Suppr超能文献

计算机辅助定量非对比 3D 黑血 MRI 作为一种有效替代参考标准的手动 CT 血管造影测量腹主动脉瘤的方法。

Computer-aided quantification of non-contrast 3D black blood MRI as an efficient alternative to reference standard manual CT angiography measurements of abdominal aortic aneurysms.

机构信息

Department of Radiology and Biomedical Imaging, University of California San Francisco, United States.

Department of Radiology, Changhai Hospital, Shanghai, China.

出版信息

Eur J Radiol. 2021 Jan;134:109396. doi: 10.1016/j.ejrad.2020.109396. Epub 2020 Nov 5.

Abstract

BACKGROUND

Non-contrast 3D black blood MRI is a promising tool for abdominal aortic aneurysm (AAA) surveillance, permitting accurate aneurysm diameter measurements needed for patient management.

PURPOSE

To evaluate whether automated AAA volume and diameter measurements obtained from computer-aided segmentation of non-contrast 3D black blood MRI are accurate, and whether they can supplant reference standard manual measurements from contrast-enhanced CT angiography (CTA).

MATERIALS AND METHODS

Thirty AAA patients (mean age, 71.9 ± 7.9 years) were recruited between 2014 and 2017. Participants underwent both non-contrast black blood MRI and CTA within 3 months of each other. Semi-automatic (computer-aided) MRI and CTA segmentations utilizing deformable registration methods were compared against manual segmentations of the same modality using the Dice similarity coefficient (DSC). AAA lumen and total aneurysm volumes and AAA maximum diameter, quantified automatically from these segmentations, were compared against manual measurements using Pearson correlation and Bland-Altman analyses. Finally, automated measurements from non-contrast 3D black blood MRI were evaluated against manual CTA measurements using the Wilcoxon test, Pearson correlation and Bland-Altman analyses.

RESULTS

Semi-automatic segmentations had excellent agreement with manual segmentations (lumen DSC: 0.91 ± 0.03 and 0.94 ± 0.03; total aneurysm DSC: 0.92 ± 0.02 and 0.94 ± 0.03, for black blood MRI and CTA, respectively). Automated volume and maximum diameter measurements also had excellent correlation to their manual counterparts for both black blood MRI (volume: r = 0.99, P < 0.001; diameter: r = 0.97, P < 0.001) and CTA (volume: r = 0.99, P < 0.001; diameter: r = 0.97, P < 0.001). Compared to manual CTA measurements, bias and limits of agreement (LOA) for automated MRI measurements (lumen volume: 1.49, [-4.19 7.17] cm; outer wall volume: -2.46, [-14.05 9.13] cm; maximal diameter: 0.08, [-6.51 6.67] mm) were largely equivalent to those of manual MRI measurements, particularly for maximum AAA diameter (lumen volume: 0.73, [-6.47 7.93] cm; outer wall volume: 0.98, [-10.54 12.5] cm; maximal diameter: 0.08, [-3.67 3.83] mm).

CONCLUSION

Semi-automatic segmentation of non-contrast 3D black blood MRI efficiently provides reproducible morphologic AAA assessment yielding accurate AAA diameters and volumes with no clinically relevant differences compared to either automatic or manual measurements based on CTA.

摘要

背景

非增强 3D 黑血 MRI 是一种很有前途的腹主动脉瘤(AAA)监测工具,可进行准确的动脉瘤直径测量,这是患者管理所必需的。

目的

评估非增强 3D 黑血 MRI 计算机辅助分割得到的自动 AAA 体积和直径测量是否准确,以及它们是否可以替代对比增强 CT 血管造影(CTA)的参考标准手动测量。

材料与方法

2014 年至 2017 年间,共招募了 30 名 AAA 患者(平均年龄 71.9 ± 7.9 岁)。参与者在彼此相距 3 个月内接受了非增强黑血 MRI 和 CTA 检查。利用可变形配准方法的半自动(计算机辅助)MRI 和 CTA 分割与使用 Dice 相似系数(DSC)的同模态手动分割进行比较。从这些分割中自动量化的 AAA 管腔和总动脉瘤体积以及 AAA 最大直径,与手动测量进行 Pearson 相关性和 Bland-Altman 分析比较。最后,使用 Wilcoxon 检验、Pearson 相关性和 Bland-Altman 分析,将非增强 3D 黑血 MRI 的自动测量与手动 CTA 测量进行了比较。

结果

半自动分割与手动分割具有极好的一致性(管腔 DSC:0.91 ± 0.03 和 0.94 ± 0.03;总动脉瘤 DSC:0.92 ± 0.02 和 0.94 ± 0.03,分别用于黑血 MRI 和 CTA)。自动体积和最大直径测量与手动测量也具有极好的相关性,无论是黑血 MRI(体积:r = 0.99,P < 0.001;直径:r = 0.97,P < 0.001)还是 CTA(体积:r = 0.99,P < 0.001;直径:r = 0.97,P < 0.001)。与手动 CTA 测量相比,自动 MRI 测量的偏倚和界限(LOA)(管腔体积:1.49,[-4.19 7.17]cm;外膜体积:-2.46,[-14.05 9.13]cm;最大直径:0.08,[-6.51 6.67]mm)在很大程度上与手动 MRI 测量相当,特别是对于最大 AAA 直径(管腔体积:0.73,[-6.47 7.93]cm;外膜体积:0.98,[-10.54 12.5]cm;最大直径:0.08,[-3.67 3.83]mm)。

结论

非增强 3D 黑血 MRI 的半自动分割可有效地提供可重复的 AAA 形态评估,与基于 CTA 的自动或手动测量相比,可准确测量 AAA 直径和体积,且无临床相关差异。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验