Affiliation: This work was done under Prof. Howard Aizenstein, MD, PhD of the University of Pittsburgh
Summary: When treating major depressive disorder (MDD), the slow behavioral response to treatment often delays a clinician’s attempt to match patients to an effective regimen, causing a significant delay between diagnosis and remission frequently involving multiple unsuccessful trials. While many studies on the treatment of MDD often involve observations about the changes in neural activation during emotional reactivity or regulation tasks, comparatively fewer focus on the predictive utility of identified changes or observe such changes within a timeframe that allows these changes to be used clinically. In a cohort of 49 participants diagnosed with late-life major depression disorder and receiving an open-labeled trial with venlafaxine, we investigated the treatment response predictive capacity of both resting and task-based activations. By utilizing activation profiles both at baseline and a day after a single dose of venlafaxine, we found that we could improve the predictive capacity of baseline clinical factors by 15%.
Published in:
Karim, H. T.*, Wang, M. B.*, Andreescu, C., Tudorascu, D., Butters, M. A., Karp, J. F., ... & Aizenstein, H. J. (2018). Acute trajectories of neural activation predict remission to pharmacotherapy in late-life depression. NeuroImage: Clinical, PubMed PMID: 30013927 (*: equal contribution)
Presented at:
Wang M. B., Karim H., Andreescu C., Tudorascu D., Karp J., Reynolds, C. III, and Aizenstein, H. (2018). “Predicting Remission in a Late-Life Depression Treatment Trial using Baseline and Single-Dose fMRI”. Oral Presentation at American Society of Neuroradiology 2018
Poster presented at the Univ. of Pittsburgh Brain Day, 2017