Can neuroimaging unlock precision therapeutics in psychosis spectrum disorders?

Neuroimaging has transformed the study of psychosis spectrum disorders (PSD), yielding major advances in our understanding of disease biology across molecular, circuit, and systems levels. Positron emission tomography established robust evidence for striatal dopamine dysfunction; magnetic resonance spectroscopy identified glutamatergic abnormalities, particularly early in illness; task-based functional MRI revealed impaired fronto-parietal recruitment during cognitive operations such as working memory; and resting-state fMRI uncovered widespread alterations in thalamo-cortical organization. Yet despite these achievements, the field has struggled to translate biological insight into precision therapeutics. A central limitation is the absence of reproducible brain–behavior associations, formalized here as neuro-phenotype geometry (NPG). NPG refers to the reproducible structure of associations between inter-individual variation in neural systems and clinically meaningful variation in symptoms, cognition, function, and illness trajectory. We argue that reproducible NPG is a central statistical object for imaging-enabled therapeutic development because both patient selection and endpoint optimization depend on it. Furthermore, translation also requires alignment with endpoints on a regulatory path, which in PSD remains narrow, centered largely on PANSS-based symptom measures and MATRICS-informed cognition. Robust NPG signatures should be linked to disease-modifying mechanisms through neurobiologically grounded computational models, situated within longitudinal designs that respect the dynamic nature of illness, and derived from multimodal datasets capable of capturing pathophysiology across scales. This agenda defines the scientific and translational priorities needed to unlock genuinely mechanism-based precision treatment in psychosis.