̽��ֱ�� of Cambridge - osteoarthritis

Improved MRI scans could aid in development of arthritis treatments

sc604 — Tue, 09 Jun 2020 19:00:00 +0000

A team of engineers, radiologists and physicians, led by the ̽��ֱ�� of Cambridge, developed the algorithm, which builds a three-dimensional model of an individual’s knee joint in order to map where arthritis is affecting the knee. It then automatically creates ‘change maps’ which not only tell researchers whether there have been significant changes during the study but allow them to locate exactly where these are.

There are few effective treatments for arthritis, and the technique could be a considerable boost to efforts to develop and monitor new therapies for the condition. ̽��ֱ��results are reported in the Journal of Magnetic Resonance Imaging.

Osteoarthritis is the most common form of arthritis in the UK. It develops when the articular cartilage that coats the ends of bones and allows them to glide smoothly over each other at joints, is worn down, resulting in painful, immobile joints. Currently, there is no recognised cure and the only definitive treatment is surgery for artificial joint replacement.

Osteoarthritis is normally identified on an X-ray by a narrowing of the space between the bones of the joint due to a loss of cartilage. However, X-rays do not have enough sensitivity to detect subtle changes in the joint over time.

“We don’t have a good way of detecting these tiny changes in the joint over time in order to see if treatments are having any effect,” said Dr James MacKay from Cambridge’s Department of Radiology, and the study’s lead author. “In addition, if we’re able to detect the early signs of cartilage breakdown in joints, it will help us understand the disease better, which could lead to new treatments for this painful condition.”

̽��ֱ��current study builds on earlier work from the same team, who developed an algorithm to monitor subtle changes in arthritic joints in CT scans. Now, they are using similar techniques for MRI, which provides more complete information about the composition of tissue – not just information about the thickness of cartilage or bone.

MRI is already widely used to diagnose joint problems, including arthritis, but manually labelling each image is time-consuming, and may be less accurate than automated or semi-automated techniques when detecting small changes over a period of months or years.

“Thanks to the engineering expertise of our team, we now have a better way of looking at the joint,” said MacKay.

̽��ֱ��technique MacKay and his colleagues from Cambridge’s Department of Engineering developed, called 3D cartilage surface mapping (3D-CaSM), was able to pick up changes over a period of six months that weren’t detected using standard X-ray or MRI techniques.

̽��ֱ��researchers tested their algorithm on knee joints from bodies that had been donated for medical research, and a further study with human participants between 40 and 60 years old. All of the participants suffered from knee pain, but were considered too young for a knee replacement. Their joints were then compared with people of a similar age with no joint pain.

“There’s a certain degree of deterioration of the joint that happens as a normal part of aging, but we wanted to make sure that the changes we were detecting were caused by arthritis,” said MacKay. “ ̽��ֱ��increased sensitivity that 3D-CaSM provides allows us to make this distinction, which we hope will make it a valuable tool for testing the effectiveness of new therapies.”

̽��ֱ��software is freely available to download and can be added to existing systems. MacKay says that the algorithm can easily be added to existing workflows and that the training process for radiologists is short and straightforward.

As part of a separate study funded by the European Union, the researchers will also be using the algorithm to test whether it can predict which patients will need a knee replacement, by detecting early signs of arthritis.

Reference:
James W. MacKay et al. ‘Three-dimensional Surface-based Analysis of Cartilage MRI data in Knee Osteoarthritis: Validation and Initial Clinical Application.’ Journal of Magnetic Resonance Imaging (2020). DOI: 10.1002/jmri.27193

An algorithm that analyses MRI images and automatically detects small changes in knee joints over time could be used in the development of new treatments for arthritis.

Thanks to the engineering expertise of our team, we now have a better way of looking at the joint

James MacKay

3D model of a knee with osteoarthritis

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

Yes

Joint lubricating fluid plays key role in osteoarthritic pain, study finds

ta385 — Thu, 15 Aug 2019 06:00:00 +0000

Osteoarthritis is the most common form of arthritis. It causes joint pain and stiffness, and in some people swelling and tenderness of the joints. ̽��ֱ��condition affects an individual’s quality of life and costs millions to the global economy, both directly in terms of healthcare costs and indirectly due to impact on the individual’s working life.

