BACKGROUND: It would be therapeutically useful to predict clinical response to antidepressant drugs. We evaluated structural magnetic resonance imaging (MRI) and functional MRI (fMRI) data as predictors of symptom change in people with depression. METHODS: Brain structure and function were measured with MRI in 17 patients with major depression immediately before 8 weeks treatment with fluoxetine 20 mg/day. For fMRI, patients were scanned during visual presentation of faces representing different intensities of sadness. Clinical response was measured by change in serial scores on the Hamilton Rating Scale for Depression. Symptom change scores (and baseline symptom severity) were regressed on structural and functional MRI data to map brain regions where grey matter volume, or activation by sad facial affect processing, was significantly associated with symptom change (or baseline severity). RESULTS: Faster rates of symptom improvement were strongly associated with greater grey matter volume in anterior cingulate cortex, insula, and right temporo-parietal cortex. Patients with greater than median grey matter volume in this system had faster rates of improvement and significantly lower residual symptom scores after 8 weeks' treatment. Faster improvement was also predicted by greater functional activation of anterior cingulate cortex. Baseline symptom severity was negatively correlated with greater grey matter volume in dorsal prefrontal and anterior midcingulate regions anatomically distinct from the pregenual and subgenual cingulate regions predicting treatment response. CONCLUSIONS: Structural MRI measurements of anterior cingulate cortex could provide a useful predictor of antidepressant treatment response.
BACKGROUND: It would be therapeutically useful to predict clinical response to antidepressant drugs. We evaluated structural magnetic resonance imaging (MRI) and functional MRI (fMRI) data as predictors of symptom change in people with depression. METHODS: Brain structure and function were measured with MRI in 17 patients with major depression immediately before 8 weeks treatment with fluoxetine 20 mg/day. For fMRI, patients were scanned during visual presentation of faces representing different intensities of sadness. Clinical response was measured by change in serial scores on the Hamilton Rating Scale for Depression. Symptom change scores (and baseline symptom severity) were regressed on structural and functional MRI data to map brain regions where grey matter volume, or activation by sad facial affect processing, was significantly associated with symptom change (or baseline severity). RESULTS: Faster rates of symptom improvement were strongly associated with greater grey matter volume in anterior cingulate cortex, insula, and right temporo-parietal cortex. Patients with greater than median grey matter volume in this system had faster rates of improvement and significantly lower residual symptom scores after 8 weeks' treatment. Faster improvement was also predicted by greater functional activation of anterior cingulate cortex. Baseline symptom severity was negatively correlated with greater grey matter volume in dorsal prefrontal and anterior midcingulate regions anatomically distinct from the pregenual and subgenual cingulate regions predicting treatment response. CONCLUSIONS: Structural MRI measurements of anterior cingulate cortex could provide a useful predictor of antidepressant treatment response.
Authors: Giacomo Salvadore; Allison C Nugent; Herve Lemaitre; David A Luckenbaugh; Ruth Tinsley; Dara M Cannon; Alexander Neumeister; Carlos A Zarate; Wayne C Drevets Journal: Neuroimage Date: 2010-11-10 Impact factor: 6.556
Authors: Deepak K Sarpal; Miklos Argyelan; Delbert G Robinson; Philip R Szeszko; Katherine H Karlsgodt; Majnu John; Noah Weissman; Juan A Gallego; John M Kane; Todd Lencz; Anil K Malhotra Journal: Am J Psychiatry Date: 2015-08-28 Impact factor: 18.112
Authors: Carrie L Masten; Naomi I Eisenberger; Larissa A Borofsky; Jennifer H Pfeifer; Kristin McNealy; John C Mazziotta; Mirella Dapretto Journal: Soc Cogn Affect Neurosci Date: 2009-06 Impact factor: 3.436
Authors: Howard J Aizenstein; Alexander Khalaf; Sarah E Walker; Carmen Andreescu Journal: J Geriatr Psychiatry Neurol Date: 2013-12-30 Impact factor: 2.680
Authors: P Cédric M P Koolschijn; Neeltje E M van Haren; Gerty J L M Lensvelt-Mulders; Hilleke E Hulshoff Pol; René S Kahn Journal: Hum Brain Mapp Date: 2009-11 Impact factor: 5.038