Diffusion tensor imaging predictors of treatment outcomes in major depressive disorder

Mayuresh S Korgaonkar; Leanne M Williams; Yun Ju Song; Tim Usherwood; Stuart M Grieve

doi:10.1192/bjp.bp.113.140376

Diffusion tensor imaging predictors of treatment outcomes in major depressive disorder

Br J Psychiatry. 2014 Oct;205(4):321-8. doi: 10.1192/bjp.bp.113.140376. Epub 2014 Jun 26.

Authors

Mayuresh S Korgaonkar¹, Leanne M Williams¹, Yun Ju Song¹, Tim Usherwood¹, Stuart M Grieve¹

Affiliation

¹ Mayuresh S. Korgaonkar, PhD, The Brain Dynamics Center, Sydney Medical School, The University of Sydney and Westmead Millennium Institute, Sydney and Discipline of Psychiatry, Sydney Medical School, The University of Sydney, Westmead Hospital, Sydney, Australia; Leanne M. Williams, PhD, The Brain Dynamics Center, Sydney Medical School, The University of Sydney and Westmead Millennium Institute, Sydney, Discipline of Psychiatry, Sydney Medical School, The University of Sydney, Westmead Hospital, Sydney, Australia and Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA; Yun Ju Song, PhD, The Brain Dynamics Center, Sydney Medical School, The University of Sydney and Westmead Millennium Institute, Sydney and Discipline of Psychiatry, Sydney Medical School, The University of Sydney, Westmead Hospital, Sydney, Australia; Tim Usherwood, MD, BS, FRACGP, Department of General Practice, Sydney Medical School, Westmead, Sydney, Australia; Stuart M. Grieve, MBBS, BSc, DPhil, RANZCR, The Brain Dynamics Center, Sydney Medical School, The University of Sydney and Westmead Millennium Institute, Sydney and Sydney Translational Imaging Laboratory, Sydney Medical School, Sydney, Australia.

PMID: 24970773
DOI: 10.1192/bjp.bp.113.140376

Abstract

Background: Functional neuroimaging studies implicate anterior cingulate and limbic dysfunction in major depressive disorder (MDD) and responsiveness to antidepressants. Diffusion tensor imaging (DTI) enables characterisation of white matter tracts that relate to these regions.

Aims: To examine whether DTI measures of anterior cingulate and limbic white matter are useful prognostic biomarkers for MDD.

Method: Of the 102 MDD out-patients from the International Study to Predict Optimized Treatment for Depression (iSPOT-D) who provided baseline magnetic resonance imaging (MRI) data, 74 completed an 8-week course of antidepressant medication (randomised to escitalopram, sertraline or extended-release venlafaxine) and were included in the present analyses. Thirty-four matched controls also provided DTI data. Fractional anisotropy was measured for five anterior cingulate-limbic white matter tracts: cingulum cingulate and hippocampus bundle, fornix, stria terminalis and uncinate fasciculus. (Trial registered at ClinicalTrials.gov: NCT00693849.)

Results: A cross-validated logistic regression model demonstrated that altered connectivity for the cingulum part of the cingulate and stria terminalis tracts significantly predicted remission independent of demographic and clinical measures with 62% accuracy. Prediction improved to 74% when age was added to this model.

Conclusions: Anterior cingulate-limbic white matter is a useful predictor of antidepressant treatment outcome in MDD.

Royal College of Psychiatrists.

Publication types

Randomized Controlled Trial
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Age Factors
Anisotropy
Antidepressive Agents / therapeutic use
Brain Mapping / methods
Depressive Disorder, Major / drug therapy
Depressive Disorder, Major / physiopathology*
Diffusion Tensor Imaging / methods*
Female
Gyrus Cinguli / physiopathology*
Humans
Limbic System / physiopathology
Logistic Models
Male
Middle Aged
Prognosis
White Matter / physiopathology*
Young Adult

Substances

Antidepressive Agents

Associated data

ClinicalTrials.gov/NCT00693849