Local aortic aneurysm wall expansion measured with automated image analysis.
Local aortic aneurysm wall expansion measured with automated image analysis.
复制标题
DOI：
10.1016/j.jvssci.2021.11.004
复制
发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Jackson BM
中科院分区：
文献类型：
--
作者：
Stoecker JB;Eddinger KC;Pouch AM;Vrudhula A;Jackson BM
评估区域主动脉壁变形（RAWD）可能比最大主动脉直径或生长速率更好地预测腹主动脉瘤（AAA）破裂。使用连续的计算机断层扫描血管造影（CTA），我们开发了一个流线型的，半自动的方法计算RAWD使用变形图像配准（dirRAWD）。选择了15例不同形状和大小的AAA患者，间隔1 - 2年进行成对连续CTA。使用每例患者的初始CTA，手动和半自动分割管腔和主动脉壁表面。接下来，使用自动刚性图像配准将同一患者的随访CTA与第一次CTA对齐。然后使用可变形图像配准来计算连续扫描之间的局部动脉瘤壁扩张（dirRAWD）。为了测量技术准确性，将变形配准结果与解剖标志（基准标记）的局部位移进行比较，例如肠系膜下动脉和/或主动脉壁钙化的起源。此外，对于每例患者，手动测量每个动脉瘤的最大RAWD，并与相同位置的dirRAWD进行比较。该技术在所有患者中均获得成功。通过Wilcoxon秩和检验，平均标志位移误差为0.59 ± 0.93 mm，真实标志位移与可变形配准标志位移之间无差异（P = 0.39）。手动测量的最大RAWD和dirRAWD之间的绝对差异为0.27 ± 0.23 mm，相对差异为7.9%，使用Wilcoxon秩和检验无差异（P = 0.69）。与使用半自动AAA分割相比，使用纯手动AAA分割得出的最大dirRAWD无差异（P = .55）。我们发现准确和自动化的RAWD测量是可行的，临床上无意义的误差。与使用手动AAA分割相比，使用半自动AAA分割进行可变形图像配准方法不会改变最大dirRAWD准确度。未来的工作将比较dirRAWD与有限元分析得出的区域壁应力，并确定是否dirRAWD可能作为一个独立的预测破裂风险。目前的腹主动脉瘤（AAA）监测方法仅限于评估最大直径，无法准确预测AAA扩张和破裂风险。在动脉瘤的整个三维几何结构中自动评估AAA扩张可以更好地描述动脉瘤生长，并可以为管理决策提供大量信息，包括修复适应症。我们开发了一种准确和简化的方法，使用常规动脉瘤监测期间获得的计算机断层扫描成像评估局部三维AAA扩张，精度为亚毫米级。这种新的过程不需要大量的用户专业知识，也不需要计算机处理能力，并且可以使用科学家和临床医生都可以访问的开源软件来执行。
Assessment of regional aortic wall deformation (RAWD) might better predict for abdominal aortic aneurysm (AAA) rupture than the maximal aortic diameter or growth rate. Using sequential computed tomography angiograms (CTAs), we developed a streamlined, semiautomated method of computing RAWD using deformable image registration (dirRAWD). Paired sequential CTAs performed 1 to 2 years apart of 15 patients with AAAs of various shapes and sizes were selected. Using each patient’s initial CTA, the luminal and aortic wall surfaces were segmented both manually and semiautomatically. Next, the same patient’s follow-up CTA was aligned with the first using automated rigid image registration. Deformable image registration was then used to calculate the local aneurysm wall expansion between the sequential scans (dirRAWD). To measure technique accuracy, the deformable registration results were compared with the local displacement of anatomic landmarks (fiducial markers), such as the origin of the inferior mesenteric artery and/or aortic wall calcifications. Additionally, for each patient, the maximal RAWD was manually measured for each aneurysm and was compared with the dirRAWD at the same location. The technique was successful in all patients. The mean landmark displacement error was 0.59 ± 0.93 mm with no difference between true landmark displacement and deformable registration landmark displacement by Wilcoxon rank sum test (P = .39). The absolute difference between the manually measured maximal RAWD and dirRAWD was 0.27 ± 0.23 mm, with a relative difference of 7.9% and no difference using the Wilcoxon rank sum test (P = .69). No differences were found in the maximal dirRAWD when derived using a purely manual AAA segmentation compared with using semiautomated AAA segmentation (P = .55). We found accurate and automated RAWD measurements were feasible with clinically insignificant errors. Using semiautomated AAA segmentations for deformable image registration methods did not alter maximal dirRAWD accuracy compared with using manual AAA segmentations. Future work will compare dirRAWD with finite element analysis–derived regional wall stress and determine whether dirRAWD might serve as an independent predictor of rupture risk. Current abdominal aortic aneurysm (AAA) surveillance methods are limited to assessments of the maximal diameter, which cannot accurately predict for AAA expansion and rupture risk. Automated assessment of AAA expansion across the entire three-dimensional geometry of the aneurysm could better describe aneurysm growth and could substantially inform management decisions, including the indications for repair. We have developed an accurate and streamlined approach to assessing local three-dimensional AAA expansion with submillimeter accuracy using computed tomography imaging obtained during routine aneurysm surveillance. This novel process does not require significant user expertise nor computer processing power and can be performed using open-source software readily accessible to both scientists and clinicians.