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Abstract #3052

Evaluation of DCE-MRI data sampling, reconstruction and model fitting using digital brain phantom

Yinghua Zhu 1 , Yi Guo 1 , Sajan Goud Lingala 1 , Samuel Barnes 2 , R. Marc Lebel 3 , Meng Law 1 , and Krishna Nayak 1

1 University of Southern California, Los Angeles, CA, United States, 2 California Institute of Technology, Pasadena, CA, United States, 3 GE Healthcare, Calgary, Canada

Brain DCE MRI is a powerful technique for evaluating blood-brain-barrier leakage in tumors, multiple sclerosis lesions, and other neurologic disorders. DCE-MRI is an active area of research but lacks a gold standard making it difficult to evaluate novel image acquisition, reconstruction, and processing techniques. We introduce the use of patient-derived digital phantoms that provide ground-truth and the ability to generate data with arbitrary temporal resolution, and perform sensitivity analysis over a broad range of inputs. We demonstrate its application to the evaluation of sparse sampling and constrained reconstruction methods.

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