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Abstract #0011

Pseudo Test-Retest Evaluation of Sparse DCE-MRI of Brain Tumor

Yannick Bliesener1, Robert Marc Lebel2,3, Jay Acharya4, Richard Frayne5, and Krishna Shrinivas Nayak1
1Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 2Applications and Workflow, GE Healthcare, Calgary, AB, Canada, 3Department of Radiology, University of Calgary, Calgary, AB, Canada, 4Department of Clinical Radiology, Keck School of Medicine of University of Southern California, Los Angeles, CA, United States, 5Departments of Radiology, and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

Brain DCE MRI suffers from poor spatial coverage, lack of standardization, and insufficient quantitative understanding of the extent of (physical) uncertainty in the measurements. Here, we attempt to overcome these by providing a fully automated high-resolution whole-brain DCE MRI pipeline with no user interaction. Prospective test-retest repeatability evaluation is challenging, therefore we employ a surrogate: multiple post-treatment time points in stable brain tumor patients. The proposed framework is able to yield consistent vascular input functions and tracer kinetic parameter histograms for repeated visits.

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