Evaluation of CT Angiography Image Quality Acquired with Single-Energy Metal Artifact Reduction (SEMAR) Algorithm in Patients After Complex Endovascular Aortic Repair

评估采用单能量金属伪影减少(SEMAR)算法获得的CT血管造影图像质量在复杂血管内主动脉修复术后患者中的应用

阅读:2

Abstract

PURPOSE: To evaluate the value of single-energy metal artifact reduction (SEMAR) algorithm on image quality in patients after complex endovascular aortic repair (EVAR) with fenestrated and branched devices. METHODS: Routine follow-up computed tomography angiography (CTA) examinations were performed between February 2016 and May 2017 in 18 patients who underwent a complex EVAR procedure at our institution. Objective analysis was performed by measuring the standard deviation (SD) of attenuation (Hounsfield Units), and the contrast-to-noise ratio (CNR) in regions of interests in the stented visceral arteries. Subjective analysis of the degree of artifacts and stent visualization was performed independently by two interventional radiologists, blinded to the image reconstruction. RESULTS: The SD of attenuation was significantly lower in all target visceral arteries (p < .001), the celiac artery (p = .002), the superior mesenteric artery (SMA; p = .043), and renal arteries (p < .001) in the CT images with SEMAR reconstruction. The CNR significantly increased in all SEMAR-reconstructed target visceral arteries (overall: p < .001, celiac artery: p = .009; SMA: p = .003; renal arteries: p < .001). The reviewers rated a significantly lower artifact degree in all target vessels (overall: p < .001, celiac artery: p = .001; SMA: p = .008; renal arteries: p < .001) and a significantly improved visualization of the stent patency in all target vessels (overall: p < .001, celiac artery: p = .031; SMA: p = .047; renal arteries: p < .001) in the SEMAR images. Overall preference of both reviewers was in favor of the SEMAR reconstruction in 15/18 cases (83%). CONCLUSION: Reconstruction with SEMAR algorithm significantly improves CTA image quality in patients after complex EVAR. LEVEL OF EVIDENCE: Level 4, Case series.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。