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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