Abstract：
BACKGROUND: Endovascular aortic repair (EVAR) requires extensive preoperative, intraoperative, and postoperative imaging for planning, surveillance, and detection of endo-leaks. There have been manyadvancements in imaging modalities to achieve this purpose. This review discussed different imaging modalities used at different stages of treatment of complex EVAR.
METHODS: We conducted a literature review of all the imaging modalities utilized in EVAR by searching various databases.
RESULTS: Preoperative techniques include analysis of images obtained via modified central line using analysis software and intravascular ultrasound. Fusion imaging (FI), carbon dioxide (CO2) angiography, intravascular ultrasound, and Fiber Optic RealShape (FORS) technology have been crucial in obtaining real-time imaging for the detection of endo-leaks during operative procedures. Conventional imaging modalities like computed tomography (CT) angiography (CTA) and magnetic resonance (MR) angiography are still employed for postoperative surveillance along with computational fluid dynamics and contrast-enhanced ultrasound (CEUS). The advancements in artificial intelligence (AI) have been the breakthrough in developing robust imaging applications.
CONCLUSIONS: This review explains the advantages, disadvantages, and side-effect profile of the abovementioned imaging modalities.
METHODS: We conducted a literature review of all the imaging modalities utilized in EVAR by searching various databases.
RESULTS: Preoperative techniques include analysis of images obtained via modified central line using analysis software and intravascular ultrasound. Fusion imaging (FI), carbon dioxide (CO2) angiography, intravascular ultrasound, and Fiber Optic RealShape (FORS) technology have been crucial in obtaining real-time imaging for the detection of endo-leaks during operative procedures. Conventional imaging modalities like computed tomography (CT) angiography (CTA) and magnetic resonance (MR) angiography are still employed for postoperative surveillance along with computational fluid dynamics and contrast-enhanced ultrasound (CEUS). The advancements in artificial intelligence (AI) have been the breakthrough in developing robust imaging applications.
CONCLUSIONS: This review explains the advantages, disadvantages, and side-effect profile of the abovementioned imaging modalities.
摘要：
目的：主动脉腔内修复术需要广泛的术前，术中,和术后成像计划，监视,和检测内漏。在成像模式中已经有许多进步来实现这个目的。本文讨论了复杂血管内修复术在不同治疗阶段使用的不同成像方式。
方法：我们通过检索各种数据库，对血管内主动脉修复术中使用的所有成像方式进行了文献综述。
结果：术前技术包括使用分析软件和血管内超声分析通过修改的中心线获得的图像。融合成像,CO2血管造影术,血管内超声,和FiberOpticRealShape技术在获得实时成像以检测手术过程中的内漏至关重要。诸如CT血管造影术和MR血管造影术之类的常规成像模态仍用于术后监视以及计算流体动力学和对比增强超声。人工智能的进步已经成为开发强大成像应用的突破。
结论：这篇综述解释了其优势，缺点,和上述成像模式的副作用分布。
方法：我们通过检索各种数据库，对血管内主动脉修复术中使用的所有成像方式进行了文献综述。
结果：术前技术包括使用分析软件和血管内超声分析通过修改的中心线获得的图像。融合成像,CO2血管造影术,血管内超声,和FiberOpticRealShape技术在获得实时成像以检测手术过程中的内漏至关重要。诸如CT血管造影术和MR血管造影术之类的常规成像模态仍用于术后监视以及计算流体动力学和对比增强超声。人工智能的进步已经成为开发强大成像应用的突破。
结论：这篇综述解释了其优势，缺点,和上述成像模式的副作用分布。
