Complementing sparse vascular imaging data by physiological adaptation rules

Abstract

To benefit personalized pulse wave propagation (PWP) modeling, we propose a novel method that, instead of relying on extensive data sets on vascular geometries, incorporates physiological adaptation rules. The developed vascular adaptation model adequately predicted arterial radius and wall thickness compared with ultrasound and MRI estimates, obtained in humans. Our approach could be used as a tool to facilitate personalized modeling, notably in case of missing data, as routinely found in clinical settings.