Imaging helps guide antidepressant medication choices
Biomarkers from brain MRI scans could soon help guide medication decisions for patients seeking mental health treatment.
A new analysis in JAMA Network Open details efforts to identify patterns on neuroimaging that could offer clues into how patients are responding to antidepressants. Using structural and functional resting-state MRI scans, the team examined how two different medications—sertraline and escitalopram—affect certain regions of the brain associated with emotional regulation, reward processing and attention.
Experts involved in the study hope their findings offer prescribers a more objective way to measure these medications' efficacy.
“Treatment of psychiatric conditions, including major depressive disorder (MDD) often fails, with more than one-half of patients with MDD not responding to first-line antidepressant treatment,” Diego A. Pizzagalli, PhD, from the Center for Depression, Anxiety and Stress Research at McLean Hospital in Massachusetts, and colleagues noted. “Leveraging machine learning in prediction of treatment response promises to accelerate symptom reduction.”
While some studies have yielded promising results, they lack generalizability, thus limiting efforts to understand their true clinical utility. To address this, researchers analyzed data across two different trials comparing the outcomes of patients with MDD who were treated with either a placebo or antidepressant. Both trials utilized imaging alongside clinical factors to determine treatment efficacy.
On imaging, the group focused on the functional connectivity of the dorsal anterior cingulate (dACC), with depression severity scores used in conjunction with image findings to establish relationships. Patients completed scans before and during treatment to monitor changes in functional connectivity patterns.
The use of imaging biomarkers related to connectivity to and from the dACC, when combined with clinical factors and depression severity scores, proved to be more accurate than clinical markers alone in gauging treatment efficacy.
“The circuit identified as predictive of treatment response included the anticorrelation between dACC and dlPFC (dorsolateral prefrontal cortex) as well as the angular gyrus,” the authors explained. “The dACC seed included posterior Brodmann area 24 and the anterior Brodmann area 32 prime. It is thus at the intersection between the hot and cold subdivisions of the dACC. These findings fit theories proposing that top-down emotional regulation is achieved by prefrontal regions regulating the ACC and amygdala activity, regions typically recruited by emotional stimuli.”
These results were generalizable across both trials, the group added. While more research is needed to further validate the team’s findings, the biomarkers identified have the potential to eventually “help connect patients with treatments that work best for them,” the authors concluded.
In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She began covering the medical imaging industry for Innovate Healthcare in 2021.