Imaging-based biomechanical parameters for assessing risk of aortic dissection and rupture in thoracic aortic aneurysms.

Objectives: Imaging-based methods of measuring aortic biomechanics may provide superior and a more personalized in vivo risk assessment of patients with thoracic aortic aneurysms compared to traditional aortic size criteria such as maximal aortic diameter. We aim to summarize the data on in vivo imaging techniques for evaluation of aortic biomechanics.

Methods: A thorough search of literature was conducted in MEDLINE, EMBASE and Google Scholar for evidence of various imaging-based biomechanics techniques. All imaging modalities were included. Data involving preclinical/animal models or exclusively focussed on abdominal aortic aneurysms were excluded.

Results: The various imaging-based biomechanical parameters can be divided into categories of increasing complexity: strain-based, stiffness-based and computational modelling-derived. Strain-based and stiffness-based parameters are more simply calculated and can be derived using multiple imaging modalities. Initial studies are promising towards linking these parameters with clinically relevant end-points, including aortic dissection, though work is required for standardization. Computationally derived parameters provide detail of stress exerted on the aortic wall with great spatial resolution. However, they are highly dependent on the assumptions applied to the models, such as material properties of the aortic wall.

Conclusions: Imaging-based aortic biomechanics represent a major technical advancement for personalized in vivo risk stratification of patients with ascending thoracic aortic aneurysm. The next steps in clinical translation require large-scale validation of these markers towards predicting aortic dissections and comparison against the gold standard ex vivo aortic biomechanics as well as development of a user-friendly, low-cost algorithm that can be widely adopted.