Osteoarthritis tends to occur later in life and has been largely considered as a degenerative disorder in which pain is produced by damage and wear and tear to bone and cartilage. However, in recent years it has become clear that osteoarthritis is not restricted to cartilage damage, but is a failure of the entire joint, with inflammation – the body’s response to stress and injury – being a major contributor to the pain experienced by patients. A recent collaboration between the two pharmaceutical companies Pfizer and Eli Lilly has found that their anti-inflammatory drug, tanezumab, produced pain relief for osteoarthritic patients in a phase 3 clinical trial.

When inflammation occurs during osteoarthritis, the body produces an increased number of cells within and around the joint. These cells release inflammatory substances into the synovial fluid, the lubricant that allows joints to move smoothly. During osteoarthritis, synovial fluid becomes less viscous and these inflammatory substances come into direct contact with sensory nerve cells in the joint, producing the sensation of pain.

In a study published on 13 August 2019 in the journal Rheumatology, researchers at the ̽��ֱ�� of Cambridge and Addenbrooke’s Hospital, part of Cambridge ̽��ֱ�� Hospitals, examined whether synovial fluid produced during osteoarthritis is capable of directly exciting sensory nerves supplying knee joints – those nerves responsible for transmitting pain signals.

“Osteoarthritis can be a very painful condition, but we only know a little about what causes this pain,” says Sam Chakrabarti, a Gates Cambridge Scholar. “We wanted to investigate what was happening in the joint and to see whether it was the lubricant that ordinarily keeps these joints moving that was contributing to the pain. Studies such as these are important in helping us develop better treatments.”

̽��ֱ��researchers obtained synovial fluid from consenting osteoarthritis patients at Addenbrooke’s Hospital and from post-mortem donors with no known joint disease. They then incubated knee sensory nerves isolated from mice in either healthy or osteoarthritis synovial fluid and recorded the activity of these nerves.

̽��ֱ��team found that when incubated with osteoarthritic synovial fluid, the knee nerves were more excitable. ̽��ֱ��nerves also showed an increase in the function of TRPV1, a molecule that detects the hotness of chilli peppers (TRPV1 is also activated by heat, which is why chillis tastes hot). Although the presence of inflammatory chemicals in osteoarthritis synovial fluid has been known since 1959, this is the first evidence that synovial fluid can directly excite sensory nerves and hence is an important contributor to an individual’s experience of pain.

“This is the first time we have been able to use synovial fluid from human osteoarthritis patients to excite sensory nerve cells, making it more clinically-relevant than mouse studies alone, and so will hopefully help translating treatments from bench to bedside,” says Dr Ewan St John Smith from the Department of Pharmacology at the ̽��ֱ�� of Cambridge.

“In the future, this set up can be used to identify the specific components of synovial fluid that cause pain and then to test if and how a drug will be useful in arthritic pain. Since synovial fluid is regularly collected from arthritic patients as part of their treatment regime, our technique can be easily set up in laboratories throughout the world to understand and help to identify a cure for arthritic pain.”

Dr Deepak Jadon, Director of the Rheumatology Research Unit at Cambridge ̽��ֱ�� Hospitals, adds: “This study highlights how much we can learn with the help of our patients, as well as the importance of collaboration between clinicians and basic scientists.”

̽��ֱ��research was funded by Versus Arthritis and the Gates Cambridge Trust.

Reference

Chakrabarti, S et al. Human osteoarthritic synovial fluid increases excitability of mouse dorsal root ganglion sensory neurons: an in-vitro translational model to study arthritic pain. Rheumatology; 13 August 2019; DOI: 10.1093/rheumatology/kez331

A team at the ̽��ֱ�� of Cambridge has shown how, in osteoarthritis patients, the viscous lubricant that ordinarily allows our joints to move smoothly triggers a pain response from nerve cells similar to that caused by chilli peppers.

In the future, this set up can be used to identify the specific components of synovial fluid that cause pain

Ewan St John Smith

Courtesy for Jamelah e. under CC license

Researcher profile: Sampurna Chakrabarti

Around the time that Sam Chakrabarti graduated from the ̽��ֱ�� of Buffalo, the State ̽��ֱ�� of New York, the US was caught in the middle of the opioid crisis, in part because these addictive pain killers were being over-prescribed. Spurred on by the crisis, Sam joined the lab of Dr Ewan St John Smith at Cambridge as a Gates Cambridge Scholar, eager to improve the lives of other by furthering the understanding of pain pathways. “I want my research to contribute towards a world where pain relief is safe and affordable, a world where the reason people take time off work is to go on vacation, not because they are in excruciating pain,” she says.

