Breakthrough in Mapping Brain's Nerve Fiber Labyrinth

Delft University of Technology

In order to understand brain diseases, neuroscientists try to untangle the intricate nerve fibre labyrinth of our brain. Before analysing brain tissue under a microscope, it is often soaked in paraffin wax to achieve high-quality sections. However, accurately mapping the densely packed nerves inside wax-treated brain slices was so far not possible. Researchers from Delft, Stanford, Jülich, and Rotterdam achieved a milestone: using a technique called ComSLI, they enable fibre mapping inside any tissue section with micrometre precision. The findings are published in Nature Communications.

Studying the network of neurons in the brain helps to understand brain diseases such as Alzheimer's or Parkinson's disease. To analyse the detailed anatomy under a microscope, the tissue is often embedded in paraffin wax and cut into micrometre-thin slices. These so-called formalin-fixed paraffin-embedded (FFPE) sections are the gold standard for studying healthy or diseased tissues. However, current microscopy techniques cannot accurately map large nerve fibre networks in these FFPE sections.

First-ever technique

Over the last years, physicist Miriam Menzel has developed a technique called Computational scattered light imaging (ComSLI) for disentangling nerve fibre networks. Now, her invention turns out to be the first-ever technique that can map dense nerve fibres in FFPE sections with micrometre precision and over large areas.

All-rounder tool

Together with Marios Georgiadis from the Stanford University and other colleagues from Delft, Stanford, Jülich, and Rotterdam, Menzel showed that ComSLI reveals the nerve fibre network in any thin tissue section, also in brain slices treated with paraffin wax. "Our technique works on all sections that are commonly used for microscopic analysis: new or century-old, unstained or stained, fresh-frozen or fixated, at different steps of sample preparation", Menzel explains. "It can be retrospectively applied to any archived section of which thousands are available in laboratories worldwide."

Human brain atlas

One prominent example is the BigBrain , a human brain atlas based on thousands of FFPE sections with stained cell bodies. It shows the brain's anatomy in 3D and users can zoom in on any part of the brain in microscopic detail. The researchers measured original tissues from the atlas with ComSLI. They were able to visualise the intricate nerve fibre network in addition to the cell bodies – something that was not possible before.

Easy add-on

ComSLI requires only an LED light and a high-resolution camera, making it a simple and cost-effective tool. "Other research or clinical laboratories can easily realise our technique, also as add-on to existing microscopes", Menzel says.

Neurological disorders

The researchers were not only able to correctly map fibre pathways in healthy tissues, but also in neurodegenerated brain samples with multiple sclerosis, Alzheimer's disease, and leukoencephalopathy. This makes ComSLI ideal for studying neurological and psychiatric disorders.

Cancer diagnostics

But ComSLI is not restricted to brain research. Menzel: "We found that the technique also makes other fibrous structures visible, like muscle or collagen fibres. And it can be applied to fresh-frozen sections, which enables tissue assessment during surgeries." In this way, ComSLI could even improve cancer diagnostics by studying the organisation of collagen fibres at tumour boundaries.

This study results from a collaboration between the Menzel Lab at TU Delft, Stanford University, Forschungszentrum Jülich, and Erasmus MC in Rotterdam. Parts of the study were supported by the Convergence Imaging Facility and Innovation Centre (CIFIC) Flagship.

Imaging Physics

Delft University of Technology has a long history in imaging technologies. The Imaging Physics department serves as a hub for physics-driven innovation in imaging technologies and instrumentation. It is at the forefront of developing new imaging tools and methods for healthcare and the digital society.

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