Abstract #3245

Accuracy of Morphometry Measures from MPRAGE data with Prospective Motion Correction Based on an Optical Tracking System

Joelle E Sarlls¹, Francois Lalonde², J Andrew Derbyshire³, Sean Marrett³, Patrick Hucker⁴, Maxim Zaitsev⁴, and S Lalith Talagala¹

¹NINDS/NMRF, National Institutes of Health, Bethesda, MD, United States, ²NIMH/DNU, National Institutes of Health, Bethesda, MD, United States, ³NIMH/fMRIF, National Institutes of Health, Bethesda, MD, United States, ⁴MR Development and Application Center, University Medical Center Freiburg, Freiburg, Germany

Subject motion during MRI results in poor image quality and may cause bias in the morphormetric measures extracted from segmentation algorithms. Prospective motion correction (PMC) techniques can mitigate these effects by tracking brain motion and updating the scan parameters in realtime. Here, we compared the accuracy of cortical thickness and volume extracted from MPRAGE data of non-moving and intentionally moving subjects when using a PMC method based on a Moire phase tracking marker and an optical system. Data show that the PMC method used here can greatly reduce image artifacts and provide more accurate segmentation resuIts during intentional motion.

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