Robot Arthur in UK-first for hand arthritis scans

From bbc.co.uk/news

A robot is being used for the first time in the UK to scan patients' hands and wrists to speed up rheumatoid arthritis diagnosis.

Arthur, at the Royal Berkshire Hospital in Reading scans while AI program Diana interprets the images and sends the results to clinicians so patients get a treatment plan the same day.

Professor Antoni Chan, consultant rheumatologist and physician said: "We are delighted to be the first site in the UK to use Arthur. Earlier diagnosis is very important as joint damage can occur if treatment is delayed."

By using the robot, the hospital hopes to increase patients and offer those with rheumatoid arthritis more frequent scans so their treatment can be monitored.

Royal Berkshire NHS Foundation Trust

James Blythe, chief executive officer at the trust said: "There are seven countries around the world that use this technology and we are the first place in the UK to bring it on stream.

"This investment is about using technology to deliver real improvements for our patients and colleagues.

"It means we can get to patients earlier and make interventions that add years to life and life to years."

Royal Berkshire NHS Foundation Trust (RBFT) said its rheumatology department in Reading currently carries out 200 hand MRIs a year with demand for their services rising every year.

Prof Chan said: "We can see patients on the day of the clinic they can have the scans and then we can make a decision - this does not replace clinician this helps the decision making and then we can proceed with treatment.

"It really improves the time to diagnose so we don't delay treatment."

The trust said the robot forms part of the wider work taking place across RBFT to invest in technology.

It said other examples included recent investment in new pharmacy dispensing robots, and our work with AI in the to speed up the diagnosis of patients who have had a stroke.

https://www.bbc.co.uk/news/articles/cx98z65zj775o 

Why rheumatoid arthritis pain may persist even when inflammation is under control

From sciencedaily.com

Pain and fatigue in rheumatoid arthritis can persist even after inflammation improves, with depression, poor sleep, obesity, smoking, and chronic pain potentially helping sustain symptoms. Researchers say identifying these hidden drivers could prevent unnecessary medication changes and lead to more personalized treatment

Researchers at Semmelweis University say persistent rheumatic symptoms may be driven by more than inflammation alone. Sleep disorders, depression, obesity, smoking, and other health problems may also help keep symptoms going. In publications in Nature Reviews Rheumatology and The Lancet Rheumatology, the team also introduced a model designed to help doctors identify the underlying causes of symptoms earlier and tailor treatment more effectively.

The researchers examined how depression, smoking, obesity, sleep problems, and other health conditions are connected with difficult-to-treat rheumatoid arthritis.

Rheumatoid arthritis is a chronic autoimmune disease in which the immune system mistakenly attacks the joints, leading to pain, swelling, and stiffness. In Hungary alone, it affects tens of thousands of people. Most patients respond well to treatment, but 6-28 percent fall into the so-called "difficult-to-treat" group because they do not achieve lasting remission despite therapy.

According to the studies in Nature Reviews Rheumatology and The Lancet Rheumatology, these additional health problems may do more than simply occur alongside rheumatoid arthritis. They may also contribute to keeping symptoms active.

Rheumatoid arthritis pain may sometimes persist because of hidden cycles involving sleep, depression, obesity, smoking, and chronic pain, not inflammation alone. Credit: Shutterstock

A Vicious Cycle of Pain, Mood, and Sleep

Pain and depression, for example, can reduce physical activity, contribute to weight gain, and worsen both sleep and mood. Those changes can then intensify pain and make daily activities more difficult, creating a difficult-to-break "vicious cycle."

The researchers also developed a new model that could improve care for patients whose rheumatoid arthritis remains difficult to manage. Under the widely used "treat-to-target" approach, doctors regularly track measurable indicators of disease activity. If inflammation is not reduced enough, treatment is adjusted, such as by increasing the medication dose or switching to another drug.

The team argues that this same approach can also serve as a kind of "early warning system." If measurable signs of inflammation improve but symptoms remain, that may indicate the pain or fatigue is not being caused solely, or perhaps at all, by ongoing inflammation.

Looking Beyond Inflammation

"When target values improve but the patient still suffers from pain and fatigue, it is worth taking a step back. In such cases, instead of automatically prescribing more medication, doctors should look for what is maintaining the symptoms - whether it is chronic pain syndrome, depression, sleep disorders, or obesity," said Dr. György Nagy, head of the Department of Rheumatology and Immunology at Semmelweis University.

The researchers say they have seen this approach improve outcomes in difficult-to-treat patients. In many cases, it may also strengthen the doctor-patient relationship by focusing treatment more closely on what is actually driving the patient's symptoms.

