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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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