Abstract #0651

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 characteristics.

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