Background Efforts to define biologically grounded subtypes of schizophrenia have increasingly leveraged neuroimaging data and clustering algorithms. Such approaches aim to capture patient-level heterogeneity with potential clinical and mechanistic relevance. This review evaluates whether structural neuroimaging-derived subtypes can be robustly identified and meaningfully linked to clinical variation.

Methods A systematic review was conducted of peer-reviewed studies published between January 2015 and December 2024 that applied data-driven clustering algorithms to neuroimaging data to identify patient-level subtypes of individuals with schizophrenia or related spectrum disorders. Transdiagnostic studies and those focusing solely on case-control classification, or on feature-level clustering without individual-level subtype assignment, were excluded.

Results Eighteen studies met inclusion criteria. Most used structural MRI, but input features and clustering algorithms varied widely. Across studies, three broad neuroanatomical patterns were described: subtypes with widespread reductions in brain structure, those with regionally circumscribed abnormalities, and those with largely preserved profiles. However, the specific brain regions implicated within each category varied considerably between studies, and no subtype profile was consistently reproduced. Subtypes were not reliably associated with clinical features although there was a trend for higher clinical burden for the widespread subtypes.

Conclusions Current evidence is insufficient to determine whether macroscale neuroimaging features can define subtypes of schizophrenia that are biologically valid or clinically meaningful. Given the limited and inconsistent findings, the subtypes reported to date may reflect continuous variation within the disorder rather than discrete, biologically distinct entities. Advancing the field will require larger, harmonized datasets, standardized analytic pipelines, and rigorous external and longitudinal validation.

The authors have declared no competing interest.

This study did not receive any funding.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

All data produced in the present work are contained in the manuscript.