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Abstract #1883

Regional Heterogeneity in Moyamoya Disease: Discovering Local Arterial Transit Time Information from Single-Delay Arterial Spin Labeling

Wendy W Ni1 and Greg Zaharchuk1

1Radiology, Stanford University, Stanford, CA, United States

Arterial transit information provides valuable diagnostic information in steno-occlusive pathologies. We propose deriving transit information from the regional spatial heterogeneity (ReHet) of standard single-delay pseudo-continuous arterial spin labeling difference images. With image processing and machine learning, we demonstrate the potential of this technique in identifying regions with slow arterial flow in pre-operative Moyamoya disease patients. We investigate a selection of 7 different ReHet metrics, and identify trends that will inform better design of ReHet metrics and machine learning models.

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