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Scattered Light Imaging Can Map Tissue Fibers at Micron Resolution

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STANFORD, Calif., Nov. 13, 2025 — The billions of nerve fibers in the brain form a dense network that controls neuronal function and connectivity. The degeneration of these fiber networks causes disruptions in neural connectivity, leading to neurological disorders.

Detailed mapping of neuronal networks is a major goal of neuroscience, but remains difficult to achieve at μm resolution and over a large FOV.

A technique developed at Stanford Medicine, in collaboration with international institutions, enables microscopic visualization of the orientation and organization of fibers in the brain and other tissues.

The new method, called computational scattered light imaging (ComSLI), exploits a principle of physics — that is, light scatters differently depending on the orientation of the microscopic structures through which it passes. By rotating the direction of the light and recording how the scattering changes, ComSLI can reconstruct the direction of the tissue fibers within each microscopic pixel, across the entire image.

Computational scattered light imaging (ComSLI) shows the orientation and organization of tissue fibers at µm resolution. The colors represent different fiber orientations. Courtesy of Stanford University/Marios Georgiadis.
Computational scattered light imaging (ComSLI) shows the orientation and organization of tissue fibers at μm resolution. The colors represent different fiber orientations. Courtesy of Stanford University/Marios Georgiadis. 

“The information about tissue structures has always been there, hidden in plain sight,” researcher Marios Georgiadis said. “ComSLI simply gives us a way to see that information and map it out.”

ComSLI uses a directed, rotating LED light source and a high-resolution camera to enhance signal to noise ratio. It uses software algorithms to analyze the patterns in the scattered light. The results of the analysis are used to produce color-coded maps, known as microstructure-informed fiber orientation distributions, that show the orientation and density of fibers within the sample.

The researchers showed that ComSLI, a highly versatile technique, can retrieve microscopic fiber orientations across different species, diseases, and tissue types, in new and archived histology sections, in samples prepared with various stains and protocols, in fresh-frozen and unstained samples, and at different steps of sample preparation. Using ComSLI, they visualized entire formalin-fixed, paraffin-embedded (FFPE) human brain sections, as well as standard-sized slides.

The team used ComSLI to reconstruct fiber microarchitecture in healthy and diseased brain tissue samples. ComSLI discerned myelin from axonal loss, revealed microstructural alterations in multiple sclerosis and leukoencephalopathy samples, and identified degeneration of the perforant pathway in sclerotic and Alzheimer’s disease hippocampus tissue.

To show that ComSLI can be applied to any slide, regardless of preparation or length of storage, the researchers imaged a brain section prepared in 1904. ComSLI revealed intricate fiber pathways in the sample, demonstrating its potential as a tool to study historical samples and trace the lineage of a disease.

The researchers also demonstrated the use of ComSLI on muscle, bone, and vascular samples, each with distinct fiber patterns related to their physiological roles. Although originally developed for neuroimaging, ComSLI proved effective for mapping fiber orientations in other types of tissues.

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The setup requires only an LED spot, a sample stage, and a μm-resolution camera, making ComSLI a relatively cost-effective technique. ComSLI can complete a full measurement in seconds, and is compatible with sections prepared using virtually any protocol. It allows mapping of microscopic fiber architectures in various types of histological samples, including FFPE samples, which are used in laboratories worldwide.

In miniaturized form, using an LED-ring instead of a rotating LED, ComSLI could be an add-on to existing microscopes and easily integrated into clinical workflows, enabling microscopic exploration of fiber orientations on sections readily available in thousands of laboratories and clinics.

Researchers can even use ComSLI to extract structural information from tissue without additional processing, by re-analyzing slides originally made for other purposes, including slides that have been stored for decades.

“This is a tool that any lab can use,” professor Michael Zeineh, MD, said. “You don’t need specialized preparation or expensive equipment. What excites me most is that this approach opens the door for anyone, from small research labs to pathology labs, to uncover new insights from slides they already have.”

This fast, easy-to-implement, low-cost technique could become a routine tool for mapping fiber orientation of histological sections, opening new ways to investigate the microarchitecture of healthy and diseased tissues. The ability to map fiber orientation in various species, organs, and decades-old specimens could reshape how scientists approach questions of organ structure and function. It could also transform millions of archived slides worldwide into potential sources of new data.

“Although we just presented the method, there are already multiple requests for scanning samples and replicating the ComSLI setup — so many labs and clinics would like to have micron-resolution fiber orientation and micro-connectivity on their histology sections,” Georgiadis said. “Another exciting plan is to go back to well-characterized brain archives or brain sections of famous people, and recover this micro-connectivity information, revealing ‘secrets’ that have been considered long lost. This is the beauty of ComSLI.”

The research was published in Nature Communications (www.doi.org/10.1038/s41467-025-64896-9).

Published: November 2025
Research & TechnologyeducationAmericasStanford UniversityStanford MedicineImagingbrain imagingMicroscopyLEDsLight Sourceslight scatteringOpticscamerasBiophotonicsmedicalmedicineneurodegenerative diseases

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