SHAP Interpretation of a Tree-Based Model for Deep Gray Matter QSM and R2* in First Episode Psychosis Patients and Their Response to Antipsychotics

Motivation: Several studies have demonstrated altered neurochemicals in psychosis. QSM quantify susceptibility changes, which have been associated with iron concentrations in dopamine pathways. Goal(s): Identify the strongest predictive QSM and R2* in first-episode psychosis (FEP) patients and their response to antipsychotics using a tree-based model. Approach: A tree-base model to discriminate between treatment-responsive (RS) and treatment-resistant (TRS) FEP patients by looking at tissue susceptibilities. Results: Our model classifies RS and TRS patients: 96.67 ± 1.38 % accuracy. Also, TRS could be classified by QSM: left amygdala, right globus pallidus interna, and nucleus accumbens, which have been associated with decreased dopamine in TRS patients. Impact: The proposed features could be used in future studies to early detect TRS-FEP patients and promptly adopt adequate treatment. This intervention may improve their clinical outcomes and minimize the functional disability and social burden resulting from prolonged psychosis.