A Model With Growing International Influence

The team's model has gained substantial international attention. Publications that introduced the concept of "difficult-to-treat" disease and the related treatment strategy have already been cited more than a thousand times by other researchers.

The definition is now used worldwide not only for rheumatoid arthritis, but also in discussions of other diseases.

AI Could Help Personalize Treatment

The researchers are now looking toward the next stage of the work. Alongside their own studies, they plan to participate in projects that use artificial intelligence to develop more effective treatments for people with rheumatoid arthritis.

"With AI-based pattern recognition, we could identify subgroups among patients, and with the help of these data we could create more effective, almost personalized treatment strategies for them," explained Dr. Lilla Gunkl-Tóth, PhD student at Semmelweis University and first author of the publications.

https://www.sciencedaily.com/releases/2026/09/260925093208.htm

AI Brings Tomorrow’s X-Rays to Life, Helping Doctors Fight Arthritis Sooner

From scitechdaily.com

An AI system developed at the University of Surrey can predict future knee X-rays, helping reveal how osteoarthritis may worsen over time. By turning complex predictions into clear images, it gives doctors and patients a better chance to act early. 

Researchers at the University of Surrey have created an artificial intelligence system that can estimate what a patient’s knee X-ray may look like one year into the future. The technology could significantly change how people with osteoarthritis understand their condition and make decisions about treatment and lifestyle changes.

Turning Data Into Visual Predictions

The findings were presented at the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2025). The study explains how the Surrey team uses advanced machine learning to produce a realistic “future” knee X-ray together with a score that estimates how likely the disease is to progress. When viewed together, these results give both doctors and patients a clearer and more visual sense of what may lie ahead.

                                                     AI predicts osteoarthritis progression. Credit: University of Surrey

A Global Condition Meets Large Scale AI

Osteoarthritis is a degenerative joint disease affecting more than 500 million people worldwide and is the leading cause of disability among older adults. The new system was trained on nearly 50,000 knee X-rays from almost 5,000 patients, making it one of the largest osteoarthritis datasets ever used for this purpose.

According to the researchers, the AI predicts disease progression more accurately than similar tools while operating around nine times faster and in a more compact form, which could help it move into everyday clinical use sooner.

Showing Patients What the Numbers Mean

David Butler, the study’s lead author from the University of Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP) and the Institute for People-Centred AI, said:

“We’re used to medical AI tools that give a number or a prediction, but not much explanation. Our system not only predicts the likelihood of your knee getting worse – it actually shows you a realistic image of what that future knee could look like. Seeing the two X-rays side by side – one from today and one for next year – is a powerful motivator. It helps doctors act sooner and gives patients a clearer picture of why sticking to their treatment plan or making lifestyle changes really matters. We think this can be a turning point in how we communicate risk and improve osteoarthritic knee care and other related conditions.”

How the Technology Builds Trust

The system relies on a type of generative AI known as a diffusion model. It creates a projected future knee X-ray and marks 16 key points within the joint. By showing exactly which areas the AI is tracking for change, the system becomes more transparent and easier for clinicians to understand and trust.

Beyond Knees and Osteoarthritis

The researchers believe this approach could eventually be adapted to other long-term health problems. Similar tools might one day help predict lung damage in smokers or monitor the progression of heart disease, giving patients and doctors visual insight that supports earlier action. The team is now looking for partners to help bring the technology into real clinical settings.

A Shift Toward Clearer Medical AI

Gustavo Carneiro, Professor of AI and Machine Learning at Surrey’s Centre for Vision, Speech and Signal Processing (CVSSP), said:

“Earlier AI systems could estimate the risk of osteoarthritis progression, but they were often slow, opaque, and limited to numbers rather than clear images. Our approach takes a big step forward by generating realistic future X-rays quickly and by pinpointing the areas of the joint most likely to change. That extra visibility helps clinicians identify high-risk patients sooner and personalize their care in ways that were not previously practical.”

Reference: “Risk Estimation of Knee Osteoarthritis Progression via Predictive Multi-task Modelling from Efficient Diffusion Model Using X-Ray Images” by David Butler, Adrian Hilton and Gustavo Carneiro, 20 September 2025, Medical Image Computing and Computer Assisted Intervention – MICCAI 2025.
DOI: 10.1007/978-3-032-05185-1_52

https://scitechdaily.com/ai-brings-tomorrows-x-rays-to-life-helping-doctors-fight-arthritis-sooner/