Structural MRI at 7T reveals amygdala nuclei and hippocampal subfield volumetric association with Major Depressive Disorder symptom severity.
Stephanie S G BrownJ W RutlandG VermaR E FeldmanJ AlperM SchneiderB N DelmanJ M MurroughP BalchandaniPublished in: Scientific reports (2019)
Subcortical volumetric changes in major depressive disorder (MDD) have been purported to underlie depressive symptomology, however, the evidence to date remains inconsistent. Here, we investigated limbic volumes in MDD, utilizing high-resolution structural images to allow segmentation of the hippocampus and amygdala into their constituent substructures. Twenty-four MDD patients and twenty matched controls underwent structural MRI at 7T field strength. All participants completed the Montgomery-Asberg Depression Rating Scale (MADRS) to quantify depressive symptomology. For the MDD group, volumes of the amygdala right lateral nucleus (p = 0.05, r2 = 0.24), left cortical nucleus (p = 0.032, r2 = 0.35), left accessory basal nucleus (p = 0.04, r2 = 0.28) and bilateral corticoamygdaloid transition area (right hemisphere p = 0.032, r2 = 0.38, left hemisphere p = 0.032, r2 = 0.35) each displayed significant negative associations with MDD severity. The bilateral centrocortical (right hemisphere p = 0.032, r2 = 0.31, left hemisphere p = 0.032, r2 = 0.32) and right basolateral complexes (p = 0.05, r2 = 0.24) also displayed significant negative relationships with depressive symptoms. Using high-field strength MRI, we report the novel finding that MDD severity is consistently negatively associated with amygdala nuclei, linking volumetric reductions with worsening depressive symptoms.
Keyphrases
- major depressive disorder
- bipolar disorder
- depressive symptoms
- prefrontal cortex
- functional connectivity
- contrast enhanced
- resting state
- magnetic resonance imaging
- temporal lobe epilepsy
- stress induced
- high resolution
- deep learning
- diffusion weighted imaging
- social support
- end stage renal disease
- ejection fraction
- convolutional neural network
- newly diagnosed
- case report
- sleep quality
- computed tomography
- magnetic resonance
- mass spectrometry
- machine learning
- cerebral ischemia
- multiple sclerosis
- patient reported
- subarachnoid hemorrhage
- patient reported outcomes
- physical activity
- brain injury