Abstract #0178

Multi-delay arterial spin labeling (ASL) more accurately detects hypoperfusion in Moyamoya disease: comparison with a normative PET/MRI database

Audrey P. Fan¹, Mohammad M. Khalighi², Jia Guo¹, Yosuke Ishii¹, Mirwais Wardak¹, Jun-Hyung Park¹, Bin Shen¹, Dawn Holley¹, Harsh Gandhi¹, Prachi Singh¹, Tom Haywood¹, Gary K. Steinberg³, Frederick T. Chin¹, and Greg Zaharchuk¹

¹Radiology, Stanford University, Stanford, CA, United States, ²GE Healthcare, Menlo Park, CA, United States, ³Neurosurgery, Stanford University, Stanford, CA, United States

We directly compared multi-delay arterial spin labeling (ASL) and standard ASL measurements of cerebral blood flow (CBF) to simultaneously acquired [¹⁵O]-PET scans on hybrid PET/MRI in Moyamoya disease. For these Moyamoya patients (N=15) with extremely long arterial transit times, multi-delay ASL outperforms standard ASL in regional correlation and reduces bias relative to PET. We also constructed a voxelwise, normative CBF database based on healthy controls (N=15) with PET/MRI, and identified regions of hypoperfusion in frontal and parietal regions of patients. Multi-delay ASL is more specific to areas of Moyamoya hypoperfusion (more similar to PET), whereas standard ASL overestimates these areas due to low signal.

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