Researchers Work On Technology That Can Predict Suicidal Patients

In October, two researchers received $3.8M for a brain imaging study, working on cutting edge technology that uses brain imaging to predict and treat suicidal patients.

The researchers, Marcel Just from Carnegie Mellon University and David Bent from the University of Pittsburgh, received the funding from the National Institute of Mental Health to advance their technology known as the Predicting Risk Imaging Suicidal Minds (PRISM) project.

They hope this will provide new insights into suicidal patients and hopefully prevent people from taking their own lives by using brain imaging to predict who will attempt suicide.

If successful, the PRISM project will develop personalized treatment strategies for suicidal patients based on their altered patterns of thinking and feeling that can more precisely and effectively reduce suicide risk.

Just and Bent will use the grant to analyze the differences in brain scans of suicidal and non-suicidal young adults to detect those most at risk and develop personalized therapies.

Bent said their first study, which was published in Nature Human Behavior (2017) was considerably smaller, but with the funding, their next study would be larger and “will repeat the procedure to see if fluctuations in neural signatures are related to fluctuations in suicidal ideation, and see how we can predict future suicidal behavior. In addition, we will be developing and testing a peripheral measure that we hope will correlate with neural findings, but can be used in a clinician’s office without needing to do fMRI.”

The new study will have 450 participants, who will be split into three groups: those with suicidal tendencies, those with a psychiatric disorder, but are not thinking of suicide and a healthy control group.

Suicide, which accounted for 5,723 deaths in the U.S. last year, is said to be the leading cause of death among young adults in the U.S. The work being done by Just and Bent is a fine example of the digital transformation of healthcare that can potentially saves lives.  

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