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，约有20%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也会导致长期的重大心脏不良事件、靶病变血管重建、再狭窄和支架血栓形成的发生率远远高于非分叉病变。当治疗无保护的左冠状动脉主干分叉病变时，会出现更复杂的情况，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置入术(即主血管支架置入术)后的介入策略，尤其是引导钢丝重新交叉以纠正监侧分支。尽管OCT的平面内分辨率很高(10-20微米)，这是唯一可以显示支架支柱的血管内成像方式，但轴向分辨率很低 (200微米)避免了对所部署的支架的完整可视化以及对周围靶分叉病变的空间关系的了解，以指导最佳的介入治疗策略。为了克服当前技术的显著缺陷，我们建议开发一种算法来显示相对于目标分叉病变的完整的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来开发一种算法，通过融合OCT和微计算机断层扫描(µCT)成像数据，以高分辨率(~5微米)自动重建完整的3D支架几何形状。(目标1)。该算法将在特定患者的冠状动脉分叉病变幻影中得到验证。为了检验该算法在临床环境中的实用性和可行性，我们将使用临床OCT数据上开发的重建技术来评估临时支架术后的几何形状和周围的靶点分叉病变(目标2)。这项拟议研究的成功完成将使仅从血管内OCT成像数据就可以完整和清楚地了解所部署的支架，以指导临床治疗策略。此外，拟议的研究将为未来研究真正针对患者的支架力学模型以开发特定于病变的支架策略奠定基础。

 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.