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MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies

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Abstract

Mouse models are crucial for neuroscience research, yet discrepancies arise between macro- and meso-scales due to sample preparation altering brain morphology. The absence of an accessible toolbox for magnetic resonance imaging (MRI) data processing presents a challenge for assessing morphological changes in the mouse brain. To address this, we developed the MBV-Pipe (Mouse Brain Volumetric Statistics-Pipeline) toolbox, integrating the methods of Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra (DARTEL)-Voxel-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) to evaluate brain tissue volume and white matter integrity. To validate the reliability of MBV-Pipe, brain MRI data from seven mice at three time points (in vivo, post-perfusion, and post-fixation) were acquired using a 9.4T ultra-high MRI system. Employing the MBV-Pipe toolbox, we discerned substantial volumetric changes in the mouse brain following perfusion relative to the in vivo condition, with the fixation process inducing only negligible variations. Importantly, the white matter integrity was found to be largely stable throughout the sample preparation procedures. The MBV-Pipe source code is publicly available and includes a user-friendly GUI for facilitating quality control and experimental protocol optimization, which holds promise for advancing mouse brain research in the future.
Title
MBV-Pipe: A One-Stop Toolbox for Assessing Mouse Brain Morphological Changes for Cross-Scale Studies
Authors
Wentao Jiang
Xinyi Liu
Ming Song
Zhengyi Yang
Lan Sun
Tianzi Jiang
Publication date
16-09-2024
Publisher
Springer US
Published in
Neuroinformatics / Issue 4/2024
Print ISSN: 1539-2791
Electronic ISSN: 1559-0089
DOI
https://doi.org/10.1007/s12021-024-09687-1
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Image Credits
Human brain illustration/© (M) CHRISTOPH BURGSTEDT / SCIENCE PHOTO LIBRARY / Getty Images, Navigating neuroimaging in Alzheimer’s care: Practical applications and strategies for integration/© Springer Health+ IME