# Comprehensive MRI-based evaluation of human renal microstructure

> **NIH NIH R01** · UNIVERSITY OF VIRGINIA · 2020 · $439,333

## Abstract

PROJECT SUMMARY/ABSTRACT
The broad, long-term goal of this multi-disciplinary collaborative of biomedical engineers and physician-
scientists is to develop a framework to rapidly and accurately assess the quality of kidneys donated for
transplant. Current methods to assess the quality of a donated kidney are derived from population-based
surrogates and the limited functional measurements of the individual kidney are only moderately predictive of
long-term survival. Additionally, there are no direct, noninvasive clinical measurements of the vasculature or
tubulointerstitial compartments. This proposal focuses on the use of novel, noninvasive, MRI-based biomarkers
to evaluate human kidneys to individualize and improve the assessment of allograft quality while remaining
within the current standards of clinical practice. This work has three Specific Aims: 1) Noninvasively compare
MRI-based biomarkers of the glomeruli in human kidneys to metrics currently used in clinical practice (KDPI
score and renal resistance by machine perfusion), 2) Noninvasively compare MRI-based biomarkers of
microvascular structure in human kidneys to metrics currently used in clinical practice and 3) Develop
noninvasive MRI biomarkers of microstructural tubulointerstitial damage that can discriminate reversible from
irreversible damage. We will synthesize these aims into a comprehensive view of the renal allograft. The long
term goal of this work will be a software platform that integrates all available data (both MRI-based and clinical
parameters) from glomerular, vascular, and tubulointerstitial compartments to provide a superior metric of
allograft quality. At the conclusion of this project, we will have the first comprehensive, integrated evaluation of
the microstructure of the human kidney, powerful data to inform the translation of these MRI-based biomarkers
for future studies to improve longevity matching and long-term allograft survival.

## Key facts

- **NIH application ID:** 9987607
- **Project number:** 5R01DK111861-04
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Kevin M Bennett
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $439,333
- **Award type:** 5
- **Project period:** 2017-08-01 → 2022-07-01

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9987607

## Citation

> US National Institutes of Health, RePORTER application 9987607, Comprehensive MRI-based evaluation of human renal microstructure (5R01DK111861-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9987607. Licensed CC0.

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