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Updated: Jan 11, 2026
Utilizing 3D Printing Technology to Merge MRI with Histology: A Protocol for Brain Sectioning
Published on: December 6, 2016
Do it yourself: Creating 3D brain-surface models and custom-made brain matrices for guided sectioning using
Sophie Holtz1, Julio Hechavarria2, Mirjam Knörnschild3
1Institute of Biology, Freie Universität Berlin, Takustraße 6, Berlin 14195, Germany; Max Planck School of Cognition, Stephanstrasse 1a, Leipzig, Germany.
Background:
Neuroethologists study many non-model animals. The development of techniques for precise and standardized histological brain analysis is key for understanding neural mechanisms across species.
New Method:
Here we present a novel cost-effective approach to generate species-specific brain matrices for precise and reproducible trimming, blocking, and sectioning of brain tissue. To produce the matrix, we took high-quality photographs of two male CP brains and then used the open-source 3D graphics suite Blender and its inexpensive photogrammetry plug-in SnapMesh to generate the 3D brain surface model. The brain matrix was then modeled in Blender, and 3D printed.
Results:
Using this approach, we produced the first 3D brain surface model and brain matrix for Seba's short-tailed fruit bat Carollia perspicillata, CP, and assessed its quality using CP brains. Our brain matrix facilitates and standardizes trimming or blocking of brains, providing consistent access to brain regions of CP in the sagittal and coronal planes. This workflow should be suitable for most vertebrate brains.
Comparison With Existing Methods:
Photogrammetry offers a viable, inexpensive alternative to 3D- or CT-scanners. Our workflow is not only cheaper than alternatives, but does not require blocking the brain during preparation of the 3D surface model, resulting in no tissue loss.
Conclusion:
The cost-effectiveness and the tissue-preserving features will benefit researchers globally, particularly those with limited financial means and/or few valuable specimens. By providing an accessible, customizable and reproducible workflow, our study represents a significant step toward democratizing advanced neuroscience across diverse species.
