1
|
Zhang X, Nan N, Tong X, Chen H, Zhang X, Li S, Zhang M, Gao B, Wang X, Song X, Chen D. Validation of biomechanical assessment of coronary plaque vulnerability based on intravascular optical coherence tomography and digital subtraction angiography. Quant Imaging Med Surg 2024; 14:1477-1492. [PMID: 38415169 PMCID: PMC10895097 DOI: 10.21037/qims-23-1094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/28/2023] [Indexed: 02/29/2024]
Abstract
Background It has been suggested that biomechanical factors may influence plaque development. However, key determinants for assessing plaque vulnerability remain speculative. Methods In this study, a two-dimensional (2D) structural mechanical analysis and a three-dimensional (3D) fluid-structure interaction (FSI) analysis were conducted based on intravascular optical coherence tomography (IV-OCT) and digital subtraction angiography (DSA) data sets. In the 2D study, 103 IV-OCT slices were analyzed. An in-depth morpho-mechanic analysis and a weighted least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify the crucial features related to plaque vulnerability via the tuning parameter (λ). In the 3D study, the coronary model was reconstructed by fusing the IV-OCT and DSA data, and a FSI analysis was subsequently performed. The relationship between vulnerable plaque and wall shear stress (WSS) was investigated. Results The influential factors were selected using the minimum criteria (λ-min) and one-standard error criteria (λ-1se). In addition to the common vulnerable factor of the minimum fibrous cap thickness (FCTmin), four biomechanical factors were selected by λ-min, including the average/maximal displacements and average/maximal stress, and two biomechanical factors were selected by λ-1se, including the average/maximal displacements. Additionally, the positions of the vulnerable plaques were consistent with the sites of high WSS. Conclusions Functional indices are crucial for plaque status assessment. An evaluation based on biomechanical simulations might provide insights into risk identification and guide therapeutic decisions.
Collapse
Affiliation(s)
- Xuehuan Zhang
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Nan Nan
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing, China
| | - Xinyu Tong
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Huyang Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Xuyang Zhang
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Shilong Li
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Mingduo Zhang
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing, China
| | - Bingyu Gao
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing, China
| | - Xifu Wang
- Department of Emergency, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Xiantao Song
- Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
- Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing, China
| | - Duanduan Chen
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| |
Collapse
|
2
|
Straughan R, Kadry K, Parikh SA, Edelman ER, Nezami FR. Fully automated construction of three-dimensional finite element simulations from Optical Coherence Tomography. Comput Biol Med 2023; 165:107341. [PMID: 37611423 PMCID: PMC10528179 DOI: 10.1016/j.compbiomed.2023.107341] [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: 05/01/2023] [Revised: 07/18/2023] [Accepted: 08/07/2023] [Indexed: 08/25/2023]
Abstract
Despite recent advances in diagnosis and treatment, atherosclerotic coronary artery diseases remain a leading cause of death worldwide. Various imaging modalities and metrics can detect lesions and predict patients at risk; however, identifying unstable lesions is still difficult. Current techniques cannot fully capture the complex morphology-modulated mechanical responses that affect plaque stability, leading to catastrophic failure and mute the benefit of device and drug interventions. Finite Element (FE) simulations utilizing intravascular imaging OCT (Optical Coherence Tomography) are effective in defining physiological stress distributions. However, creating 3D FE simulations of coronary arteries from OCT images is challenging to fully automate given OCT frame sparsity, limited material contrast, and restricted penetration depth. To address such limitations, we developed an algorithmic approach to automatically produce 3D FE-ready digital twins from labeled OCT images. The 3D models are anatomically faithful and recapitulate mechanically relevant tissue lesion components, automatically producing morphologies structurally similar to manually constructed models whilst including more minute details. A mesh convergence study highlighted the ability to reach stress and strain convergence with average errors of just 5.9% and 1.6% respectively in comparison to FE models with approximately twice the number of elements in areas of refinement. Such an automated procedure will enable analysis of large clinical cohorts at a previously unattainable scale and opens the possibility for in-silico methods for patient specific diagnoses and treatment planning for coronary artery disease.
Collapse
Affiliation(s)
- Ross Straughan
- Cardiac Surgery Division, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA; Department of Mechanical and Process Engineering, ETH Zurich, Leonhardstrasse 21, 8092 Zurich, Switzerland.
| | - Karim Kadry
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, USA.
| | - Sahil A Parikh
- Division of Cardiology, Columbia University Irving Medical Center, New York, 10032, NY, USA.
| | - Elazer R Edelman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, MA, USA; Cardiovascular Division, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA.
| | - Farhad R Nezami
- Cardiac Surgery Division, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA.
| |
Collapse
|