Active Brain & Nervous System Bones, Joints & Muscles

Muscle ultrasound-derived fasciculation characterisation as a marker of MND progression

In plain English

AI plain-English summary

A simple, pain-free ultrasound scan could help doctors spot motor neurone disease (MND) earlier and track its progression more accurately. MND destroys the nerve cells that control movement, leading to muscle wasting and paralysis. Currently, diagnosing the disease and monitoring its advance relies on clinical exams and electrical tests that can be uncomfortable and miss subtle early changes. The researchers have already built software that automatically detects tiny, involuntary muscle twitches—called fasciculations—in ultrasound video recordings. They now aim to turn this into a clinical tool that gives a clear, easy-to-read score of muscle health. If successful, the tool could allow doctors to diagnose MND months earlier, when potential treatments might still slow the disease. It would also make clinical trials faster and cheaper: because the ultrasound measure is more sensitive than current methods, fewer participants would be needed to detect whether a drug is working. That could speed up the discovery of effective treatments for a disease that currently has no cure.

View original technical description
We aim to develop a sensitive and pain-free way of monitoring muscle health in MND that will make it easier to diagnose MND earlier. Then, when treatments become available, people can start them before the disease has affected them too much. Improving how sensitively we measure muscle health will also mean fewer people would need to take part in treatment trials, because the effects of the treatment would be spotted more easily. This would make trials faster and cheaper and speed up treatment discovery. Changes in muscle cause the physical problems in MND. Recording videos of muscles using ultrasound imaging reveals important changes in their health. We have already begun developing software that automatically detects some changes and propose developing this into a tool that will give a simple and easy to interpret readout that would help clinicians to diagnose MND sooner and assess the effects of new MND treatments.

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Researchers

Adrian Davison (Co-Investigator)Amina Chaouch (Co-Investigator)Emma Hodson-Tole (Principal Investigator)Moi Hoon Yap (Co-Investigator)

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Original classification

Research and Innovation

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