Using AI to deliver more precise magnetic stimulation treatment for depression

A USQ Professor is helping bring new technology to the forefront in the fight against depression.

A decade after Transcranial Magnetic Stimulation therapy was declared a new weapon in the fight against depression, researchers at the University of Southern Queensland are planning to use artificial intelligence to improve the procedure.

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.

More patients will soon have access to the treatment after it was announced in the latest federal budget rTMS therapy would be added to the Medicare Benefits Scheme.

While the benefits of rTMS are well recognised, Professor Raj Gururajan and his team are working with the Belmont Private Hospital to develop an AI model that can inform treatment decisions 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,” Professor 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.

Professor Gururajan said the AI algorithms they were developing would enable Psychiatrists to treat patients with a more precise treatment of rTMS.

“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.”

Professor Gururajan said AI had enormous promise for mental health care and was 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,” he 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 $21m 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.

“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.”

Professor Gururajan’s research team consists of Associate Professor Xiaohui Tao, Dr Xujuan Zhou, Professor Rajendra Acharya and research student Matthew Squires, while Belmont Private Hospital’s team includes CEO/DCS Mary Williams, Area Manager Rachel Stark and Dr Soman Elangovan.

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