Abstract #1952

High spatiotemporal resolution cones 4D flow using memory-efficient iterative reconstruction

Christopher M. Sandino¹, Frank Ong², Joseph Y. Cheng³, Michael Lustig², Marcus T. Alley³, and Shreyas S. Vasanawala³

¹Electrical Engineering, Stanford University, Stanford, CA, United States, ²Electrical Engineering, University of California, Berkeley, Berkeley, CA, United States, ³Radiology, Stanford University, Stanford, CA, United States

4D flow MRI enables comprehensive cardiovascular assessment, but is limited by long acquisition times and motion corruption. Non-Cartesian sampling strategies, such as radial and cones, exhibit excellent aliasing properties that allow reduced scan times and improve motion robustness. However, trade-offs between spatial and temporal resolution are necessary due to computational burden of iterative 4D non-Cartesian reconstruction. This has restricted cones 4D flow to low temporal resolution venous applications. Here we present a memory-efficient iterative reconstruction utilizing batch processing to enable arbitrary spatiotemporal resolution. We demonstrate feasibility of sub-millimeter, 30 cardiac phase cones 4D flow for coronary artery and valvular assessment.

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