Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework

Area of Science:

• Neuroimaging
• Biomedical Engineering
• Histology

Background:

• High-resolution magnetic resonance imaging (MRI) offers non-destructive tissue microstructure analysis.
• Direct comparison of MRI metrics with conventional histology is challenging due to resolution and contrast differences.
• Accurate validation is essential for interpreting MRI-derived contrasts.

Purpose of the Study:

• To validate various MRI metrics against histological data at high resolution.
• To integrate multimodal and multiscale brain imaging datasets within a common 3D framework.
• To improve the understanding of brain complexity by correlating different imaging modalities.

Main Methods:

• Acquisition of whole mouse brain multigradient recalled-echo and multishell diffusion MRI at 25-μm isotropic resolution.
• Utilizing the Allen Mouse Brain Common Coordinate Framework (CCFv3) for spatial integration.
• Comparison of MRI parameters (T2*, QSM, DTI, NODDI) with serial two-photon tomography and 3D Nissl staining images.

Main Results:

• Demonstrated strong correlations between MRI metrics and Nissl staining, varying by metric and brain region.
• Achieved comparable spatial resolution (25-μm) for multimodal image analysis.
• Established a framework for integrating diverse neuroimaging datasets.

Conclusions:

• The correlation between MRI and Nissl staining is metric- and region-dependent.
• Integrating multimodal imaging data into a common 3D space enhances brain complexity understanding.
• High-resolution MRI validation with histology is feasible and informative for neurobiological research.