Originally from Kolkata, India, Sam is interested in finding better ways of studying painful knee arthritis to help identify drug targets. Arthritis affects millions of people worldwide, but patients often receive inadequate pain relief. A major reason for this is the lack of understanding of the basic biology underlying the disease, but Sam recognizes that tackling arthritic pain will require a much broader approach than basic science.

“I hope my research will lead to an understanding of pain that crosses many disciplines and breaks down the language barrier between psychologists, biologists and computer scientists,” she says. “Pain is complex and manifests at multiple levels – a way to understand a phenomenon like this should also be multidisciplinary.”

Sam has been at Cambridge since 2016, during which time she says: “I have met more fascinating, inspiring and engaging people than in my entire life. At Cambridge I feel I am a part of the quest for knowledge that transcends grades and papers, but reflects our innate curiosity.”

Yes

Licence type:

Attribution-Noncommercial-ShareAlike

New 3D imaging analysis technique could lead to improved arthritis treatment

sc604 — Mon, 18 Jun 2018 09:00:00 +0000

̽��ֱ��technique, which detects tiny changes in arthritic joints, could enable greater understanding of how osteoarthritis develops and allow the effectiveness of new treatments to be assessed more accurately, without the need for invasive tissue sampling. ̽��ֱ��results are published in the journal Scientific Reports.

Osteoarthritis is the most common form of arthritis in the UK. It develops when the articular cartilage that coats the ends of bones, and allows them to glide smoothly over each other at joints, is worn down, resulting in painful, immobile joints. Currently there is no recognised cure and the only definitive treatment is surgery for artificial joint replacement.

Osteoarthritis is normally identified on an x-ray by a narrowing of the space between the bones of the joint due to a loss of cartilage. However, x-rays do not have enough sensitivity to detect subtle changes in the joint over time.

“In addition to their lack of sensitivity, two-dimensional x-rays rely on humans to interpret them,” said lead author Dr Tom Turmezei from Cambridge’s Department of Engineering. “Our ability to detect structural changes to identify disease early, monitor progression and predict treatment response is frustratingly limited by this.”

̽��ֱ��technique developed by Turmezei and his colleagues uses images from a standard computerised tomography (CT) scan, which isn’t normally used to monitor joints, but produces detailed images in three dimensions.

̽��ֱ��semi-automated technique, called joint space mapping (JSM), analyses the CT images to identify changes in the space between the bones of the joint in question, a recognised surrogate marker for osteoarthritis. After developing the algorithm with tests on human hip joints from bodies that had been donated for medical research, they found that it exceeded the current ‘gold standard’ of joint imaging with x-rays in terms of sensitivity, showing that it was at least twice as good at detecting small structural changes. Colour-coded images produced using the JSM algorithm illustrate the parts of the joint where the space between bones is wider or narrower.

“Using this technique, we’ll hopefully be able to identify osteoarthritis earlier, and look at potential treatments before it becomes debilitating,” said Turmezei, who is now a consultant at the Norfolk and Norwich ̽��ֱ�� Hospital’s Department of Radiology. “It could be used to screen at-risk populations, such as those with known arthritis, previous joint injury, or elite athletes who are at risk of developing arthritis due to the continued strain placed on their joints.”

While CT scanning is regularly used in the clinic to diagnose and monitor a range of health conditions, CT of joints has not yet been approved for use in research trials. According to the researchers, the success of the JSM algorithm demonstrates that 3D imaging techniques have the potential to be more effective than 2D imaging. In addition, CT can now be used with very low doses of radiation, meaning that it can be safely used more frequently for the purposes of ongoing monitoring.

“We’ve shown that this technique could be a valuable tool for the analysis of arthritis, in both clinical and research settings,” said Turmezei. “When combined with 3D statistical analysis, it could be also be used to speed up the development of new treatments.”

Tom Turmezei acknowledges the Wellcome Trust for research funding. Ken Poole acknowledges the support of the Cambridge NIHR Biomedical Research Centre.

Reference
T.D. Turmezei et al. ‘A new quantitative 3D approach to imaging of structural joint disease.’ Scientific Reports (2018). DOI: 10.1038/s41598-018-27486-y

An algorithm to monitor the joints of patients with arthritis, which could change the way that the severity of the condition is assessed, has been developed by a team of engineers, physicians and radiologists led by the ̽��ֱ�� of Cambridge.

Using this technique, we’ll hopefully be able to identify osteoarthritis earlier, and look at potential treatments before it becomes debilitating.

Tom Turmezei

Hip, knee and ankle joints analysed by the JSM algorithm

Yes