Pre-treatment brain morphology predicts symptom-specific outcomes in paediatric emotional disorders

Depressive and anxiety disorders commonly co-occur in paediatric patients, but treatment response varies widely. Brain morphometric features may provide prognostic markers for symptom-specific outcomes and guide personalised interventions. This study examined whether pre-treatment brain morphology predicts improvement after inpatient treatment in adolescents with emotional disorders.

Adolescents with major depressive disorder and/or anxiety disorders admitted to a specialised psychiatric hospital underwent magnetic resonance imaging (MRI) before comprehensive inpatient treatment, including pharmacotherapy and psychotherapy (approximately 4-6 weeks, n = 66). Treatment response was assessed by percentage reductions in the Children's Depression Inventory (CDI) and Screen for Child Anxiety Related Emotional Disorders (SCARED) total scores. Backward stepwise regression was performed separately for depressive and anxiety symptom improvement, focusing on predefined morphometric features associated with depressive or anxiety disorder derived from prior large-scale neuroanatomical findings.

Among 66 adolescents, significant reductions in CDI and SCARED scores were observed over inpatient treatment. Regression analyses showed that larger pre-treatment surface area of the right postcentral gyrus was associated with greater improvement in depressive symptoms (slope=0.022; 95 % CI, 0.004-0.040; β=0.319; p = 0.016; n = 57), while smaller surface area of the left temporal pole (slope=-0.179; 95 % CI, -0.314 to -0.044; β=-0.304; p = 0.010; n = 64) and larger surface` area of the right frontal pole (slope=0.245; 95 % CI, 0.013-0.477; β=0.238; p = 0.039; n = 64) was associated with greater improvement in anxiety symptoms.

Pre-treatment morphometric features may serve as distinct neuroanatomical markers predicting symptom-specific response to inpatient treatment in paediatric emotional disorders, supporting the role of brain-based biomarkers in improving therapeutic outcomes.