Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI
| Autor: | Armin Raznahan, Lisa Ronan, Francois Lalonde, Aaron Alexander-Bloch, Jay N. Giedd, Liv S. Clasen, Michael Stockman |
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| Rok vydání: | 2016 |
| Předmět: |
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Radiological and Ultrasound Technology medicine.diagnostic_test Brain morphometry Magnetic resonance imaging 030218 nuclear medicine & medical imaging 03 medical and health sciences Brain anatomy 0302 clinical medicine Neurology Neuroimaging Convergent validity Functional neuroimaging medicine Radiology Nuclear Medicine and imaging Neurology (clinical) Anatomy Psychology Functional magnetic resonance imaging Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | Human Brain Mapping. 37:2385-2397 |
| ISSN: | 1065-9471 |
| Popis: | While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among "good quality" structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion-even at levels which do not manifest in visible motion artifact-can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. Hum Brain Mapp 37:2385-2397, 2016. © 2016 Wiley Periodicals, Inc. |
| Databáze: | OpenAIRE |
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