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Abstract #2487

Spatial Heterogeneity in Quantitative Renal ADC, ASL perfusion and R2* Maps Using Texture Analysis

Lu-Ping Li1,2, Emily Wilt1, Artem Mikheev3, Henry Rusinek3, Stuart Sprague1,2, Orly Kohn2, and Pottumarthi Prasad1,2
1NorthShore University HealthSystem, Evanston, IL, United States, 2Pritzker School of Medicine, University of Chicago, Chicago, IL, United States, 3Langone School of Medicine, New York University School of Medicine, New York, NY, United States


While regions of interest analysis is widely used in quantitative MRI, emphasis usually is placed only on the spatial average and information of spatial heterogeneity is ignored. Texture analysis has gained increasing interest in the context of applying artificial intelligence. These Radiomic tools are now readily available in image analysis tool boxes for more widespread adoption. We illustrate an application of such analysis on quantitative renal MRI, including ADC, ASL and R2* maps. Our results show that several measures of heterogeneity of cortical voxel-wise maps discriminate between healthy and individuals with chronic kidney disease.

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