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https://hdl.handle.net/2440/121625
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Type: | Journal article |
Title: | Optimizing full-brain coverage in human brain MRI through population distributions of brain size |
Author: | Mennes, M. Jenkinson, M. Valabregue, R. Buitelaar, J.K. Beckmann, C. Smith, S. |
Citation: | NeuroImage, 2014; 98:513-520 |
Publisher: | Elsevier |
Issue Date: | 2014 |
ISSN: | 1053-8119 1095-9572 |
Statement of Responsibility: | Maarten Mennes, Mark Jenkinson, Romain Valabregue, Jan K. Buitelaara, Christian Beckmann, Stephen Smith |
Abstract: | 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 11mm 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 142mm, 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. |
Keywords: | Brain Humans Magnetic Resonance Imaging Diffusion Magnetic Resonance Imaging Demography Adolescent Adult Aged Aged, 80 and over Middle Aged Child Child, Preschool Female Male Young Adult Neuroimaging |
Rights: | © 2014 Elsevier Inc. All rights reserved. |
DOI: | 10.1016/j.neuroimage.2014.04.030 |
Published version: | http://dx.doi.org/10.1016/j.neuroimage.2014.04.030 |
Appears in Collections: | Aurora harvest 4 Computer Science publications |
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