Background: Approximately 20-30% of ultra-high risk (UHR) individuals transition to psychosis within 2-3 years. Neurobiological markers predicting conversion remain critical for precision prevention strategies.
Objective: To systematically identify and evaluate structural and functional neuroimaging biomarkers at UHR baseline that predict subsequent conversion to psychosis.
Methods: Following PRISMA 2020 guidelines, we searched five databases from January 2000 to February 2025. Two independent reviewers screened studies and assessed quality using the Newcastle-Ottawa Scale. Eligible studies examined baseline neuroimaging measures (structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy) as predictors of psychosis conversion in UHR cohorts.
Results: Twenty-five studies comprising 2436 UHR individuals (627 converters, 25.7%) were included (80.0% high quality). Reduced baseline gray matter volume in medial temporal structures (hippocampus: Cohen's d = -0.45 to -0.68; parahippocampal gyrus: d = -0.52 to -0.71) and prefrontal cortex (d = -0.41 to -0.68) consistently predicted conversion. Progressive gray matter loss in superior temporal gyrus distinguished converters (d = -0.72). Reduced prefrontal-temporal functional connectivity predicted conversion (AUC = 0.73-0.82). Compromised white matter integrity in uncinate fasciculus (fractional anisotropy: d = -0.47 to -0.71) and superior longitudinal fasciculus predicted transition. Elevated striatal glutamate predicted conversion (d = 0.52-0.76). Thalamocortical dysconnectivity showed large effects (Hedges' g = 0.66-0.88). Multimodal imaging models achieved 78-85% classification accuracy.
Conclusions: Neuroimaging biomarkers, particularly medial temporal and prefrontal structural alterations, functional dysconnectivity, and white matter abnormalities, demonstrate moderate-to-large effect sizes in predicting UHR conversion. Multimodal approaches combining structural, functional, and neurochemical measures show promise for individualized risk prediction and early intervention targeting in precision prevention strategies.
Keywords: MRI; neuroimaging; precision prevention; predictive biomarkers; psychosis conversion; ultra-high risk.