In vivo estimation of glomerular filtration in the kidney using DCE-MRI

Abstract

In vivo estimation of glomerular filtration rate (GFR) in the kidney is a valuable tool for the clinician for diagnostics, treatment planning and follow up. In this work we present a pipeline for voxelwise computation of in vivo GFR using DCE-MRI. We apply fully automated elastic image registration with normalized gradient fields for motion correction. Kidney segmentation is performed using semi-automated nearest-neighbor segmentation. GFR is computed from pharmacokinetic modeling using two different models, and the obtained values are compared across time points and subjects, and between left and right kidney. The processing pipeline gives promising voxel-wise GFR estimates, but there are challenges related to numerical stability, calculation of concentration curves from signal intensities, and validation issues.