Non-invasive estimation of relative pressure in the murine aortic arch using virtual work-energy (vWERP)

Motivation: MRI-based relative pressure is a promising imaging biomarker. A new technique, vWERP, improves pressure estimations compared to more simplified approaches. Validated in clinical settings, it's unexplored in mouse models. Goal(s): To apply the vWERP algorithm to MRI-microscopy for pressure measurements in wild-type and atherosclerotic mouse models. Approach: 4D flow MRI was performed in wild-type and ApoE-/- mice. Post-processing involved segmenting the aorta, defining analysis planes, and calculating pressure drops using the vWERP algorithm for analysis. Results: Using vWERP with 4D flow MRI shows promise for studying vascular disease hemodynamics. Preliminary findings suggest pressure as a robust parameter to examine changes in CVD progression. Impact: Application of vWERP to MRI-microscopy in mice reveals high potential for assessing cardiovascular disease progression, particularly in studying pressure changes. This new diagnostic tool benefits vascular health studies in preclinical settings and may be used to study atherosclerotic plaque development.