Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation
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Brain volume measurements extracted from structural MRI data sets are a widely-accepted neuroimaging biomarker to study mouse models of neurodegeneration. Whether to acquire and analyse data in vivo or ex vivo is a crucial decision during the phase of experimental designs, as well as data analysis. In this work, we extracted the brain structures for both longitudinal in vivo and single-time-point ex vivo MRI acquired from the same animals using accurate automatic multi-atlas structural parcellation, and compared the corresponding statistical and classification analysis. We found that most grey matter structures volumes decrease from in vivo to ex vivo, while most white matter structures volume increase. The level of structural volume change also varies between different genetic strains and treatment. In addition, we showed superior statistical and classification power of ex vivo data compared to the in vivo data, even after resampled to the same level of resolution. We further demonstrated that the classification power of the in vivo data can be improved by incorporating longitudinal information, which is not possible for ex vivo data. In conclusion, this paper demonstrates the tissue-specific changes, as well as the difference in statistical and classification power, between the volumetric analysis based on the in vivo and ex vivo structural MRI data. Our results emphasise the importance of longitudinal analysis for in vivo data analysis.
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Previous DTI studies assessing microstructural changes in rTg4510 mice produced conflicting results.
“Previous DTI studies assessing microstructural changes in rTg4510 mice, which express transgenic tau P301L mutations driven by a Ca 2+ / calmodulin kinase II promoter system [30,31] in the white and grey matter produced conflicting results [33][34][35][36].”
From Diffusion tensor imaging reveals whole-brain microstructural changes in the P301L mouse model of tauopathy. (2020) · cites this paper as [34]
The Introduction describes inconsistent findings about volume changes between in vivo and ex vivo imaging, not conflicting DTI findings in rTg4510 mice. The Experimental Data section identifies the mouse model, but neither it nor the additional passages retrieved for DTI and microstructural changes addresses the attributed claim. No page numbers were provided in our copy. (LLM, conf=0.76)
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Anesthesia‐related brain microstructure modulations detected by diffusion magnetic resonance imaging
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Fletcher, E. J. R., Finlay, C. J., López, A. A., Crum, W. R., Vernon, A. C., & Duty, S. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.567222 · Cited by 14 · see citing works
Dynamic Changes of Brain Networks during Working Memory Tasks in Schizophrenia
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Fernandes, D., Spring, S., Corre, C., Tu, A., Qiu, L. R., Hammill, C. F., Vousden, D. A., Noakes, T. L. S., Nieman, B. J., Bowdish, D. M. E., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01535-5 · Cited by 12 · see citing works
Magnetic Resonance Imaging in Tauopathy Animal Models
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To, X. V., Benetatos, J., Soni, N., Liu, D., Abraha, H. M., Yan, W., Panagiotopoulou, O., & Nasrallah, F. A. (2020) · Journal of Neurotrauma · doi:10.1089/neu.2019.6944 · Cited by 9 · see citing works
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Self-citationSantini, T., Shim, A., Liou, J., Rahman, N., Varela-Mattatall, G. E., Budde, M. D., Inoue, W., Everling, S., & Baron, C. A. (2024) · Magnetic Resonance in Medicine · doi:10.1002/mrm.30298 · Cited by 6 · see citing works
Knopper, R. W., Skoven, C. S., Eskildsen, S. F., Østergaard, L., & Hansen, B. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1498133 · Cited by 7 · see citing works
A cross‐comparative analysis of in vivo versus ex vivo MRI indices in a mouse model of concussion
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Impaired glymphatic transport in hypoxic-ischemic encephalopathy
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Self-citationA New Similarity Metric for Deformable Registration of MALDI–MS and MRI Images
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Deep learning-driven MRI for accurate brain volumetry in murine models of neurodegenerative diseases
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Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivityPreprint
Authier, F., Jan, A., Faress, I. M. G., Skoven, C. S., Esperon‐Abril, I., Balasubramaniam, S. T., Coquelin, K.-S., Nyengaard, J. R., Scavenius, C., Attianese, B., et al. (2025) · eLife · doi:10.7554/elife.107170 · Cited by 1 · see citing works
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Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivity
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Pathogenic O-GlcNAc dyshomeostasis associated with cortical malformations and hyperactivityPreprint
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Pathogenic O-GlcNAc dyshomeostasis is associated with cortical malformations and hyperactivityPreprint
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Morphometric Brain Changes in a Merino Sheep (Ovis aries) CLN6 Neuronal Ceroid Lipofuscinosis Model
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- Authors
- Ma, D., Holmes, H. E., Cardoso, M. J., Modat, M., Harrison, I. F., Powell, N. M., O’Callaghan, J. M., Ismail, O., Johnson, R. A., O’Neill, M. J., Collins, E. C., Beg, M. F., Popuri, K., Lythgoe, M. F., & Ourselin, S.
- Affiliations
- Simon Fraser University (CA)
- University College London (GB)
- King's College London (GB)
- Eli Lilly (United States) (US)
- Eli Lilly (United Kingdom) (GB)
- Corresponding author
- Ma, Da
- ORCID
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2019-01-24
- Volume
- 13
- Pages
- 11-11
- ISSN
- 1662-453X (ISSN-L)
- PMC
- PMC6354066
- OpenAlex
- W2914916753
- Cited by
- 36
- References
- 82
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 6 · 2023: 4 · 2022: 5 · 2021: 3 · 2020: 8 · 2019: 1 · 2018: 1
- FWCI
- 3.39
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Funders
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/K500276/1)
- Medical Research Council (MR/J500422/1, MR/G0900207-3/1, MR/J01107X/1, MR/K026739/1)
- Engineering and Physical Sciences Research Council (EP/H046410/1, EP/J020990/1, EP/K005278, 000012287)
- University College London (PR/ylr/18575)
- National Institute for Health Research (BW.mn.BRC10269)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- tauopathy, brain volume, gray matter volume, white matter volume, disease progression, treatment effects, longitudinal analysis, genetic strain differences
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