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Updated: May 13, 2026

Measuring Ascending Aortic Stiffness In Vivo in Mice Using Ultrasound
Published on: December 2, 2014
In vivo aortic elasticity measurement using electrocardiogram-gated computed tomography: validation with ex vivo
Junki Yokota1,2, Takashi Shirakawa1, Kazuo Shimamura1
1Department of Cardiovascular Surgery, Osaka University Graduate School of Medicine, Suita, Osaka, Japan.
Objectives:
Aortic aneurysm size is a key determinant for surgical intervention, but aortic catastrophes can occur before reaching the size criteria, indicating size alone is insufficient for risk assessment. Aortic mechanical properties could be another factor for predicting such catastrophes. However, its estimation in daily clinical settings remains impractical. This study aimed to validate a noninvasive electrocardiogram-gated computed tomography (EGCT)-based method for assessing aortic mechanical properties by comparing its measurements with ex vivo tensile testing of resected specimens.
Methods:
We analysed 49 patients who underwent surgical repair of the ascending aorta. The mechanical properties of the aortic wall were assessed using two parameters: elastic modulus (E), representing stiffness and strain energy (SE), reflecting stored deformation energy. Ex vivo loading test was performed on resected specimens, while in vivo measurements were obtained from preoperative EGCT scans using a custom analysis plugin. Correlation and agreement between methods were evaluated using Spearman's correlation (r), Bland-Altman analysis and intraclass correlation coefficients (ICC).
Results:
EGCT-based measurements of E and SE showed strong correlations with ex vivo loading test (r = 0.733 and r = 0.773, respectively). Bland-Altman analysis demonstrated good agreement, with minimal bias for E and a negative proportional bias for SE. ICC values indicated good-to-excellent reliability for E (0.86) and moderate reliability for SE (0.63).
Conclusions:
EGCT-based measurement is a feasible, reliable method for assessing aortic mechanical properties noninvasively. Although further studies are needed to refine predictive accuracy, this approach may enhance risk stratification for aortic catastrophes in future clinical practice.
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