Journal articles

Virtual histology of an entire mouse brain from formalin fixation to paraffin embedding. Part 2: Volumetric strain fields and local contrast changes

Background: Fixation and embedding of post mortem brain tissue is a pre-requisite for both gold-standard conventional histology and X-ray virtual histology. This process alters the morphology and density of the brain microanatomy.

New method: To quantify these changes, we employed synchrotron radiation-based hard X-ray tomography with 3 μm voxel length to visualize the same mouse brain after fixation in 4% formalin, immersion in ethanol solutions (50%, 70%, 80%, 90%, and 100%), xylene, and finally after embedding in a paraffin block. The volumetric data were non-rigidly registered to the initial formalin-fixed state to align the microanatomy within the entire mouse brain.

Results: Volumetric strain fields were used to characterize local shrinkage, which was found to depend on the anatomical region and distance to external surface. X-ray contrast was altered and enhanced by preparation-induced inter-tissue density changes. The preparation step can be selected to highlight specific anatomical features. For example, fiber tract contrast is amplified in 100% ethanol.

Comparison with existing methods: Our method provides volumetric strain fields, unlike approaches based on feature-to-feature or volume measurements. Volumetric strain fields are produced by non-rigid registration, which is less labor-intensive and observer-dependent than volume change measurements based on manual segmentations. X-ray microtomography provides spatial resolution at least an order of magnitude higher than magnetic resonance microscopy, allowing for analysis of morphology and density changes within the brain’s microanatomy.

Conclusion: Our approach belongs to three-dimensional virtual histology with isotropic micrometer spatial resolution and therefore complements atlases based on a combination of magnetic resonance microscopy and optical micrographs of serial histological sections.

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Reference

G. Rodgers, W. Kuo, G. Schulz. M. Scheel, A. Migga, Ch. Bikis, Ch. Tanner, V. Kurtcuoglu, T. Weitkamp, B. Müller. Journal of Neuroscience Methods, 365, 109385 (2022). doi: 10.1016/j.jneumeth.2021.109385