intravascular-ultrasound-image-based-finite-element-modeling-approach

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Quantifying the mechanical properties of coronary arterial walls could provide meaningful information for the diagnosis, management, and treatment of ...

Shandong Second Provincial General Hospital

Southeast University

Atherosclerotic plaque progression and rupture play an important role in cardiovascular disease development and the final drastic events such as heart attack and stroke. Medical imaging and image-based computational modeling methods advanced considerably in recent years to quantify plaque morphology and biomechanical conditions and gain a better understanding of plaque evolution and rupture process. This article first briefly reviewed clinical imaging techniques for coronary thin-cap fibroatheroma (TCFA) plaques used in image-based computational modeling. This was followed by a summary of different types of biomechanical models for coronary plaques. Plaque progression and vulnerability prediction studies based on image-based computational modeling were reviewed and compared. Much progress has been made and a reasonable high prediction accuracy has been achieved. However, there are still some inconsistencies in existing literature on the impact of biomechanical and morphological factors on future plaque behavior, and it is very difficult to perform direct comparison analysis as differences like image modality, biomechanical factors selection, predictive models, and progression/vulnerability measures exist among these studies. Encouraging data and model sharing across the research community would partially resolve these differences, and possibly lead to clearer assertive conclusions. In vivo image-based computational modeling could be used as a powerful tool for quantitative assessment of coronary plaque vulnerability for potential clinical applications.

Image-based biomechanical modeling for coronary atherosclerotic plaque progression and vulnerability prediction.

While it has been hypothesized that high plaque stress and strain may be related to plaque rupture, its direct verification using in vivo coronary plaque rupture data and full 3-dimensional fluid-structure interaction models is lacking in the current literature due to difficulty in obtaining in vivo plaque rupture imaging data from patients with acute coronary syndrome. This case-control study aims to use high-resolution optical coherence tomography-verified in vivo plaque rupture data and 3-dimensional fluid-structure interaction models to seek direct evidence for the high plaque stress/strain hypothesis.

Plaque Ruptures Are Related to High Plaque Stress and Strain Conditions: Direct Verification by Using In Vivo OCT Rupture Data and FSI Models.

Mechanical stress and strain conditions play an important role in atherosclerosis plaque progression, remodeling and potential rupture and may be used in plaque vulnerability assessment for better clinical diagnosis and treatment decisions. Single layer plaque models without residual stress have been widely used due to unavailability of multi-layer image segmentation method and residual stress data. However, vessel layered structure and residual stress have large impact on stress/strain calculations and should be included in the models.

Impact of residual stress on coronary plaque stress/strain calculations using optical coherence tomography image-based multi-layer models.

Plaque erosion (PE) with secondary thrombosis is one of the key mechanisms of acute coronary syndrome (ACS) which often leads to drastic cardiovascular events. Identification and prediction of PE are of fundamental significance for disease diagnosis, prevention and treatment. In vivo optical coherence tomography (OCT) data of eight eroded plaques and eight non-eroded plaques were acquired to construct three-dimensional fluid-structure interaction models and obtain plaque biomechanical conditions for investigation. Plaque stenosis severity, plaque burden, plaque wall stress (PWS) and strain (PWSn), flow shear stress (FSS), and ΔFSS (FSS variation in time) were extracted for comparison and prediction. A logistic regression model was used to predict plaque erosion. Our results indicated that the combination of mean PWS and mean ΔFSS gave best prediction (AUC = 0.866, 90% confidence interval (0.717, 1.0)). The best single predictor was max ΔFSS (AUC = 0.819, 90% confidence interval (0.624, 1.0)). The average of maximum FSS values from eroded plaques was 76% higher than that from the non-eroded plaques (127.96 vs. 72.69 dyn/cm) while the average of mean FSS from erosion sites of the eight eroded plaques was 48.6% higher than that from sites without erosion (71.52 vs. 48.11 dyn/cm). The average of mean PWS from plaques with erosion was 22.83% lower than that for plaques without erosion (83.2 kPa vs. 107.8 kPa). This pilot study suggested that combining plaque stress, strain and flow shear stress could help better identify patients with potential plaque erosion, enabling possible early intervention therapy. Further studies are needed to validate our findings.

Comparison and identification of human coronary plaques with/without erosion using patient-specific optical coherence tomography-based fluid-structure interaction models: a pilot study.

Article	Year
Image-based biomechanical modeling for coronary atherosclerotic plaque progression and vulnerability prediction. International journal of cardiology\| PubMed ID: 35149139	2022
Plaque Ruptures Are Related to High Plaque Stress and Strain Conditions: Direct Verification by Using In Vivo OCT Rupture Data and FSI Models. Arteriosclerosis, thrombosis, and vascular biology\| PubMed ID: 38721707	2024
Impact of residual stress on coronary plaque stress/strain calculations using optical coherence tomography image-based multi-layer models. Frontiers in cardiovascular medicine\| PubMed ID: 38725836	2024
Comparison and identification of human coronary plaques with/without erosion using patient-specific optical coherence tomography-based fluid-structure interaction models: a pilot study. Biomechanics and modeling in mechanobiology\| PubMed ID: 39528856	2024

Rui Lv

Biography

JoVE Journal Publications

Other Publications