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Updated: Aug 10, 2025
Multiple-mouse Neuroanatomical Magnetic Resonance Imaging
Published on: February 27, 2011
A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla
Naila Rahman1,2, Kathy Xu3, Matthew D Budde4
1Centre for Functional and Metabolic Mapping (CFMM), Robarts Research Institute, University of Western Ontario, London, Ontario, Canada. nrahma25@uwo.ca.
Abstract:
Multimodal microstructural MRI has shown increased sensitivity and specificity to changes in various brain disease and injury models in the preclinical setting. Here, we present an in vivo longitudinal dataset, including a subset of ex vivo data, acquired as control data and to investigate microstructural changes in the healthy mouse brain. The dataset consists of structural T2-weighted imaging, magnetization transfer ratio and saturation imaging, and advanced quantitative diffusion MRI (dMRI) methods. The dMRI methods include oscillating gradient spin echo (OGSE) dMRI and microscopic anisotropy (μA) dMRI, which provide additional insight by increasing sensitivity to smaller spatial scales and disentangling fiber orientation dispersion from true microstructural changes, respectively. The technical skills required to analyze microstructural MRI data are complex and include MRI sequence development, acquisition, and computational neuroimaging expertise. Here, we share unprocessed and preprocessed data, and scalar maps of quantitative MRI metrics. We envision utility of this dataset in the microstructural MRI field to develop and test biophysical models, methods that model temporal brain dynamics, and registration and preprocessing pipelines.
Insights
This study shares a multimodal microstructural MRI dataset of healthy mouse brains. The data aids in developing advanced neuroimaging analysis methods for brain research.
Area of Science:
- Neuroimaging
- Preclinical Research
- Mouse Models
Background:
- Multimodal microstructural MRI enhances sensitivity to brain changes in disease and injury models.
- Understanding healthy brain microstructural dynamics is crucial for interpreting disease-related alterations.
Purpose of the Study:
- To present a comprehensive in vivo longitudinal dataset of microstructural changes in the healthy mouse brain.
- To provide a valuable resource for developing and validating advanced neuroimaging analysis techniques.
Main Methods:
- Acquisition of multimodal microstructural MRI data, including T2-weighted imaging, magnetization transfer ratio, saturation imaging, and advanced quantitative diffusion MRI (dMRI).
- Utilized oscillating gradient spin echo (OGSE) dMRI for enhanced sensitivity to small spatial scales.
- Employed microscopic anisotropy (μA) dMRI to differentiate fiber orientation dispersion from microstructural changes.
Main Results:
- A shared dataset comprising unprocessed and preprocessed data, along with scalar maps of quantitative MRI metrics.
- The dataset includes in vivo longitudinal data and a subset of ex vivo data for comprehensive analysis.
- Demonstrated advanced dMRI techniques for detailed microstructural characterization.
Conclusions:
- The shared dataset is a valuable resource for the microstructural MRI field.
- Facilitates the development and testing of biophysical models and computational neuroimaging pipelines.
- Aids in the advancement of methods for modeling temporal brain dynamics and improving registration/preprocessing techniques.
