Imaging Intravoxel Vessel Size Distribution in the Brain Using Susceptibility Contrast Enhanced MRI

Abstract

Vascular remodelling is inherent to the pathogenesis of many diseases including cancer, neurodegeneration, fibrosis, hypertension, and diabetes. In this paper, a new susceptibility-contrast based MRI approach is established to analyse intravoxel vessel size distribution (VSD) enabling more comprehensive and quantitative assessment of vascular remodelling than existing clinical imaging modalities. We use segmented vascular structures from light-sheet fluorescence microscopy images of whole rodent brain to simulate gradient echo sampling of free induction decay and spin echo sequence (GESFIDE) and train a deep learning model to predict cerebral blood volume (CBV) and VSD from the simulated GESFIDE signal. The results from ex vivo experiments showed strong correlation (r=0.96) between the true and predicted CBV. Also, high similarity between true and predicted VSDs was observed with mean Bhattacharya Coefficient being 0.92. With further in vivo validation, intravoxel VSD imaging could become a transformative clinical tool for interrogating disease and treatment induced vascular remodelling.