Affiliation:
1. Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center Nashville Tennessee USA
2. Department of Radiology and Radiological Sciences Vanderbilt University Medical Center Nashville Tennessee USA
3. Vanderbilt O'Brien Kidney Research Center Vanderbilt University Medical Center Nashville Tennessee USA
4. Division of Nephrology and Hypertension Vanderbilt University Medical Center Nashville Tennessee USA
5. Department of Biomedical Engineering Vanderbilt University Nashville Tennessee USA
6. Pharmaceuticals Bayer AG Research & Development Wuppertal Germany
Abstract
PurposeWe aimed to compare multiple MRI parameters, including relaxation rates (, , and ), ADC from diffusion weighted imaging, pool size ratio (PSR) from quantitative magnetization transfer, and measures of exchange from spin‐lock imaging (), for assessing and predicting the severity of polycystic kidney disease (PKD) over time.MethodsPcy/Pcy mice with CD1 strain, a mouse model of autosomal dominant PKD, were imaged at 5, 9, and 26 wk of age using a 7T MRI system. Twelve‐week normal CD1 mice were used as controls. Post‐mortem paraffin tissue sections were stained using hematoxylin and eosin and picrosirius red to identify histological changes.ResultsHistology detected segmental cyst formation in the early stage (week 5) and progression of PKD over time in Pcy kidneys. In ‐weighted images, small cysts appeared locally in cystic kidneys in week 5 and gradually extended to the whole cortex and outer stripe of outer medulla region from week 5 to week 26. Regional PSR, , , and decreased consistently over time compared to normal kidneys, with significant changes detected in week 5. Among all the MRI measures, and allow highest detectability to PKD, while PSR and have highest correlation with pathological indices of PKD. Using optimum MRI parameters as regressors, multiple linear regression provides reliable prediction of PKD progression.Conclusion, , and PSR are sensitive indicators of the presence of PKD. Multiparametric MRI allows a comprehensive analysis of renal changes caused by cyst formation and expansion.
Funder
National Institutes of Health
Subject
Radiology, Nuclear Medicine and imaging