Integrating Multimodality MRI to Allen Mouse Brain Common Coordinate Framework (CCFv3).
Nian WangSurendra MaharjanAndy P TsaiPeter B LinYi QiAbigail WallaceMegan JewettFang LiuGary E LandrethAdrian L OblakPublished in: NMR in biomedicine (2022)
High-resolution MRI affords unique image contrasts to non-destructively probe the tissue microstructure, validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impede the accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multi-gradient recalled-echo (MGRE) and multi-shell diffusion MRI datasets at 25 μm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common 3D space. The T2*, quantitative susceptibility mapping (QSM), diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) parameters were compared with both serial two-photon (STP) tomography images and 3D Nissl staining images in CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.
Keyphrases
- contrast enhanced
- high resolution
- magnetic resonance imaging
- diffusion weighted imaging
- diffusion weighted
- white matter
- deep learning
- magnetic resonance
- computed tomography
- machine learning
- optical coherence tomography
- multiple sclerosis
- quantum dots
- convolutional neural network
- functional connectivity
- living cells
- brain injury