Prof. Aviv Metzer is developing a new generation of quantitative magnetic resonance imaging, which aims to measure microscopic changes in myelin and the water environment in the tissue, and provide doctors with a more precise tool for understanding damage and examining treatments that encourage remyelination.
Prof. Aviv Metzer, a brain imaging researcher at the Edmond and Lily Safra Center for Neuroscience at the Hebrew University, wants to take one of the most familiar tools in medicine—the MRI scan—and give it a “role upgrade.” Instead of an impressive but mostly high-quality image, he aims to turn it into a precise measurement tool that manages to capture tiny processes occurring within tissue.
This is the heart of the National Science Foundation-supported research: turning a signal that originates from the microscopic into a quantitative map of the brain. As Matzer explains, “Usually you see large changes, for example in the case of multiple sclerosis you can identify large lesions – macroscopic. But the source of his signal is not macroscopic but microscopic – the delicate interactions between water molecules and their environment.”
The question is: How do we turn MRI into an accurate measurement tool that captures tiny processes occurring within tissue?
From “a beautiful picture” to “a physical map”"
The research is based on a basic understanding: MRI essentially measures the behavior of water molecules in tissue. But water doesn’t “float in the air”—it’s constantly interacting with its environment: with myelin layers, with proteins, with iron, and other components. In this sense, water molecules are a kind of “natural sensors” that are everywhere, and MRI is the way to read the signal they leave.
Instead of an MRI image that depends on the device settings and the operator, quantitative MRI or qMRI provides physical numbers: Time it takes for protons in water to return to a magnetic rest state after the device “disturbs” them, water volumes in sub-divisions, and metrics that can be compared between people and between scans. “It’s not a picture anymore – it becomes a map,” says Metzer.
The biophysical goal is to build models that interpret the behavior of water like a “fingerprint”: Is the water in an environment rich in myelin? Is the myelin dense and tight or rather loose and damaged? As Matzer puts it: “We want to turn MRI into a kind of precise sensor. The product resembles microscopy. It’s a concept called in vivo histology.”
"Like an electrical wire without insulation."
Why is this so important? The prime example is multiple sclerosis, a disease in which the immune system attacks the “white matter” pathways in the brain and spinal cord. The axons—the “wires” that transmit electrical signals between nerve cells—are coated in a fatty insulating layer called myelin. “Like an electrical wire is wrapped in a layer of insulation,” Metzer describes, “and in multiple sclerosis the immune system attacks that sheath.”
The uniqueness of the disease lies in its dynamics: there is an episodic-remitting phase in which the damage comes and goes, sometimes with partial repair (remyelination – rebuilding of the myelin). But in the advanced, progressive phase, the damage is already so great that repair is ineffective, and the damage becomes permanent.
In the medical world, treatments are being developed that try to improve or induce remyelination—one of the biggest problems for them is measurement. “It’s hard to test them in humans… You can test their success by changing symptoms… which is very indirect,” explains Metzer.
This is precisely where he wants to introduce a new “marker”: not a functional test or a subjective assessment, but an index that relates to the structure itself – how “tight” the myelin is, and what water subenvironments exist at each point in the tissue.
In the medical world, treatments are being developed that attempt to improve or stimulate remyelination (rebuilding myelin) in multiple sclerosis patients. One of the biggest problems is measurement.
How do you check that the index really works??
The research is progressing in stages. First, a mathematical-physical model is being built that describes how changes in the myelin structure should affect the behavior of water molecules and the signal measured in MRI.
The model is then tested on “phantoms” – controlled laboratory models that simulate tissue, in which parameters such as the density or “tightening” of the myelin can be changed in a known way. If the quantitative index is able to identify the known change, we move on to the next stage. These research stages are led by Dr. Rona Shahrabani, a researcher at the Metzer Laboratory and director of the MRI unit at the Safra Institute for Brain Research at the Hebrew University.
The research includes two different technical directions: one based on Magnetization Transfer and one based on 2T, each “telling” something slightly different about the microscopic environment, and together they should provide a complementary picture.
Finally comes the reality test: scans of healthy and sick subjects. The experiment is planned to be done in collaboration with Dr. Michal Cohen of Shaarei Tzedek and Prof. Paul Friedemann of the Charité Hospital in Berlin. At the same time, there will be an animal test: a model of myelin damage scanned at Tel Aviv University by Prof. Ben Elazar and Prof. Frankel, which can be directly compared to real histology—that is, to microscopic staining of the tissue.
Why does it matter??
Metzer emphasizes that the research is not “drug development” but rather the creation of a basic measurement tool: “This is basic research with the aim of generating knowledge for the world of medicine and brain research, not just for multiple sclerosis. Success in the project will also benefit researchers of aging, development, and other brain conditions related to the white matter in the brain. We are creating something that will be in the public domain.”
In a world where treatments are increasingly advanced—especially treatments that aim for rehabilitation and not just slowing down—a good measuring tool can be the difference between a clinical trial that “looks promising” and a treatment that is proven to change the nature of the disease.
Metzer also points to another challenge: understanding in advance who a particular treatment is likely to help and who it won't, so as not to "fail" a trial of a good drug on the wrong measure. In other words: if we know how to better measure what is really happening in the tissue, we can also treat better.
More of the topic in Hayadan:
