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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
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Prediction of nonremission to antidepressant therapy using diffusion tensor imaging
Stuart M Grieve1, Mayuresh S Korgaonkar, Evian Gordon
1The Brain Dynamics Center, Westmead Millennium Institute for Medical Research, 176 Hawkesbury Rd, Westmead, Sydney, NSW 2145, Australia stuart.grieve@sydney.edu.au.
The Journal of Clinical Psychiatry
|May 4, 2016
Summary
A novel diffusion tensor imaging (DTI) brain biomarker can identify major depressive disorder (MDD) patients unlikely to respond to antidepressant medication. This biomarker helps avoid ineffective treatments, improving patient outcomes in depression management.
Area of Science:
- Neuroimaging
- Psychiatry
- Biomarker Discovery
Background:
- Over 50% of major depressive disorder (MDD) outpatients do not achieve remission with initial antidepressant medication (ADM).
- Currently, no reliable pretreatment measures exist to guide ADM selection for nonpsychotic MDD.
- This highlights a critical unmet need for personalized treatment strategies in depression.
Purpose of the Study:
- To investigate if a diffusion tensor imaging (DTI) biomarker based on brain connectivity can identify patients with nonpsychotic MDD who are unlikely to achieve remission.
- To determine if this biomarker can achieve sufficient specificity to avoid prescribing medications likely to fail.
Main Methods:
- Recruited MDD outpatients from community and primary-care settings.
- Utilized pretreatment magnetic resonance imaging (MRI) to calculate fractional anisotropy (FA) ratios of the stria terminalis and cingulate bundle (CgC).
- Validated the biomarker in a test cohort (n=74) and replicated findings in a second cohort (n=83), defining remission as a Hamilton Depression Rating Scale (HDRS17) score ≤ 7 after 8 weeks of open-label treatment.
Main Results:
- A CgC/stria terminalis FA ratio > 1.0 identified nonremitting patients with 88% accuracy in the test cohort and 83% in the replication cohort.
- This DTI-derived metric identified 29% of nonremitters with 86% accuracy in pooled data (OR = 4.0).
- Greater specificity was observed for escitalopram and sertraline compared to venlafaxine.
Conclusions:
- This DTI-derived ratio is the first brain biomarker to reliably identify nonremitting MDD patients.
- The biomarker has high specificity and identifies a significant proportion of nonremitters.
- It may assist clinicians in optimizing antidepressant treatment selection for depression management.
