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Abstract #1551

The Influence of Image Registration and Segmentation Error on Functional MR Renography

Christopher C. Conlin1, 2, Jeff L. Zhang, 23, Marta E. Heilbrun, 23, Henry Rusinek4, Artem V. Mikheev4, Vivian S. Lee, 23

1Department of Bioengineering, University of Utah, Salt Lake City, UT, United States; 2Utah Center for Advanced Imaging Research, Salt Lake City, UT, United States; 3Department of Radiology, University of Utah, Salt Lake City, UT, United States; 4Department of Radiology, New York University, New York, United States

This investigation employed Monte Carlo simulations and a patient study to examine the effects of image registration and segmentation error on the accuracy of renal functional parameter estimates as measured with dynamic Gd-MRI. Image registration and segmentation is performed as the first step in quantitative analysis of the dynamic images. Imperfect registration and segmentation may lead to errors in the estimated single kidney glomerular filtration rate (skGFR). It was found that GFR is a robust functional renal parameter that is resistant to errors introduced during registration and segmentation of Gd-MRI and that clinically acceptable GFR estimates can be obtained quickly.