Improved MRI scans could aid in development of arthritis treatments


Date:
June 9, 2020
Source:
University of Cambridge
Summary:
An algorithm which analyses MRI images and automatically detects
small changes in knee joints over time could be used in the
development of new treatments for arthritis.



FULL STORY ==========================================================================
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.


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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.



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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.

The 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. "The 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." The 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.


========================================================================== Story Source: Materials provided by University_of_Cambridge. The original
story is licensed under a Creative_Commons_License. Note: Content may
be edited for style and length.


========================================================================== Journal Reference:
1. James W. MacKay, Joshua D. Kaggie, Graham M. Treece, Stephen M.

McDonnell, Wasim Khan, Alexandra R. Roberts, Robert L. Janiczek,
Martin J. Graves, Tom D. Turmezei, Andrew W. McCaskie, Fiona
J. Gilbert.

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 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/06/200609122908.htm

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