Abstract #0717

Multiple Linear Regression for Predicting Fibrosis in the Kidney using T1 Mapping and ‘RESOLVE’ Diffusion-Weighted MRI

Iris FRIEDLI¹, Lindsey Alexandra CROWE¹, Lena BERCHTOLD², Solange MOLL³, Karine HADAYA², Thomas DE PERROT¹, Pierre-Yves MARTIN², Sophie DE SEIGNEUX², and Jean-Paul VALLEE¹

¹Department of Radiology, Geneva University Hospitals, Geneva, Switzerland, ²Department of Nephrology, Geneva University Hospitals, Geneva, Switzerland, ³Department of Pathology, Geneva University Hospitals, Geneva, Switzerland

Multi-parametric studies are beginning to emerge in renal disease assessment. However these studies investigated each MR parameter independently and compare the MR sequences but do not combine multiple parameters in a single statistic. In this multi-parametric 3T MR study, the sensitivity of T1 mapping and Readout Segmentation Of Long Variable Echo train (RESOLVE) DWI parameters was first independently evaluated and compared against interstitial fibrosis of 31 Chronic Kidney Disease patients undergoing renal biopsy. The two MR parameters were then associated in a single statistic with the hypothesis that used together they can improve the non-invasive detection of interstitial fibrosis.

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