Poster No:
1286
Submission Type:
Abstract Submission
Authors:
Yeun Kim1, Paloma Pfeiffer1, Brandon Taraku1, Randall Espinoza2, Katherine Narr1, Artemis Zavaliangos-Petropulu1
Institutions:
1Ahmanson-Lovelace Brain Mapping Center, UCLA, Los Angeles, CA, 2Jane and Terry Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA
First Author:
Yeun Kim
Ahmanson-Lovelace Brain Mapping Center, UCLA
Los Angeles, CA
Co-Author(s):
Paloma Pfeiffer
Ahmanson-Lovelace Brain Mapping Center, UCLA
Los Angeles, CA
Brandon Taraku
Ahmanson-Lovelace Brain Mapping Center, UCLA
Los Angeles, CA
Randall Espinoza
Jane and Terry Semel Institute for Neuroscience and Human Behavior, UCLA
Los Angeles, CA
Katherine Narr
Ahmanson-Lovelace Brain Mapping Center, UCLA
Los Angeles, CA
Introduction:
Electroconvulsive therapy (ECT) is one of the most effective FDA-approved techniques for treating treatment-resistant major depressive disorder (MDD) (Pagnin et al., 2008). However, ECT's underlying effects on the brain are not yet clearly understood. Previous findings have shown transient increases in hippocampal grey matter (GM) volume post-treatment in MDD (Bouckaert et al., 2016) that have been attributed to neuroplasticity or inflammation (Ousdal et al., 2020). To further investigate the underlying biological changes of hippocampal GM, we here analyze diffusion-weighted MRI (dMRI) data of MDD patients pre- and post-ECT using the neurite orientation dispersion and density imaging (NODDI) model (Zhang et al., 2012).
Methods:
Patients with MDD (N=30; age=36.90土14.06; 12F) had brain MRI data and 17-item Hamilton Depression Rating Scale (HAMD) (Hamilton, 1960) scores collected at baseline (BL) and post-index (PI; average 13 ECT sessions). A subset of participants (N=19; age=34.37土11.20; 7F) also had data collected at a follow-up time point (5-weeks after last treatment). MRI sequences adhered to the Human Connectome Project (HCP) protocol and included T1-, T2-, and diffusion-weighted MRI, which were acquired using a Siemens 3T Prisma at UCLA. The structural and diffusion data had 0.8mm3 and 1.5mm3 voxel sizes, respectively. The dMRIs were collected using 2 phase encoding polarities and 2 diffusion weightings (b=1500 and 3000 s/mm2). All imaging data were preprocessed using the HCP minimal preprocessing pipeline (Glasser et al., 2013). The processed dMRI data in T1 space were used to render orientation dispersion index (ODI) and neurite density (NDI), and cerebrospinal fluid volume fraction (FISO) maps using the NODDI Matlab Toolbox (Zhang et al., 2012). The output ODI and NDI images were nonlinearly coregistered to MNI space using the NODDI-GBSS pipeline (Nazeri et al., 2015). The average ODI and NDI values of the right and left gross hippocampi were then extracted using the Harvard-Oxford subcortical atlas (Fig. 1A) (Makris et al., 2006). A mixed-effects GLM tested for the effect of time from BL to PI for ODI and NDI adjusting for age and sex and including participant as a random effect. Linear regression tested for associations between percent change in ODI and NDI values (PI-BL) and percent change in HAMD scores, also adjusting for age and sex. A mixed-effects model also tested for longitudinal effects in participants who completed all 3 assessment sessions, with post-hoc t-tests comparing effects between timepoints pairwise. All models were Bonferroni corrected (0.05/2 tests, p<0.025).
Results:
HAMD significantly improved by PI (p-value=0.00013) (Fig. 1B). From BL to PI, ODI significantly increased (left: p=0.01; d=1.003, right: p=0.002; d=-0.72), whereas the right hippocampus NDI decreased (p=0.008; d=-1.05) (Fig. 1C). A trending percent change (PI-BL) in left hippocampal ODI was negatively correlated with improved HAMD scores (p=0.03; d=0.89) (Fig. 1D). In the subset of participants with 3 timepoints, we observed significant time effects on hippocampal ODI values (p=0.02, f=4.42) in the right hemisphere only, driven primarily by changes from PI to follow-up (p=0.004, t=3.35) (Fig. 2A). Significant NDI changes were not observed in this subset of participants (Fig. 2B).
Conclusions:
ECT led to significant improvements in depressive symptoms. Hippocampal ODI increased during ECT, but was negatively associated with ECT's antidepressant effects for the left hippocampus, and returned towards baseline at 5-wks for the right hippocampus. Decreased right hippocampal NDI was also observed following ECT in the full sample. These results suggest that microstructural alterations in the hippocampus observed using dMRI add unique insights into the biological mechanisms underlying ECT's antidepressant effects and those potentially related to seizure therapy itself.
Brain Stimulation:
Non-Invasive Stimulation Methods Other 2
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 1
Keywords:
Other - Electroconvulsive therapy; Depression; DMRI; Hippocampus
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
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Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Patients
Was this research conducted in the United States?
Yes
Are you Internal Review Board (IRB) certified?
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Were any human subjects research approved by the relevant Institutional Review Board or ethics panel?
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Were any animal research approved by the relevant IACUC or other animal research panel?
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Please indicate which methods were used in your research:
Structural MRI
Diffusion MRI
Other, Please specify
-
Electroconvulsive therapy
For human MRI, what field strength scanner do you use?
3.0T
Which processing packages did you use for your study?
FSL
Free Surfer
Provide references using APA citation style.
Bouckaert, F., De Winter, F. L., Emsell, L., Dols, A., Rhebergen, D., Wampers, M., ... & Vandenbulcke, M. (2016). Grey matter volume increase following electroconvulsive therapy in patients with late life depression: a longitudinal MRI study. Journal of Psychiatry and Neuroscience, 41(2), 105-114.
Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., Van Essen, D. C., Jenkinson, M., & WU-Minn HCP Consortium. (2013). The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage, 80, 105–124.
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23, 56–62.
Makris, N., Goldstein, J. M., Kennedy, D., Hodge, S. M., Caviness, V. S., Faraone, S. V., ... & Seidman, L. J. (2006). Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophrenia Research, 83(2-3), 155-171.
Nazeri, A., Chakravarty, M. M., Rotenberg, D. J., Rajji, T. K., Rathi, Y., Michailovich, O. V., & Voineskos, A. N. (2015). Functional consequences of neurite orientation dispersion and density in humans across the adult lifespan. Journal of Neuroscience, 35(4), 1753-1762.
Ousdal, O. T., Argyelan, M., Narr, K. L., Abbott, C., Wade, B., Vandenbulcke, M., ... & Sienaert, P. (2020). Brain changes induced by electroconvulsive therapy are broadly distributed. Biological psychiatry, 87(5), 451-461.
Pagnin, D., de Queiroz, V., Pini, S., & Cassano, G. B. (2008). Efficacy of ECT in depression: a meta-analytic review. Focus, 6(1), 155-162.
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage, 61(4), 1000-1016.
No