Simulator predicts progression of knee osteoarthritis in overweight patients

By John Murphy, MDLinx
Published March 25, 2016

Key Takeaways

Scientists in Finland have developed a computer-aided simulator that is able to predict an individual patient’s progression of osteoarthritis of the knee, according to a study published online February 24, 2016 in Scientific Reports.

“The method we have developed is based on stresses experienced by the knee joint during walking, and these were simulated on a computer. Our idea was that walking-induced cumulative stresses that exceed a certain threshold will cause local degeneration in the articular cartilage of the knee,” said corresponding author Mika Mononen, PhD, Postdoctoral Researcher in the Department of Applied Physics at the University of Eastern Finland, in Kuopio, Finland.

Dr. Mononen and colleagues reasoned that, to prevent osteoarthritis effectively, there should be an algorithm that could simulate the development of osteoarthritis in individual patients. In addition, this algorithm should be able to guide patients toward the best possible intervention—whether that’s weight loss, surgery, or rehabilitation—in order to prevent or delay the onset and/or progression of osteoarthritis.

The algorithm should also take into account that the patient’s weight heavily affects the progression of knee osteoarthritis.

For this study, the researchers developed a cartilage degeneration algorithm based only on information obtained from a patient’s MRI to simulate the progression of osteoarthritis in the knee for overweight subjects. “The algorithm was based on cartilage overloading so that cumulatively accumulated excessive stresses caused alterations in tissue properties with time,” the authors wrote.

To test the algorithm, the researchers obtained patient data on 429 people under age 65 who had no osteoarthritis, and then classified the patients into two groups: the normal weight group and the overweight group. In each group, the subjects were of the same gender and similar weight and height.

The researchers followed the subjects for 4 years. In the normal weight group, the thickness of healthy cartilage did not change. But in the overweight group, significant degeneration did occur, as measured by the Kellgren-Lawrence grading system.

When the researchers compared the simulator’s predictions of the onset and development of osteoarthritis, they found that it agreed with the subjects’ outcomes after 4 years.

“The study shows that this new method, which is based on computer modelling, was able to predict similar changes in the articular cartilage of the knee as experimental follow-up data,” Dr. Mononen said.

In the future, the simulator could be applied as a clinical tool to predict an individual patient’s development of knee osteoarthritis from a sports injury, joint disorder, or overweight, and help to choose the best possible intervention, the researchers predicted. This algorithm could also estimate the effect of different interventions—such as osteotomy, meniscectomy, meniscus replacement, and weight loss—before they are applied to the patient. It could even be used to optimize surgical operations to minimize the need for and the costs of re-operations.

But before the algorithm is ready for clinical use, the researchers will need to validate it further by modeling more subjects from different groups that must be compared to experimentally observed osteoarthritis grades.

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