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Abstract #0682

Automated Quality Evaluation Index for 2D ASL CBF Maps

Sudipto Dolui1,2, Ronald L. Wolf1, Seyed Ali Nabavizadeh1, David A. Wolk2, and John A. Detre1,2

1Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, 2Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States

We propose an automated Quality Evaluation Index (QEI) for evaluating the quality of cerebral blood flow (CBF) maps obtained using arterial spin labeling (ASL). Agreement between the proposed QEI and human ratings was comparable to that between human ratings. Poor quality CBF maps as assessed by QEI significantly correlated with lower test-retest reliability of mean CBF in different regions of interest for elderly control subjects. The proposed QEI can potentially be used in large-scale studies to automatically identify and discard degraded data from analysis, thereby reducing human effort and potential user bias.

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