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Abstract #2904

Towards a robust and reproducible GluCEST analysis pipeline

Joelle Jee1, Ravi Prakash Reddy Nanga2, Abigail Cember2, Paul Jacobs2, Heather Robinson1, Mark A Elliott2, Ravinder Reddy2, and David R Roalf1
1Psychiatry, University of Pennsylvania, Philadelphia, PA, United States, 2Radiology, University of Pennsylvania, Philadelphia, PA, United States


Robust, reproducible methods are paramount in neuroimaging. This is a challenge for leading-edge and novel techniques at 7T MRI, such as glutamate-weighted chemical exchange saturation transfer (GluCEST). As such, our primary objective is to move towards a robust and reproducible analytical pipeline for GluCEST imaging data. Here we show, using python-based neuroimaging tools, the development of GluCEST-prep. GluCEST-prep incorporates common neuroimaging analysis steps—brain extraction, tissue segmentation, co-registration and normalization—that are optimized for 7T MRI and uses python-based analysis—in place of in-house MATLAB scripts—to generate post-processed 2D or 3D GluCEST images in both native and template space.

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