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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
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A relaxation-diffusion MRI dataset of aging mouse brains at 9.4 Tesla
Baoxing Ren1,2, Ye Wu3, Yan Liu1,2
1School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.
Scientific Data
|November 17, 2025
Summary
This study presents a new relaxation-diffusion MRI (rdMRI) dataset of aging mouse brains. This valuable resource aids in developing advanced MRI techniques for preclinical research and understanding brain aging.
Area of Science:
- Neuroimaging
- Biomedical Engineering
- Gerontology
Background:
- Relaxation-diffusion MRI (rdMRI) offers advanced insights into tissue microstructure by separating relaxation and diffusion effects.
- Limited availability of rdMRI datasets in preclinical mouse models hinders research into complex biological processes and aging.
Purpose of the Study:
- To present a novel, high-quality in-vivo rdMRI dataset of aging mouse brains.
- To facilitate the validation and optimization of rdMRI techniques in a preclinical setting.
- To provide a resource for investigating age-related structural brain changes.
Main Methods:
- Acquisition of rdMRI data from five age groups of mice (n=6 per group) using a 9.4T ultra-high field MRI scanner.
- Data collection across 5 echo times (TEs) with multi-shell diffusion scans at each TE.
- Rigorous data processing via a specialized pipeline with systematic quality control.
Main Results:
- Generation of a comprehensive, high-quality in-vivo rdMRI dataset of aging mouse brains.
- Ensured data reliability through meticulous processing and quality control measures.
Conclusions:
- The presented dataset serves as a foundational resource for advancing rdMRI methodology.
- This dataset will accelerate research into age-related structural alterations in the mouse brain, supporting preclinical studies.
