Predicting the Evolution of Type-B Aortic Dissection: Combining Computational Hemodynamics and Data Analysis

Abstract: Type-B Aortic Dissection (TBAD) is a lethal heart disease that occurs when a tear develops in the intimal tear of the aorta, causing the layers of the aortic wall to separate. The tear leads to the formation of False Lumen (FL). It challenges clinicians as it is quite difficult to predict the evolution of the pathology once detected. Invasive operations should be limited to cases when the prognosis indicates a significant risk of growth and rupture of the FL. A variety of possible morphological indicators have been considered, however none of them are controversy-free. The present contribution stems from the hypothesis that a strong integration of morphological and hemodynamics data can provide the key for an accurate prediction of the FL evolution in time to support clinical guidelines. The hemodynamics can be retrieved from computational simulations, challenged by the complexity of the anatomy and the flow conditions. An accurate data analysis is, in turn, challenged by the lack of data and the variety of possible morphologies that make it difficult to draw statistically significant conclusions. In this talk, we will present preliminary results of an integrated data-driven/model-driven approach, and we will point out possible new combined morphological/functional indicators with a potential predictive role, outlining the importance of the combination of different approaches for the successful accomplishment of the task.

Last modified: Wed Mar 27 14:12:57 EDT 2024