Abstract
OBJECTIVE: Aortic wall thickness (AWT) is important for anatomic description and biomechanical modeling of aneurysmal disease. However, no validated, noninvasive method for measuring AWT exists. We hypothesized that semiautomated image segmentation algorithms applied to computed tomography angiography (CTA) can accurately measure AWT. METHODS: Aortic samples from 10 patients undergoing open thoracoabdominal aneurysm repair were taken from sites of the proximal or distal anastomosis, or both, yielding 13 samples. Aortic specimens were fixed in formalin, embedded in paraffin, and sectioned. After staining with hematoxylin and eosin and Masson's trichrome, sections were digitally scanned and measured. Patients' preoperative CTA Digital Imaging and Communications in Medicine (DICOM; National Electrical Manufacturers Association, Rosslyn, Va) images were segmented into luminal, inner arterial, and outer arterial surfaces with custom algorithms using active contours, isoline contour detection, and texture analysis. AWT values derived from image data were compared with measurements of corresponding pathologic specimens. RESULTS: AWT determined by CTA averaged 2.33 ± 0.66 mm (range, 1.52-3.55 mm), and the AWT of pathologic specimens averaged 2.36 ± 0.75 mm (range, 1.51-4.16 mm). The percentage difference between pathologic specimens and CTA-determined AWT was 9.5% ± 4.1% (range, 1.8%-16.7%). The correlation between image-based measurements and pathologic measurements was high (R = 0.935). The 95% limits of agreement computed by Bland-Altman analysis fell within the range of -0.42 and 0.42 mm. CONCLUSIONS: Semiautomated analysis of CTA images can be used to accurately measure regional and patient-specific AWT, as validated using pathologic ex vivo human aortic specimens. Descriptions and reconstructions of aortic aneurysms that incorporate locally resolved wall thickness are feasible and may improve future attempts at biomechanical analyses.