Abstract #1230

Scan parameter optimization of dual-venc 4D Flow MRI for the assessment of neurovascular flow networks in brain arteriovenous malformation

Maria Aristova¹, Alireza Vali², Alex Barker², Ali Shaibani³, Sameer Ansari⁴, Matthew Potts⁵, Babak Jahromi⁵, Michael Hurley⁴, Susanne Schnell², and Michael Markl²

¹Biomedical Engineering, Northwestern University, Chicago, IL, United States, ²Radiology, Northwestern University, Chicago, IL, United States, ³Radiology, Neurosurgery, Northwestern University, Chicago, IL, United States, ⁴Neurointerventional radiology, Northwestern University, Chicago, IL, United States, ⁵Neurosurgery, Northwestern University, Chicago, IL, United States

To optimize dual-venc 4D Flow MRI parameters for flow assessment in brain arteriovenous malformations, we conducted an in-vitro optimization analysis and compared it to in-vivo data from a patient with complex AVM. Using k-t acceleration factors of 2-5 and about 2-10 voxels across the imaged vessels, we quantified the agreement with the ground truth flow and geometry. We applied a flow distribution network graph concept to characterize flow conservation as an additional quality metric. Data indicated that approximately 5 voxels across imaged vessels are needed, consistent with results from previous publications.

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