New AI tool to track efficacy of multiple sclerosis treatments

IANS April 7, 2025 253 views

Researchers at University College London have developed a groundbreaking AI tool called MindGlide that can rapidly analyze brain images for multiple sclerosis patients. The technology can process complex MRI scans in just 5-10 seconds, detecting subtle brain changes that were previously impossible to identify. MindGlide has been tested on over 14,000 images from more than 1,000 patients, demonstrating remarkable accuracy in tracking disease progression. This innovation promises to transform how medical professionals understand and treat multiple sclerosis by unlocking valuable insights from existing medical imaging data.

"We hope that the tool will unlock valuable information from millions of untapped brain images" - Dr. Philipp Goebl, UCL
New AI tool to track efficacy of multiple sclerosis treatments
New Delhi, April 7: UK researchers have developed a new artificial intelligence (AI) tool that can help interpret and assess how well treatments are working for patients with multiple sclerosis (MS).

Key Points

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Innovative AI tool MindGlide analyzes complex brain MRI scans in seconds

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Processes over 14,000 images from 1,000 MS patients

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Identifies brain tissue changes with unprecedented accuracy

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Enables deeper understanding of treatment effectiveness

MS is a condition where the immune system attacks the brain and spinal cord. This causes problems in how a person moves, feels or thinks.

The AI tool, called MindGlide, developed by researchers from the University College London (UCL) uses mathematical models to train computers by using massive amounts of data to learn. It solves problems in ways that can seem human, including how to perform complex tasks like image recognition.

MindGlide can extract key information from brain images (MRI scans) acquired during the care of MS patients, such as measuring damaged areas of the brain and highlighting subtle changes such as brain shrinkage and plaques.

While MRI markers are crucial for studying and testing treatments for MS, measuring them needs specialised scans, limiting the effectiveness of many routine hospital scans.

"We hope that the tool will unlock valuable information from millions of untapped brain images that were previously difficult or impossible to understand, immediately leading to valuable insights into multiple sclerosis for researchers and, in the near future, to better understand a patient's condition through AI in the clinic. We hope this will be possible in the next five to 10 years," said Dr. Philipp Goebl from UCL’s Queen Square Institute of Neurology.

In the new study, published in the journal Nature Communications, researchers tested the effectiveness of MindGlide on over 14,000 images from more than 1,000 patients with MS.

MindGlide was able to successfully use AI to detect how different treatments affected disease progression in clinical trials and routine care, using images that could not previously be analysed and routine MRI scan images. The process took just five to 10 seconds per image.

"Using MindGlide will enable us to use existing brain images in hospital archives to better understand multiple sclerosis and how treatment affects the brain,” Goebl added.

The results from the study show that it is possible to use MindGlide to accurately identify and measure important brain tissues and lesions even with limited MRI data and single types of scans that aren't usually used for this purpose -- such as T2-weighted MRI without FLAIR -- a type of scan that highlights fluids in the body but still contains bright signals -- making it harder to see plaques.

As well as performing better at detecting changes in the brain's outer layer, MindGlide also performed well in deeper brain areas.

The findings were valid and reliable both at one point in time and over longer periods (that is., at annual scans attended by patients).

In addition, MindGlide was able to corroborate previous high-quality research regarding which treatments were most effective.

Reader Comments

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Sarah K.
This is incredible progress for MS research! My aunt has MS and getting accurate treatment assessments has always been a challenge. The fact that it can analyze routine scans in seconds is mind-blowing 🤯 Hope this gets implemented worldwide soon!
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James T.
While the technology sounds promising, I wonder about data privacy concerns. Who will have access to these brain images and AI analyses? The article doesn't mention any safeguards. Important to consider as we advance medical AI.
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Miguel R.
As someone in the neurology field, this could be a game-changer for clinical trials. Analyzing 14,000 images manually takes forever - 10 seconds per scan is revolutionary. Kudos to the UCL team!
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Anika P.
The name "MindGlide" is so fitting! Love seeing AI being used for good like this. My only concern is whether smaller hospitals will be able to afford this tech - hope it doesn't create disparities in care quality.
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Trevor L.
Interesting read, but the article could've explained more about how exactly the AI detects changes. Is it looking at specific biomarkers? How does it differentiate between normal aging and MS progression?
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Emma S.
Five to ten years seems like a long wait when this could help people now. Are there plans for accelerated approval pathways? MS patients deserve access to the best diagnostic tools asap 💜

We welcome thoughtful discussions from our readers. Please keep comments respectful and on-topic.

Tags:
Multiple Sclerosis AI Healthcare Medical Technology Brain Imaging UCL Research Dr. Philipp Goebl
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