Zhang Xuehuan, Nan Nan, Tong Xinyu, Chen Huyang, Zhang Xuyang, Li Shilong, Zhang Mingduo, Gao Bingyu, Wang Xifu, Song Xiantao, Chen Duanduan
School of Medical Technology, Beijing Institute of Technology, Beijing, China.
Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Quant Imaging Med Surg. 2024 Feb 1;14(2):1477-1492. doi: 10.21037/qims-23-1094. Epub 2024 Jan 15.
It has been suggested that biomechanical factors may influence plaque development. However, key determinants for assessing plaque vulnerability remain speculative.
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.
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.
Functional indices are crucial for plaque status assessment. An evaluation based on biomechanical simulations might provide insights into risk identification and guide therapeutic decisions.
有人提出生物力学因素可能会影响斑块的形成。然而，评估斑块易损性的关键决定因素仍具有推测性。
在本研究中，基于血管内光学相干断层扫描（IV-OCT）和数字减影血管造影（DSA）数据集进行了二维（2D）结构力学分析和三维（3D）流固耦合（FSI）分析。在二维研究中，分析了103个IV-OCT切片。通过调整参数（λ）进行深入的形态力学分析和加权最小绝对收缩和选择算子（LASSO）回归分析，以识别与斑块易损性相关的关键特征。在三维研究中，通过融合IV-OCT和DSA数据重建冠状动脉模型，随后进行FSI分析。研究了易损斑块与壁面剪应力（WSS）之间的关系。
使用最小标准（λ-min）和单标准误差标准（λ-1se）选择影响因素。除了最小纤维帽厚度（FCTmin）这一常见的易损因素外，λ-min选择了四个生物力学因素，包括平均/最大位移和平均/最大应力，λ-1se选择了两个生物力学因素，包括平均/最大位移。此外，易损斑块的位置与高WSS部位一致。
功能指标对于斑块状态评估至关重要。基于生物力学模拟的评估可能有助于风险识别并指导治疗决策。
