3D Stent Reconstruction in Bifurcating Lesions By Fusion of OCT and Micro-CT Data

 描述（由申请人提供）：在每年进行的125万例经皮冠状动脉介入治疗（PCI）中，约20%的患者会遇到冠状动脉分叉病变。即使在药物洗脱支架时代，这些病变的复杂性及其治疗中的技术挑战导致长期主要不良心脏事件、靶病变血运重建、再狭窄和支架血栓形成率远远高于非分叉病变。当治疗未受保护的左主干冠状动脉分叉病变时，会出现进一步的复杂性，因为并发症可能是灾难性的。光学相干断层扫描（OCT）通常用于指导临时支架植入术（即，主血管的支架植入），特别是导丝再交叉以校正被束缚的侧分支。尽管OCT（10-20 µm）的平面内分辨率很高，这是唯一允许支架支柱可视化的血管内成像模式，但轴向分辨率较差 (200μm）妨碍了展开支架的完全可视化以及与周围靶分叉病变的空间关系的理解，从而无法指导最佳介入治疗策略。为了克服当前技术的显著缺点，我们建议开发一种算法来可视化相对于目标分叉病变的完整3D支架结构。我们的方法将使用先进的图像处理和形状记忆匹配技术开发一种算法，通过融合OCT和微型计算机断层扫描（µCT）成像数据，以高分辨率（~5 µm）自动重建完整的3D展开支架几何结构。(Aim 1）。该算法将在患者特定的冠状动脉分叉病变体模中得到确认。为了检查该算法在临床环境中的实用性和可行性，我们将使用开发的临床OCT数据重建技术来评估临时支架几何结构和周围目标分叉病变（目标2）。成功完成拟定研究将允许仅从血管内OCT成像数据中完整和清晰地了解展开的支架，以指导临床治疗策略。此外，所提出的研究将为未来研究真正的患者特异性支架力学建模奠定基础，以开发病变特异性支架植入策略。

 DESCRIPTION (provided by applicant): Coronary bifurcation lesions are encountered in approximately 20% of the >1.25 million percutaneous coronary interventions (PCI) performed annually. Even in the drug-eluting stent era, the complexity of these lesions and technical challenges in their treatment result in long term major adverse cardiac event, target lesion revascularization, restenosis, and stent thrombosis rates that are far greater than in non-bifurcating lesions. Further complexities arise when treating unprotected left main coronary artery bifurcating lesions, as complications may be catastrophic. Optical coherence tomography (OCT) is commonly employed to guide interventional strategies following a provisional stenting (i.e., stenting of the main vessel) and, in particular, guide wire recrossing to correct for a jaild side branch. Despite the high in-plane resolution of OCT (10-20 µm), which is the only intravascular imaging modality that allows for visualization of stent struts, poor axial resolution (200 µm) prevents a complete visualization of the deployed stent and understanding of the spatial relationship with surrounding target bifurcation lesion to guide optimal interventional treatment strategies. To overcome the significant shortcoming of current techniques, we propose to develop an algorithm to visualize the complete 3D stent structure with respect to the target bifurcation lesion. Our approach will use advanced image processing and shape memory matching techniques to develop an algorithm to automatically reconstruct, at a high-resolution (~5 µm), the complete 3D deployed stent geometry by fusing OCT and micro- computed tomography (µCT) imaging data. (Aim 1). The algorithm will be validated in patient-specific coronary bifurcating lesion phantoms. To examine the utility and feasibility of the algorithm in the clinical environment, we will employ the developed reconstruction technique on clinical OCT data to assess the post-provisional stent geometry and surrounding target bifurcation lesion (Aim 2). Successful completion of the proposed research will allow for a complete and clear understanding of the deployed stent from only intravascular OCT imaging data to guide clinical treatment strategy. Furthermore, the proposed research will form the foundation for future investigations of truly patient-specific stent mechanical modeling towards development of lesion- specific stenting strategies.