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Abstract #4685

Performance of Generalized Factor Analysis of Dynamic Sequence (GFADS) in the Automated Characterization of Renal Function and Tissue Enhancement in Dynamic Magnetic Resonance Imaging (MRI)

Ruth Lim1, Jinsong Ouyang1, Matthew D. Schmitz1, Michael S. Gee1, Ranu Shailam1, Raul N. Uppot1, Georges El Fakhri1

1Department of Radiology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, United States

We assessed the performance of a novel generalized factor analysis of dynamic sequences (GFADS) in dynamic, contrast-enhanced renal magnetic resonance imaging (MRI). By detecting unique time-intensity curves for each renal tissue/compartment type, this technique automates the creation of regions of interest (ROIs) around and within the kidneys, and obviates the need for manually-drawn ROIs. These time factor curves are computed from entire factor images and are significantly less affected by noise than time-intensity curves computed within regions of interest that span a few voxels. In this study, we found that GFADS software can successfully, semi-automatically, and rapidly identify the renal cortex, medulla, and collecting system on dynamic contrast-enhanced renal MRI studies while obviating the need to use manually-drawn regions of interest. This enables detailed quantitative assessment of cortical and medullary renal function in normal and abnormal kidneys.