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Automated Computational Processing of 3-D MR Images of Mouse Brain for Phenotyping of Living Animals

Medina, Christopher S. and Manifold-Wheeler, Brett and Gonzales, Aaron and Bearer, Elaine L. (2017) Automated Computational Processing of 3-D MR Images of Mouse Brain for Phenotyping of Living Animals. Current Protocols in Molecular Biology, 119 . 29A.5.1-29A.5.38. ISSN 1934-3639. PMCID PMC6195809. https://resolver.caltech.edu/CaltechAUTHORS:20170710-083149452

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Abstract

Magnetic resonance (MR) imaging provides a method to obtain anatomical information from the brain in vivo that is not typically available by optical imaging because of this organ's opacity. MR is nondestructive and obtains deep tissue contrast with 100-µm^3 voxel resolution or better. Manganese-enhanced MRI (MEMRI) may be used to observe axonal transport and localized neural activity in the living rodent and avian brain. Such enhancement enables researchers to investigate differences in functional circuitry or neuronal activity in images of brains of different animals. Moreover, once MR images of a number of animals are aligned into a single matrix, statistical analysis can be done comparing MR intensities between different multi-animal cohorts comprising individuals from different mouse strains or different transgenic animals, or at different time points after an experimental manipulation. Although preprocessing steps for such comparisons (including skull stripping and alignment) are automated for human imaging, no such automated processing has previously been readily available for mouse or other widely used experimental animals, and most investigators use in-house custom processing. This protocol describes a stepwise method to perform such preprocessing for mouse.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1002/cpmb.40DOIArticle
http://onlinelibrary.wiley.com/doi/10.1002/cpmb.40/abstractPublisherArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195809PubMed CentralArticle
Additional Information:© 2017 John Wiley & Sons, Inc. Published Online: 5 JUL 2017. This work was funded by The Harvey Family Endowment (E.L.B.), MH096093 (E.L.B.), NIGMS (P50GM085273) (E.L.B.), NIDA (DA018184) (Russel E. Jacobs with sub-award to E.L.B.), and NINDS (NS046810, and NS062184) (E.L.B.). We are indebted to Russell E. Jacobs and the Beckman Institute Imaging Center at Caltech for access to the 11.7 MR scanner, the images, the template image, and the modal scaling code, as well as advice and coaching for over a dozen years on MR technology. We also gratefully acknowledge UNM's BA-MD program for support of Christopher Medina. We thank Kevin P. Reagan, Sharon Wu Lin, and XiaoWei Zhang for technical assistance, Krish Subramaniam for the modal scaling program, and current and former student helpers Brianna S. Mulligan, Amber Jean Zimmerman, Abdul Faheem Mohed, Adam Mitchell, Adam Delora, and Frances Chaves. The authors report no conflicts of interest.
Funders:
Funding AgencyGrant Number
Harvey Family EndowmentUNSPECIFIED
NIHMH096093
NIHP50GM085273
NIHDA018184
NIHNS046810
NIHNS062184
Subject Keywords:magnetic resonance imaging (MRI);manganese-enhanced magnetic resonance imaging (MEMRI);computational analysis and preprocessing; mouse and rodent brain; phenotyping brain anatomy
PubMed Central ID:PMC6195809
Record Number:CaltechAUTHORS:20170710-083149452
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170710-083149452
Official Citation:Medina, C. S., Manifold-Wheeler, B., Gonzales, A., & Bearer, E. L. (2017). Automated computational processing of 3-D MR images of mouse brain for phenotyping of living animals. Current Protocols in Molecular Biology, 119, 29A.5.1–29A.5.38. doi: 10.1002/cpmb.40
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:78881
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:10 Jul 2017 16:54
Last Modified:03 Oct 2019 18:13

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