Computer assisted coronary artery stent interventions

计算机辅助冠状动脉支架介入治疗 摘要 当使用支架治疗高度钙化的冠状动脉病变时，介入心脏科医生在信息有限的情况下做出应激性的治疗决定，这可能导致支架部署不当和预后不良，甚至是罕见的灾难性事件。当出现钙化时，心脏病专家必须选择使用 正常大小的血管成形术球囊；较大的血管成形术球囊，压力越来越高，持续时间长 使钙化破裂；打分或切割气球；多种动脉粥样硬化装置中的任何一种；和/或 支架扩张后球囊压力高达30atm。心脏病专家必须选择支架直径和长度， 考虑到远端动脉大小、血管锥度和钙化程度(弧长和厚度)。一些人 潜在的负面后果是支架可能展开不足和/或支柱错位；气球 可能会破裂；血管可能会解剖；或者动脉粥样硬化装置可能会穿孔。血管内光学相干断层扫描(IVOCT)对支架部署的评估显示，大的偏心性钙化通常导致 在支柱错位和小血管解剖的情况下进行部署。为了应对这些挑战， 具体目标是：1)开发支架前图像中钙化的成像/量化方法。2)执行EX 活体实验，以获得详细的生物力学数据，并展示支架部署的关键问题。 3)开发有效的、特定于病变的有限元模型。4)用于硅学实验和物理测量，以阐明支架部署中的问题并建立治疗指南。随着成功，该项目 将导致来自IVOCT或其他成像方式的用于实时治疗计划的未来决策支持软件。项目团队将在干预、IVOCT定量图像分析和有限元建模方面的专业知识基础上再接再厉。

Computer assisted coronary artery stent interventions Summary When treating highly calcified coronary artery lesions with stents, interventional cardiologists, with limited information, make stressful treatment decisions, which can lead to inadequate stent deployment and poor outcomes, or even rare calamitous events. When calcification is present, a cardiologist must choose to use a normal sized angioplasty balloon; a larger angioplasty balloon with increasingly high, prolonged pressures to fracture the calcification; a scoring or cutting balloon; any one of a number of atherectomy devices; and/or stent post-dilation balloon pressures up to 30 atm. The cardiologist must choose stent diameter and length, taking into account distal artery size, vessel taper, and extent (arc length and thickness) of calcification. Some potential negative consequences are that a stent can under deploy and/or have malapposed struts; a balloon can rupture; a vessel can dissect; or an atherectomy device can perforate the wall. Intravascular optical coherence tomography (IVOCT) evaluations of stent deployment show that large eccentric calcifications often lead to under deployment with malapposition of struts and small vessel dissections. To address these challenges, specific aims are: 1) Develop methods for imaging/quantifying calcifications in pre-stent images. 2) Perform ex vivo experiments to obtain detailed biomechanical data and demonstrate key issues in stent deployment. 3) Develop well-validated, lesion specific FEM models. 4) Use in silico experiments and physical measurements to elucidate issues in stent deployment and establish guidelines for treatment. With success, the project will lead to future decision-support software for live-time treatment planning from IVOCT or other imaging modalities. The project team will build on expertise in interventions, quantitative image analysis of IVOCT, and finite element modeling.