Abstract #0011

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

Yannick Bliesener¹, Robert Marc Lebel^2,3, 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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