Tractography from Serial Optical Coherence Tomography: How and Why?
Year: 2026
Type: preprint
Abstract: ABSTRACT To disentangle complex fiber configurations that remain challenging for diffusion MRI tractography, insights might be gained from microscopy tractography. By precisely following small white matter (WM) fascicles, invisible at the resolution of diffusion MRI, microscopy tractography can help explain how fiber populations are organized at the finest scales. Due to its high resolution and its 3D nature, serial optical coherence tomography (S-OCT) offers promise for studying WM at the microscale. However, whether the reflectivity contrast from S-OCT supports tractography at the microscale is unknown. Furthermore, there is a gap in the literature regarding how an ideal microscopy tractography should behave with respect to the choice of tractography algorithm, tracking maps and microscale orientation distribution functions (µODF) estimation. In this work, we describe a tailored approach for microscopy tractography from S-OCT acquisitions. We validate our approach on a simulated microscopy-like FiberCup dataset, and show that multiscale Frangi filters outperforms structure tensor analysis for estimating µODF. We also show that anatomically-constrained particle filtering tractography enables targeted, region-toregion tractography, and outperforms standard deterministic or probabilistic tracking approaches. We further demonstrate our method on an ex vivo whole mouse brain S-OCT reconstruction at 10 µm by reconstructing thalamocortical WM projections. Overall, our results show that SOCT tractography recovers fine WM fascicles that are supported by viral tracing experiments from the Allen Mouse Brain Connectivity Atlas. Moreover, this work shows the first µODF estimation and fully-3D probabilistic particle filtering tractography of the mouse brain from SOCT reconstructions at 10 µm isotropic resolution.
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7203740207