Prediction of nonremission to antidepressant therapy using diffusion tensor imaging

Abstract

Objective: Over 50% of outpatients with nonpsychotic major depressive disorder (MDD) do not achieve remission with any single antidepressant medication (ADM). There are currently no clinically useful pretreatment measures that inform the decision to prescribe or select ADMs. This report examines whether a biomarker based on diffusion tensor imaging (DTI) measures of brain connectivity can identify a subset of nonremitting patients with a sufficiently high degree of specificity that use of a medication that is likely to fail could be avoided.

Methods: MDD outpatients recruited from community and primary-care settings underwent pretreatment magnetic resonance imaging as part of the international Study to Predict Optimized Treatment in Depression (conducted December 2008-June 2014). DSM-IV criteria and a 17-item Hamilton Depression Rating Scale (HDRS17) score ≥ 16 confirmed the primary diagnosis of nonpsychotic MDD. Data from the first cohort of MDD patients (n = 74) were used to calculate fractional anisotropy measures of the stria terminalis and cingulate portion of the cingulate bundle (CgC). On the basis of our previous data, we hypothesized that nonremission might be predicted using a ratio of these 2 values. Remission was defined as an HDRS17 score of ≤ 7 following 8 weeks of open-label treatment with escitalopram, sertraline, or venlafaxine extended-release, randomized across participants. The second study cohort (n = 83) was used for replication.

Results: Thirty-four percent of all participants achieved remission. A value > 1.0 for the ratio of the fractional anisotropy of the stria terminalis over the CgC identified 38% of the nonremitting participants with an accuracy of 88% (test cohort; odds ratio [OR] = 9.6; 95% CI, 2.0-45.9); 24% with an accuracy of 83% (replication cohort; OR = 1.8; 95% CI, 0.5-6.9) and 29% with an accuracy of 86% (pooled data; OR = 4.0; 95% CI, 1.5-11.1). Treatment moderation analysis showed greater specificity for escitalopram and sertraline (χ(2) = 8.07; P = .003).

Conclusions: To our knowledge, this simple DTI-derived metric represents the first brain biomarker to reliably identify nonremitting patients in MDD. The test identifies a meaningful proportion of nonremitters, has high specificity, and may assist in managing the antidepressant treatment of depression.

Trial registration: ClinicalTrials.gov identifier: NCT00693849.