Joelle E. Sarlls1, Philip Shaw2, 3, Nancy E. Adleman4, Vinai Rooopchansingh5
1NINDS/NIH MRI Research Facility, National Institutes of Health, Bethesda, MD, United States; 2NIMH, National Institutes of Health; 3NHGRI, National Institutes of Health; 4NIMH/Emotion and Development Branch, National Institutes of Health; 5NIMH/Functional MRI Facility, National Institutes of Health
A retrospective study of pediatric imaging data revealed widespread corruption of diffusion images due to large head motion. Using an automated real-time software framework, and straightforward calculations in AFNI, diffusion-weighted imaging volumes that have been corrupted by large motions can be detected and reacquired within a scan session. This rapid diffusion QA method provides an efficient way for consistent diffusion data sets to be acquired, with minimal scan time. Reacquiring the corrupted diffusion data avoids potential bias due to removal of variable numbers of corrupted volumes and potentially increases sensitivity to detect change in diffusion properties in populations that tend to move.