Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol...

Area of Science:

• Neuroscience
• Psychiatry
• Medical Imaging

Background:

• Major Depressive Disorder (MDD) affects millions, with ~50% experiencing suboptimal response to initial antidepressant treatments.
• Predictive biomarkers are needed to personalize treatment, reducing patient burden and healthcare costs.
• Brain imaging offers a neurobiologically grounded approach to identify predictors of antidepressant response.

Purpose of the Study:

• To identify pretreatment neuroimaging predictors of treatment response in major depressive disorder (MDD).
• To investigate the utility of functional and structural MRI in predicting outcomes for escitalopram, sertraline, and venlafaxine-XR.
• To validate imaging biomarkers in a large, multi-center, randomized clinical trial.

Main Methods:

• The international Study to Predict Optimized Treatment in Depression (iSPOT-D) is a multi-center, randomized trial with an embedded imaging sub-study.
• Participants (N=2016) receive open-label escitalopram, sertraline, or venlafaxine-XR.
• The imaging sub-study (n≈201) includes baseline and post-treatment structural MRI, diffusion tensor imaging, and functional MRI during cognitive and emotional tasks.

Main Results:

• Predictive models will be developed and validated within the imaging sub-study sample.
• Analysis will compare baseline imaging features between treatment responders and non-responders.
• Findings will be extended to the full iSPOT-D cohort.

Conclusions:

• Identifying neurobiological predictors could enable personalized antidepressant selection for MDD.
• This study aims to establish brain imaging as a tool for optimizing depression treatment.
• Successful prediction of treatment response could significantly improve patient outcomes and treatment efficiency.