Volumetric Layer Based Analysis for Quantitative Renal MRI

Motivation: To provide improved methods to estimate cortical-medullary changes in multiparametric MRI measures of the kidney. Goal(s): To develop an analysis method for use with 3D data to generate quantitative-depth-based cortical-medullary layers which can be applied to any multiparametric map. Approach: 3DQLayers segments the kidney into layers based on their distance from the renal surface using the Trimesh Python library. Results: Generated 3D layers can be applied to multiparametric MRI scans collected in the same session. Here, this is applied to assess cortical layer profiles and contour plots of quantitative T1-mapping, R2*-mapping and perfusion measures, and to estimate renal cortical thickness. Impact: 3DQLayers provides a layer-based analysis technique for renal multiparametric MRI data, extending traditional ROI-based methods. Layer profiles of any quantitative MRI data can be output and average renal cortical thickness estimated, these are important measures to study in renal disease.