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both age (b= 0.08; P<0.0001) and MAP (b=0.03; P<0.0001) were independent predictors of PWV. The 3D models showed that 55% of the variation in left ventricle wall thickness can be accounted for by a linear model that includes PWV, age, gender, race, and BSA as co-variates. The models demonstrated strong regional associations between PWV and wall thickness which may reflect adaptations to normalize wall shear stress in the LV. Conclusions This study of healthy volunteers showed that age is the strongest independent predictor of PWV and that the associated morphological adaptations of the LV may be modelled in 3D. This computational approach to phenotyping may provide insights into the physiological adaptations in the LV associated with vascular function

Three dimensional modelling of the effect of arterial pulse wave velocity and body size on left ventricular geometry