3D-Fiber Mapping in Biological Tissues with Computational Scattered Light Imaging Enabled Through 3D-Nanoprinting
TL;DR
This analytical model was able to estimate inclination angles of non-crossing fibers up to 60° inclination with an accuracy of 3° or better and finally allows to quantitatively determine fiber inclinations and reconstruct 3D fiber pathways with ComSLI.
Abstract
Computational Scattered Light Imaging (ComSLI) exploits the anisotropic scattering on aligned structures to reconstruct biological fiber networks like nerve, muscle or collagen fibers. ComSLI discerns individual fiber pathways also in densely interwoven regions with multiple crossing fibers, achieves micrometer resolution across centimeter fields of view, is compatible with various sample preparations and staining, and only requires an LED light source and a camera, making it attractive for histological tissue analysis. However, while ComSLI precisely determines the 2D (in-plane) fiber orientations, determining the 3D (out-of-plane) fiber inclinations remained challenging due to missing a-priori knowledge of the inclination angles. In this study, we measured differently inclined 3D-nanoprinted fiber bundles with ComSLI, compared the resulting scattering patterns to those obtained from nerve fibers in a tilted brain section (vervet corpus callosum), and analyzed scattering patterns and angular profiles in differently inclined brain regions. We show that the highest scattering intensity occurs along the same curved line as conical diffraction at an inclined grating. With this analytical model, we were able to estimate inclination angles of non-crossing fibers up to 60° inclination with an accuracy of 3° or better. This finally allows to quantitatively determine fiber inclinations and reconstruct 3D fiber pathways with ComSLI.