Transcranial Sonography and Machine Learning for Schizophrenia Identification

Starting soon

Conditions studied: Schizophrenia

In brief

Schizophrenia is a serious mental illness. Doctors usually diagnose schizophrenia by talking with patients, reviewing symptoms, and using clinical assessment. In early or less typical cases, diagnosis may be difficult. This study will look at whether brain ultrasound information can help doctors identify features related to schizophrenia. The ultrasound scan used in this study is called transcranial sonography. It is a non-invasive scan that uses sound waves to look at brain structures through natural thin areas of the skull. The study will include adults with schizophrenia and adults without a personal or family history of mental disorders. All participants will have a transcranial sonography scan and provide basic clinical information. The researchers will measure brain ultrasound features, including the substantia nigra, raphe nuclei, and third ventricle, and will combine these features with clinical information. The main question is whether a computer model using ultrasound and clinical information can help distinguish adults with schizophrenia from adults without schizophrenia. The model is intended only as a research tool and possible future aid for doctors. It will not replace diagnosis by a psychiatrist and will not change the participant's usual medical care.

Key facts

Study ID
NCT07604129
Run by
Taizhou Second People's Hospital
People needed
200
Starts
2026-06-15
Expected to finish
2027-12-31
Last updated by the study team
2026-05-22

Who can join

Age: 18 and older, up to 65. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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