Although age is the dominant risk factor for cardiovascular diseases (CVDs), only recently the specific mechanisms underlying the increased risks conferred by arterial ageing are being considered. Much of the current investigations and diagnostic decisions are derived from simple anatomic observations, notwithstanding the complexity of the human aorta geometry. In addition, volumetric information is available and advanced morphometric and hemodynamic tools to investigate complex hemodynamic problems can be developed. This project addresses the need for an advanced characterization of the age-related morphological/hemodynamic alterations and on their synergistic interplay in aorta, which is currently missing mainly because encumbered by time-consuming operator-dependent tasks. By the identification of new relevant markers of subclinical age-related alterations, which are major cardiovascular risk factors, the proposed thorough analyses represent a novel approach to study aortic ageing, providing objective, quantitative, and mechanism-based parameters useful for the study of the origin, development and progression of CVDs. In this way, it will be possible to provide mechanistic explanations to clinical observations. To obtain such a novel point of view, a multidisciplinary approach is required to combine advanced morphometric analysis and advanced hemodynamic analyses, which will be substantially improved as they are currently not fully automated and more research-oriented than clinically-oriented. The minimization of the operator intervention (increasing repeatability and robustness) will improve the state-of-the-art in terms of completeness and accuracy of the currently available tools. The introduction of an open-access tool will hopefully lead to the widespread adoption, improvement and standardization of methods, facilitating the reproducibility and comparability of results among studies, and ultimately increasing the chance of generating results contributing to clinical evidence. To improve morphometric characterization, the 3D geometry will be characterized over time. Considering the hemodynamic in vivo characterization, for the first time the hemodynamic changes due to ageing will be characterized quantitatively and from the analysis of the relationship morphology-hemodynamics, a novel point of view on age-associated remodelling will be given. To maximize the potential of hemodynamics as a source of information, a multidisciplinary approach combining CFD and PCMRI is proposed. State-of-the-art modelling strategies of aortic hemodynamics require assumptions and operator-dependent specifications influencing the predicted hemodynamic scenario. The incorporation of PCMRI velocity measurements can provide a more accurate description of the hemodynamics, merging measured information (generally sparse and noisy) into a numerical model. Main limitations linked to the CFD assumptions like rigid wall and laminar assumption will be addressed, developing a numerical framework validated by the PCMRI acquisitions. In conclusion, the possibility to screen CVD risk from in vivo measurements of morphometric of hemodynamic quantities as promoters/surrogates of disturbed shear stress is attractive in terms of translation of biomechanical principles into clinical practice.
