Magnetic Resonance Imaging Measures of Brain Structure to Predict Antidepressant Treatment Outcome in Major Depressive Disorder

Mayuresh S Korgaonkar, William Rekshan, Evian Gordon, A John Rush, Leanne M Williams, Christine Blasey, Stuart M Grieve, Mayuresh S Korgaonkar, William Rekshan, Evian Gordon, A John Rush, Leanne M Williams, Christine Blasey, Stuart M Grieve

Abstract

Background: Less than 50% of patients with Major Depressive Disorder (MDD) reach symptomatic remission with their initial antidepressant medication (ADM). There are currently no objective measures with which to reliably predict which individuals will achieve remission to ADMs.

Methods: 157 participants with MDD from the International Study to Predict Optimized Treatment in Depression (iSPOT-D) underwent baseline MRIs and completed eight weeks of treatment with escitalopram, sertraline or venlafaxine-ER. A score at week 8 of 7 or less on the 17 item Hamilton Rating Scale for Depression defined remission. Receiver Operator Characteristics (ROC) analysis using the first 50% participants was performed to define decision trees of baseline MRI volumetric and connectivity (fractional anisotropy) measures that differentiated non-remitters from remitters with maximal sensitivity and specificity. These decision trees were tested for replication in the remaining participants.

Findings: Overall, 35% of all participants achieved remission. ROC analyses identified two decision trees that predicted a high probability of non-remission and that were replicated: 1. Left middle frontal volume < 14 · 8 mL & right angular gyrus volume > 6 · 3 mL identified 55% of non-remitters with 85% accuracy; and 2. Fractional anisotropy values in the left cingulum bundle < 0 · 63, right superior fronto-occipital fasciculus < 0 · 54 and right superior longitudinal fasciculus < 0 · 50 identified 15% of the non-remitters with 84% accuracy. All participants who met criteria for both decision trees were correctly identified as non-remitters.

Interpretation: Pretreatment MRI measures seem to reliably identify a subset of patients who do not remit with a first step medication that includes one of these commonly used medications. Findings are consistent with a neuroanatomical basis for non-remission in depressed patients.

Funding: Brain Resource Ltd is the sponsor for the iSPOT-D study (NCT00693849).

Keywords: Biomarker predictors; Decision trees; Diffusion tensor imaging; Magnetic resonance imaging; Major depressive disorder; Remission; Replication; iSPOT-D.

Figures

Fig. 1
Fig. 1
iSPOT-D study CONSORT Diagram. Abbreviations: ADMs, antidepressant medications; DTI, diffusion tensor imaging; MDD, major depressive disorder; sMRI, structural T1 MRI.
Fig. 2
Fig. 2
Decision tree for prediction of remission using the DTI measures. Abbreviations: R, remitters; NR, non-remitters; FA, fractional anisotropy; CgC, cingulum portion of the cingulate gyrus; SFOF, superior fronto-occipital fasciculus; SLF, superior longitudinal fasciculus.
Fig. 3
Fig. 3
Decision tree for prediction of remission using the volumetric measures. Abbreviations: R, remitters; NR, non-remitters.
Fig. 4
Fig. 4
Significant left middle frontal cluster (shown in red) identified in the whole brain VBM analysis comparing selected non-remitters identified from the volumetric decision tree & all remitted MDD participants. The cluster peak was at (− 40, 14, 43) and comprised of 700 voxels (p 

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