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Abstract #1148

Development of an Automated Threshold Technique Based on Reproducibility of FMRI Activation.

Tynan Stevens1,2, Steven Beyea, 12, Ryan D'Arcy2,3, David Clarke4,5, Chris Bowen, 12, Gerhard Stroink1

1Physics, Dalhousie University, Halifax, NS, Canada; 2NRC Institute for Biodiagnostics (Atlantic), Halifax, NS, Canada; 3Neuroscience, Dalhousie University, Halifax, NS, Canada; 4Neurosurgery, QEII Health Science Center, Halifax, NS, Canada; 5Surgery, Dalhousie University, Halifax, NS, Canada

Setting activation thresholds remains a challenge in functional MRI. While strategies exist to address the increased chance of false positive activations due to the large number of voxels in an fMRI image, these methods frequently ignore differences in activation strength between tasks, individuals, and scanners. Setting appropriate thresholds is particularly pertinent in presurgical mapping, as knowledge of the location and extent of functional cortex can affect surgical decisions. In this work, we demonstrate an automated threshold technique based on test-retest imaging and receiver-operator characteristic curves, which produces individualized threshold levels optimized for reproducibility of the observed activation.