This technology is a diagnostic tool for schizophrenia using magnetic resonance spectroscopy (MRS) for detecting elevated metabolite levels in the brain.
Schizophrenia is often diagnosed by a combination of observing behavioral symptoms and running tests which may rule out other conditions. The lack of biomarkers or reliable diagnostic tests makes diagnosing schizophrenia particularly difficult and can lead to misdiagnosis.
This technology describes a tool which uses magnetic resonance spectroscopy (MRS) to diagnose schizophrenia based on metabolite changes in the brain. Schizophrenic individuals have elevated levels of glutamate and glutamine which, among other metabolites, can be detected by MRS. The spectrum data obtained from MRS of a subject’s brain is processed by a trained machine learning model to estimate frequency and phase corrections to then quantify metabolites and aid in the diagnosis of schizophrenia and related disorders.
Patent Pending(WO/2022/221760)