A team of engineers, radiologists and physicians, led by the University 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. The 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.”
The 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.
The 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.
Image: 3D model of a knee with osteoarthritis
Credit: James MacKay
Reproduced courtesy of the University of Cambridge