USQ uses AI to deliver more precise rTMS treatment for depression

rTMS

Professor Raj Gururajan. Image credit: USQ

Researchers at the University of Southern Queensland (USQ) are planning to use artificial intelligence to improve the Transcranial Magnetic Stimulation (rTMS) procedure, to better treat depression.

Repetitive Transcranial Magnetic Stimulation (rTMS) is a safe and non-invasive brain stimulation technique used to treat depression and other mental health disorders, especially in patients who have not responded well to antidepressant medication.

After it was announced in the latest federal budget that rTMS therapy would be added to the Medicare Benefits Scheme, more patients are expecting access to the treatment. However, while the benefits of rTMS are well recognised, Professor Raj Gururajan and his team are working with Belmont Private Hospital to develop an AI model that can inform treatment decisions. It does this by recognising patterns from data collected after previous treatments.

“The World Health Organisation estimates that depression will be the number one health concern by 2030, therefore improving treatment outcomes and developing new technology to combat depression is fundamental,” Gururajan said.

“rTMS is quickly becoming a leading medical treatment for depression, but given it is a relatively new procedure, there are still ways we can improve its diagnosis, treatment and outcome prediction.”

A standard course of rTMS includes 20 treatment sessions that last between 20 to 40 minutes per each session.

The AI algorithms they are developing will enable psychiatrists to treat patients with a more precise treatment of rTMS, according to Gururajan.

“Our aim is to develop cutting-edge algorithms that will inform Psychiatrists on the most appropriate duration of stimulation for an individual patient at the outset of the treatment,” he said.

“rTMS is very time consuming, therefore expensive, but being able to use AI to facilitate personalised treatment planning and prediction could potentially save both the patient and health systems’ time and money, while improving patient outcomes.

“We plan to have an initial AI model developed and implemented between 24 to 30 months.”

AI has enormous promise for mental health care and is arguably the most important tool in addressing the growing rate of mental illness, and increased demand for mental health services due to the COVID-19 pandemic.

“The University of Southern Queensland has identified AI as a solution to help solve the mental health crisis and clinical access,” Gururajan said.

“Belmont Private Hospital is the largest private mental health care provider in Queensland, and the second largest in Australia.

“In addition to TMS and Electroconvulsive Therapy services already provided, its $21 million expansion will make Belmont Private the only private hospital in the state to offer continuity of care for adolescents through to older persons’ mental health,” he said.

“We’re pleased to partner with them on a project that will ultimately help more people get the treatment they need to improve their mental health.”

Gururajan’s research team consists of associate professor Xiaohui Tao, Dr Xujuan Zhou, professor Rajendra Acharya and research student Matthew Squires.

Belmont Private Hospital’s team includes CEO/DCS Mary Williams, area manager Rachel Stark and Dr Soman Elangovan.

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