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A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla. Sci Data 2023 Feb 14;10(1):94



Pubmed ID


Pubmed Central ID




Scopus ID

2-s2.0-85148086939 (requires institutional sign-in at Scopus site)


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.

Author List

Rahman N, Xu K, Budde MD, Brown A, Baron CA


Matthew Budde PhD Associate Professor in the Neurosurgery department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Diffusion Magnetic Resonance Imaging
Magnetic Resonance Imaging
Mice, Inbred C57BL
Sensitivity and Specificity