Predictors of responsiveness to ketamine: An updated systematic review of neuroimaging findings.

A systematic review of fifteen neuroimaging studies identifies potential brain-based markers that could predict which patients with major depressive disorder will respond to ketamine. The anterior cingulate cortex and amygdala, along with their connections to other brain regions, frequently predicted better response. Higher fractional anisotropy in the cingulum, larger hippocampus volume, and a higher Glx/glutamate ratio in the dorsomedial prefrontal cortex also correlated with response. Task-based imaging showed that anterior cingulate cortex activity predicted antidepressant response. The review notes limitations due to differences in assessments, follow-up times, ketamine doses, and imaging methods across studies.

Study at a glance

Abstract

Major depressive disorder (MDD) is a leading cause of disability worldwide, with a significant portion of patients experiencing treatment-resistant depression (TRD). Ketamine, a rapid-acting antidepressant, has shown promise in alleviating symptoms of TRD and suicidality, but variability in treatment response remains a challenge. Identifying neuroimaging biomarkers that predict responsiveness to ketamine could enhance treatment precision and efficacy. We conducted a systematic search on PubMed, Embase, Scopus, and Web of Science databases of neuroimaging studies exploring biomarkers predictive of responsiveness to ketamine in MDD and suicidality. Fifteen studies were included in this updated review. The anterior cingulate cortex (ACC) and the amygdala emerged as significant regions of interest. Notably, connectivity of the pregenual ACC and the amygdala with other brain regions was frequently associated with better response to ketamine. Furthermore, diffusion MRI showed higher fractional anisotropy in cingulum of responders to ketamine. Structural MRI studies, on the other hand, found that hippocampus volume had a significant positive correlation with response to ketamine. Moreover, proton magnetic resonance spectroscopy showed that responders had a higher Glx/glutamate ratio in the dorsomedial/dorsal anterolateral. Finally, also task-based imaging showed that ACC activity was predictive of antidepressant response. This review presents some limitations, including heterogeneity in psychological assessments, follow-up duration, ketamine dosage, and imaging protocols across the included studies. The review identifies the ACC, amygdala, and their connectivity with other brain regions as potential neuroimaging biomarkers for predicting responsiveness to ketamine in MDD. Future studies should aim to standardize methodologies and explore the role of different ketamine administration routes.