Accelerated brain DCE-MRI using Contrast Agent Kinetic Models as Temporal Constraints
Sajan Goud Lingala1, Yi Guo1, Yinghua Zhu1, Naren Nallapareddy1, R. Marc Lebel2, Meng Law3, and Krishna Nayak1
1Electrical Engineering, University of Southern California, Los Angeles, CA, United States, 2GE Health care, Calgary, Canada, 3Radiology, University of Southern California, Los Angeles, CA, United States
We propose a novel tracer-kinetic model based constrained
reconstruction scheme to enable highly accelerated DCE-MRI. The proposed
approach efficiently leverages information of the contrast agent kinetic
modeling into the reconstruction, and provides a novel alternative to current
constraints that are blind to tracer kinetic modeling.
We develop the frame-work to include constraints derived from the extended-Tofts (e-Tofts) model. We perform noise
sensitivity analysis to determine the accuracy and precision of parameter mapping
with the proposed e-Tofts derived temporal bases. We demonstrate its utility in
retrospectively accelerating brain tumor DCE datasets with different tumor
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