered by the use of imaging modalities such as Computed Tomography Angiography (CTA), Magnetic Resonance Imaging (MRI), Optical Coherence Tomography (OCT), and Intravascular Ultrasound (IVUS) to reconstruct accurate 2D and 3D representations of artery geometries. The goal of this study was to conduct a comprehensive review on CFD and FSI models on coronary arteries, and evaluate their translational potential. METHODS This paper reviewed recent work on patient-specific numerical simulations of coronary arteries that describe the biomechanical conditions associated with atherosclerosis using CFD and FSI models. Imaging modality for geometry collection and clinical applications were also discussed. RESULTS Numerical models using CFD and FSI approaches are commonly used to study biomechanics within the vasculature. At high temporal and spatial resolution (compared to most cardiac imaging modalities), these numerical models can generate large amount of biomechanics data. CONCLUSIONS Physiologically relevant FSI models can more accurately describe atherosclerosis pathogenesis, and help to translate biomechanical assessment to clinical evaluation.
Collapse
Affiliation(s)
- Marina Fandaros
- Department of Biomedical Engineering, Stony Brook University, Bioengineering Building, Room 109, 11794, Stony Brook, NY, USA
| | - Chloe Kwok
- Department of Biomedical Engineering, Stony Brook University, Bioengineering Building, Room 109, 11794, Stony Brook, NY, USA
| | - Zachary Wolf
- Department of Biomedical Engineering, Stony Brook University, Bioengineering Building, Room 109, 11794, Stony Brook, NY, USA
| | - Nicos Labropoulos
- Department of Surgery, Stony Brook Medicine, 11794, Stony Brook, NY, USA
| | - Wei Yin
- Department of Biomedical Engineering, Stony Brook University, Bioengineering Building, Room 109, 11794, Stony Brook, NY, USA.
| |
Collapse
|
2
|
Sachdeva R, Armstrong AK, Arnaout R, Grosse-Wortmann L, Han BK, Mertens L, Moore RA, Olivieri LJ, Parthiban A, Powell AJ. Novel Techniques in Imaging Congenital Heart Disease: JACC Scientific Statement. J Am Coll Cardiol 2024; 83:63-81. [PMID: 38171712 PMCID: PMC10947556 DOI: 10.1016/j.jacc.2023.10.025] [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: 07/21/2023] [Revised: 10/05/2023] [Accepted: 10/13/2023] [Indexed: 01/05/2024]
Abstract
Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow at well-resourced centers. Studies to evaluate the clinical value and cost-effectiveness of these techniques are needed. For techniques that enhance the value of care for congenital heart disease patients, resources will need to be allocated for education and training to promote widespread implementation.
Collapse
Affiliation(s)
- Ritu Sachdeva
- Department of Pediatrics, Division of Pediatric Cardiology, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, Georgia, USA.
| | - Aimee K Armstrong
- The Heart Center, Nationwide Children's Hospital, Department of Pediatrics, Division of Cardiology, Ohio State University, Columbus, Ohio, USA
| | - Rima Arnaout
- Division of Cardiology, Department of Medicine, University of California-San Francisco, San Francisco, California, USA
| | - Lars Grosse-Wortmann
- Division of Cardiology, Department of Pediatrics, Oregon Health and Science University, Portland, Oregon, USA
| | - B Kelly Han
- Division of Cardiology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Luc Mertens
- Division of Cardiology, Department of Pediatrics, University of Toronto and The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ryan A Moore
- The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Laura J Olivieri
- Division of Cardiology, Department of Pediatrics, Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anitha Parthiban
- Department of Cardiology, Texas Children's Hospital, Baylor College of Medicine, Houston, Texas, USA
| | - Andrew J Powell
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts, USA; Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|