Optimizing full-brain coverage in human brain MRI through population distributions of brain size

Journal article

When defining an MRI protocol, brain researchers need to set multiple interdependent parameters that define repetition time (TR), voxel size, field-of-view (FOV), etc. Typically, researchers aim to image the full brain, making the expected FOV an important parameter to consider. Especially in 2D-EPI sequences, non-wasteful FOV settings are important to achieve the best temporal and spatial resolution. In practice, however, imperfect FOV size estimation often results in partial brain coverage for a significant number of participants per study, or, alternatively, an unnecessarily large voxel-size or number of slices to guarantee full brain coverage. To provide normative FOV guidelines we estimated population distributions of brain size in the x-, y-, and z-direction using data from 14,781 individuals. Our results indicated that 11. mm in the z-direction differentiate between obtaining full brain coverage for 90% vs. 99.9% of participants. Importantly, we observed that rotating the FOV to optimally cover the brain, and thus minimize the number of slices needed, effectively reduces the required inferior-superior FOV size by ~. 5%. For a typical adult imaging study, 99.9% of the population can be imaged with full brain coverage when using an inferior-superior FOV of 142. mm, assuming optimal slice orientation and minimal within-scan head motion. By providing population distributions for brain size in the x-, y-, and z-direction we improve the potential for obtaining full brain coverage, especially in 2D-EPI sequences used in most functional and diffusion MRI studies. We further enable optimization of related imaging parameters including the number of slices, TR and total acquisition time. © 2014 Elsevier Inc.

Authors: Mennes, M; Jenkinson, M; Valabregue, R; Buitelaar, J; Beckmann, C

• Publisher: Academic Press Inc.
• Journal: NeuroImage
• Volume: 98
• Pages: 513-520
• Publication date: 2014-01-01
• DOI: 10.1016/j.neuroimage.2014.04.030
• EISSN: 1095-9572
• ISSN: 1053-8119
• Language: English
• Keywords: Field-of-view; Neuroimaging; Population brain size; FOV