Technical implications of a novel deep learning system in the segmentation and evaluation of computed tomography angiography before transcatheter aortic valve replacement.

IF 2.6 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS
Min Jin, Yu Mao, Jian Yang, Jian Liu, Guozhong Chen, Timothée Noterdaeme, Rüdiger Lange, Chenming Ma, Yingqiang Guo, Haibo Zhang
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引用次数: 0

Abstract

Objective: The goal of this study was to compare the computed tomography angiography scans of the segmentation results from the Cvpilot, 3mensio, and Volume Viewer systems to explore the practicability of the Cvpilot system in the automatic segmentation and technical evaluation of the aortic root before transcatheter aortic valve replacement (TAVR).

Design: A total of 154 patients who underwent TAVR at our center from January 2022 to May 2023 were enrolled, and their computed tomography angiography images were analyzed using the Cvpilot, 3mensio, and Volume Viewer systems, respectively.

Setting: Not applicable.

Participants: Not applicable.

Main outcome measures: The reconstructed computed tomography angiography images were evaluated by experts, and the measurements of the aortic roots were analyzed statistically.

Results: Compared with the 3mensio system, 92.2% of patients (n = 142) evaluated with the Cvpilot system reached grade A, 5.2% of patients (n = 8) reached grade B, and 2.6% of patients (n = 4) reached grade C. Compared with the Volume Viewer system, 90.9% of patients (n = 140) evaluated with the Cvpilot system achieved grade A, 7.1% of patients (n = 11) achieved grade B, and 2.0% of patients (n = 3) achieved grade C. Furthermore, there was no significant difference among the measurement results of the Cvpilot, 3mensio, and Volume Viewer systems (all p > 0.05).

Conclusion: Overall, the Cvpilot system is effective and reliable. It can accurately complete the segmentation and the measurement of aortic root structures, thereby effectively improving the measurement quality before TAVR.

Trial registration: Not applicable.

一种新型深度学习系统在经导管主动脉瓣置换术前计算机断层血管造影分割和评估中的技术意义。
目的:本研究的目的是比较Cvpilot、3mensio和Volume Viewer系统的ct血管造影分割结果,探讨Cvpilot系统在经导管主动脉瓣置换术(TAVR)前主动脉根部自动分割和技术评估中的实用性。设计:共有154例于2022年1月至2023年5月在我们中心接受TAVR的患者入组,分别使用Cvpilot、3mensio和Volume Viewer系统对其计算机断层血管造影图像进行分析。设置:不适用。参与者:不适用。主要观察指标:专家对重建的ct血管造影图像进行评价,并对主动脉根部测量结果进行统计分析。结果:与3mensio系统相比,Cvpilot系统评估的92.2%的患者(n = 142)达到A级,5.2%的患者(n = 8)达到B级,2.6%的患者(n = 4)达到c级。与Volume Viewer系统相比,Cvpilot系统评估的90.9%的患者(n = 140)达到A级,7.1%的患者(n = 11)达到B级,2.0%的患者(n = 3)达到c级。Cvpilot、3mensio和Volume Viewer系统的测量结果无显著差异(均p < 0.05)。结论:总体而言,Cvpilot系统是有效可靠的。能够准确完成主动脉根部结构的分割和测量,有效提高TAVR前的测量质量。试验注册:不适用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Therapeutic Advances in Cardiovascular Disease
Therapeutic Advances in Cardiovascular Disease CARDIAC & CARDIOVASCULAR SYSTEMS-
CiteScore
3.50
自引率
0.00%
发文量
11
审稿时长
9 weeks
期刊介绍: The journal is aimed at clinicians and researchers from the cardiovascular disease field and will be a forum for all views and reviews relating to this discipline.Topics covered will include: ·arteriosclerosis ·cardiomyopathies ·coronary artery disease ·diabetes ·heart failure ·hypertension ·metabolic syndrome ·obesity ·peripheral arterial disease ·stroke ·arrhythmias ·genetics
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