Contemporary Perspectives in Schizophrenia Care
Human Impact of Relapse

Two Distinct Neuroanatomical Subtypes of Schizophrenia Revealed Using Machine Learning

CHAND GB, ET AL.  BRAIN. 2020;143:1027-1038.
1 min

The Study

Using structural MRI and deep machine learning, researchers at the University of Pennsylvania became the first to identify 2 distinct, highly reproducible neuroanatomical subtypes of schizophrenia.

The Analysis

Researchers analyzed brain scans of 307 schizophrenia patients and 364 healthy, age-matched controls and identified that ~60% of schizophrenia patients showed widespread reductions in grey matter, while the remaining 40% had no loss of brain volume, despite controlling for age and duration of illness.

The Reason It Matters

These subtypes challenge the assertion that brain volume loss is a universal feature of schizophrenia and may help facilitate novel strategies for personalized treatment and diagnostics among patients with schizophrenia. These data reinforce the anatomical complexity and heterogeneity within schizophrenia, as well as the importance of individualized care plans for patients.

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