Predissection-derived geometric and distensibility indices reveal increased peak longitudinal stress and stiffness in patients sustaining acute type A aortic dissection: Implications for predicting dissection.

OBJECTIVE

To assess ascending aortic distensibility and build geometry and distensibility-based patient-specific stress distribution maps in patients sustaining type A aortic dissection (TAAD) using predissection noninvasive imaging.

METHODS

Review of charts from patients undergoing surgical repair of TAAD (n = 351) led to the selection of a subset population (n = 7) with 2 or more predissection computed tomography angiography scans and echocardiograms at least 1 year before dissection. Ascending aortic wall biomechanical properties (aortic strain, distensibility, and stiffness) were compared with age- and size-matched nondissected nonaneurysmal controls. Patient-specific aortic strain served as an input in aortic geometry-based simulated 3-dimensional reconstructions to generate longitudinal and circumferential wall stress maps. Inspection of perioperative dissection scans and intraoperative visual examination confirmed primary tear locations.

RESULTS

Predissection echocardiography revealed ascending aortas of patients sustaining TAAD to exhibit decreased aortic wall strain (14.50 ± 1.13% vs 8.49 ± 1.08%; P < .01), decreased distensibility (4.26 ± 0.44 vs 2.39 ± 0.33 10 cm·dyne; P < .01), increased stiffness (3.84 ± 0.24 vs 7.48 ± 1.05; P < .001), and increased longitudinal wall stress (246 ± 22 vs 172 ± 37 kPa; P < .01). There was no significant difference in circumferential wall stress. Predissection computed tomography angiography models revealed overlap between regions of increased longitudinal wall stress and primary tear sites.

CONCLUSIONS

Using predissection imaging, we identified increased stiffness and longitudinal wall stress in ascending aortas of patients with dissection. Patient-specific imaging-derived biomechanical property maps like these may be instrumental toward designing better prediction models of aortic dissection potential.