Abstract：
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.
摘要：
动脉粥样硬化斑块进展和破裂在心血管疾病发展和最终的严重事件如心脏病发作和中风中起重要作用。近年来，医学成像和基于图像的计算建模方法在量化斑块形态和生物力学条件方面取得了长足的进步，并更好地了解了斑块的演变和破裂过程。本文首先简要回顾了基于图像的计算建模中使用的冠状动脉薄帽纤维粥样硬化（TCFA）斑块的临床成像技术。随后总结了冠状动脉斑块的不同类型的生物力学模型。回顾并比较了基于图像的计算模型的斑块进展和脆弱性预测研究。已经取得了很大进展，并且已经实现了合理的高预测精度。然而,关于生物力学和形态学因素对未来斑块行为的影响，现有文献中仍存在一些不一致之处，很难像图像模态一样进行直接比较分析，生物力学因素选择，预测模型，这些研究中存在进展/脆弱性措施。鼓励整个研究社区的数据和模型共享将部分解决这些差异，并可能导致更明确的结论。基于体内图像的计算建模可以用作定量评估冠状动脉斑块易损性的强大工具，以用于潜在的临床应用。
