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AGeing effects on human aORta: from shApe to flowS

Periodic Reporting for period 1 - AGORAs (AGeing effects on human aORta: from shApe to flowS)

Reporting period: 2016-05-16 to 2018-05-15

Age-related remodeling of the aorta is associated with alterations in morphology and hemodynamics . These alterations are involved and accelerated in the presence of cardiovascular diseases (CVDs), suggesting that they are the likely culprits that underlie the increased cardiovascular risk associated with ageing . However, an advanced characterization of the age-related morphological/hemodynamic alterations and on their synergistic interplay is missing, mainly because encumbered by time-consuming operator-dependent tasks. In this 36 months global fellowship (University of Toronto, Canada and Politecnico di Torino, Italy), terminated after 6 months, the potential clinical utility of such a characterization will be addressed, developing tools for the quantitative assessment of the age-associated alterations in a large-scale cross-sectional dataset of aortas from subjects with successful ageing. After training on phase-contrast magnetic resonance imaging (PCMRI) technique, for each subject the 4D velocity field will be acquired. Quantitative morphometric parameters will be defined and evaluated in vivo. To investigate aortic hemodynamics, PCMRI will be complemented by computational fluid dynamics (CFD) to overcome PCMRI limitations on temporal/spatial resolution and wall shear stress quantification . The impact of CFD assumptions will be assessed by validating CFD results with PCMRI measurements. To improve CFD results accuracy, in the return phase PCMRI data will be incorporated into the numeric simulations, through the assimilation of the acquired flow fields into the CFD solver. Descriptors quantifiable in vivo and able to simplify the understanding of the complex 4D hemodynamic and of age-associated remodeling will be defined. The new tools for diagnostic/prognostic purposes will be integrated within the open-source Vascular Modelling ToolKit, to facilitate and streamline the diagnosis and monitoring of a wider range of CVDs when applied to other vascular districts (e.g. carotid, aneurysm).
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.
AGORAs will provide a) a framework able to enrich the information that can be extracted in vivo from clinical images and b) computational tools for the reliable reconstruction of aortic hemodynamics (validated by in vivo measurements). Such a technology is the first step for predictive, personalized and integrative medicine and is expected to have an outstanding impact on the health and welfare of populations suffering cardiovascular diseases and on health care systems in Europe. The developed methodology and tools will be applicable to a whole range of other vascular districts, e.g. carotid, coronaries, aneurysms and therefore opening new interesting lines of research. The outcomes of AGORAs will open interesting scenarios and numerous opportunities. The set of competences acquired during the project will impact on the participation to future research programs and network of excellence. For example, this project fits several of the societal challenges indicated by Horizon 2020 (e.g. topics: “development of new diagnostic tools and technologies: in vivo medical imaging technologies”, “using in silico medicine for improving disease management and prediction”). Other opportunities will be related to the development and application of patient-specific modelling methods for planning of CVD intervention and for the virtual evaluation of devices. In addition to the obvious scientific interest, it is worth noting that this kind of analysis has reached a sufficient level of maturity to be translated into the clinics and to be exploited commercially. Furthermore, the insights on disease progression will define design criteria for cardiovascular devices (e.g. aortic grafts), opening opportunities with medical devices companies.