Researchers at the University of California, Los Angeles, US, have developed a new test to predict whether obsessive-compulsive disorder (OCD) will improve with treatment using specific therapy.

OCD is a lifelong illness treated using cognitive behavioural therapy, which is known to be expensive, time-consuming, and might not work for all the patients.

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The new predictive tool combines magnetic resonance imaging (MRI) with a form of artificial intelligence (AI) called machine learning and is expected to improve the overall success rate of the therapy and enable tailored treatment for each patient.

During a study, the researchers used functional MRI machine (fMRI) to scan the brains of 42 OCD patients prior to and following treatment with four weeks of daily cognitive behavioural therapy.

The activation of various parts of the brain and severity of OCD symptoms before and after the therapy were analysed and the resulting fMRI data and symptom scores were fed into a computer.

“This method opens a window into OCD patients’ brains to help us see how responsive they will be to treatment.”

Machine learning was subsequently used to predict people who would respond to the treatment. It was found that the AI programme identified which patients would fail to respond with 70% accuracy.

Study’s senior author Dr Jamie Feusner said: “This method opens a window into OCD patients’ brains to help us see how responsive they will be to treatment.

“The algorithm performed far better than our own predictions based on their symptoms and other clinical information.”

Feusner further added that confirmation of these results in additional settings could optimise therapy and avoid unnecessary cost of treatment for OCD patients.