Predict psychosis before it occurs – Medical News

Brain images from thousands of people around the world were used to create a machine learning classifier that could help with early diagnosis.

Appearance psychosis This can be predicted before it happens by using a machine learning tool that can classify MRI brain scans between healthy people and those at risk of a psychotic episode.

An international consortium, including researchers from the University of Tokyo, used the classifier to compare scans of more than 2,000 people from 21 locations around the world. Approximately half of the participants were clinically diagnosed high risk

development of psychosis.

Using training data, the classifier was 85% accurate in distinguishing between people who were not at risk and those who later experienced overt psychotic symptoms. Using the new data, the accuracy was 73%. This tool may be useful in future clinical settings because although most people with psychosis make a full recovery, earlier intervention usually leads to better outcomes with less negative impact on people’s lives.

Anyone can experience a psychotic episode, usually involving delusions, hallucinations, or disorganized thoughts.

There is no single cause, but it can be caused by illness or injury, trauma, drug or alcohol use, medication, or genetic predisposition. Although psychosis can be frightening or distressing, it is treatable and most people recover. Because the first episode most often occurs during adolescence or early adulthood, when the brain and body are going through many changes, it can be difficult to identify young people who need help.

“In most cases, only 30% of people at high clinical risk subsequently develop overt psychotic symptoms, while the remaining 70% do not,” explained Associate Professor Shinsuke Koike from the University’s Graduate School of Arts and Sciences in Tokyo. “Clinicians therefore need help in identifying those who will have psychotic symptoms, using not only subclinical signs such as changes in thinking, behavior and emotions, but also some biological markers.”

A consortium of researchers has been working to create a machine learning tool that uses brain MRI to identify people at risk of psychosis before it begins. Previous studies using brain MRI have shown that structural differences occur in the brain after the onset of psychosis. However, for the first time, differences have been identified in the brains of those who are at very high risk but have not yet experienced psychosis.

The team of 21 institutions from 15 different countries brought together a large and diverse group of adolescent and young adult participants. Studying psychotic disorders using MRI can be challenging because differences in brain development and MRI machines make it difficult to obtain very precise and comparable results, Koike said. In addition, young people may have difficulty distinguishing changes that occur as a result of typical development from those that occur due to mental illness.