Magnetic Resonance Spectroscopy in Depressed Subjects Treated With Electroconvulsive Therapy—A Systematic Review of Literature

Electroconvulsive therapy (ECT) is considered to be the most effective acute treatment for otherwise treatment resistant major depressive episodes, and has been used for over 80 years. Still, the underlying mechanism of action is largely unknow. Several studies suggest that ECT affects the cerebral neurotransmitters, such as gamma-aminobutyric acid (GABA) and glutamate. Magnetic resonance spectroscopy (MRS) allows investigators to study neurotransmitters in vivo, and has been used to study neurochemical changes in the brain of patients treated with ECT. Several investigations have been performed on ECT-patients; however, no systematic review has yet summarized these findings. A systematic literature search based on the Prisma guidelines was performed. PubMed (Medline) was used in order to find investigations studying patients that had been treated with ECT and had undergone an MRS examination. A search in the databases Embase, PsycInfo, and Web of Science was also performed, leading to no additional records. A total of 30 records were identified and screened which resulted in 16 original investigations for review. The total number of patients that was included in these studies, ignoring potential overlap of samples in some investigations, was 325. The metabolites reported were N-acetyl aspartate, Choline, Myoinositol, Glutamate and Glutamine, GABA and Creatine. The strongest evidence for neurochemical change related to ECT, was found for N-acetyl aspartate (reduction), which is a marker of neuronal integrity. Increased choline and glutamate following treatment was also commonly reported.publishedVersio

Feasibility of deep learning-based tumor segmentation for target delineation and response assessment in grade-4 glioma using multi-parametric MRI

Background Tumor burden assessment is essential for radiation therapy (RT), treatment response evaluation, and clinical decision-making. However, manual tumor delineation remains laborious and challenging due to radiological complexity. The objective of this study was to investigate the feasibility of the HD-GLIO tool, an ensemble of pre-trained deep learning models based on the nnUNet-algorithm, for tumor segmentation, response prediction, and its potential for clinical deployment. Methods We analyzed the predicted contrast-enhanced (CE) and non-enhancing (NE) HD-GLIO output in 49 multi-parametric MRI examinations from 23 grade-4 glioma patients. The volumes were retrospectively compared to corresponding manual delineations by 2 independent operators, before prospectively testing the feasibility of clinical deployment of HD-GLIO-output to a RT setting. Results For CE, median Dice scores were 0.81 (95% CI 0.71–0.83) and 0.82 (95% CI 0.74–0.84) for operator-1 and operator-2, respectively. For NE, median Dice scores were 0.65 (95% CI 0.56–0,69) and 0.63 (95% CI 0.57–0.67), respectively. Comparing volume sizes, we found excellent intra-class correlation coefficients of 0.90 (P .01) for non-responders, and 0.80 (P = .05) for intermediate/mixed responders. Conclusions HD-GLIO was feasible for RT target delineation and MRI tumor volume assessment. CE/NE tumor-compartment growth correlation showed potential to predict clinical response to treatment.publishedVersio

The effect of electroconvulsive therapy (ECT) on serum tryptophan metabolites

Background: Prior studies suggest that activation of the tryptophan catabolism via the kynurenine pathway by proinflammatory cytokines may be involved in the pathophysiology of depression. Electroconvulsive therapy (ECT) is an effective treatment for major depression (MD) with immunomodulation as one of the proposed modes of action. Objective: The aim of this study was to investigate serum concentrations of tryptophan and kynurenine pathway metabolites in MD patients and healthy controls, and to explore the effect of ECT on components of the kynurenine pathway. Methods: The study included 27 moderately to severely depressed patients referred to ECT. Blood samples were collected prior to treatment and after the completed ECT-series. Baseline samples were also collected from 14 healthy, age- and sex-matched controls. Serum concentrations of tryptophan, kynurenine, 3-hydroxykynurenine (HK), kynurenic acid (KA), xanthurenic acid (XA), anthranilic acid (AA), 3-hydroxyanthranilic acid (HAA), quinolinic acid (QA), picolinic acid (Pic), pyridoxal 5′-phosphat (PLP), riboflavin, neopterin and cotinine were measured. Results: Patients with MD had lower levels of neuroprotective kynurenine-pathway metabolites (KA, XA and Pic) and lower metabolite ratios (KA/Kyn and KA/QA) reflecting reduced neuroprotection compared to controls. The concentration of the inflammatory marker neopterin was increased after ECT, along with Pic and the redox active and immunosuppressive metabolite HAA. Conclusion: In this pilot study, we found increased concentrations of inflammatory marker neopterin and putative neuroprotective kynurenine metabolites HAA and Pic in MD patients after ECT. Further research in larger cohorts is required to conclude whether ECT exerts its therapeutic effects via changes in the kynurenine pathway.publishedVersio

Multimodal multi-center analysis of electroconvulsive therapy effects in depression: Brainwide gray matter increase without functional changes

Background: Electroconvulsive therapy (ECT) is an effective treatment for severe depression and induces gray matter (GM) increases in the brain. Small-scale studies suggest that ECT also leads to changes in brain functioning, but findings are inconsistent. In this study, we investigated the influence of ECT on changes in both brain structure and function and their relation to clinical improvement using multicenter neuroimaging data from the Global ECT-MRI Research Collaboration (GEMRIC). Methods: We analyzed T1-weighted structural magnetic resonance imaging (MRI) and functional resting-state MRI data of 88 individuals (49 male) with depressive episodes before and within one week after ECT. We performed voxel-based morphometry on the structural data and calculated fractional amplitudes of low-frequency fluctuations, regional homogeneity, degree centrality, functional connectomics, and hippocampus connectivity for the functional data in both unimodal and multimodal analyses. Longitudinal effects in the ECT group were compared to repeated measures of healthy controls (n = 27). Results: Wide-spread increases in GM volume were found in patients following ECT. In contrast, no changes in any of the functional measures were observed, and there were no significant differences in structural or functional changes between ECT responders and non-responders. Multimodal analysis revealed that volume increases in the striatum, supplementary motor area and fusiform gyrus were associated with local changes in brain function. Conclusion: These results confirm wide-spread increases in GM volume, but suggest that this is not accompanied by functional changes or associated with clinical response. Instead, focal changes in brain function appear related to individual differences in brain volume increases.publishedVersio

Anterior cingulate gamma-aminobutyric acid concentrations and electroconvulsive therapy

Objective The anticonvulsant hypothesis posits that ECT’s mechanism of action is related to enhancement of endogenous anticonvulsant brain mechanisms. Results of prior studies investigating the role of the inhibitory neurotransmitter gamma‐aminobutyric acid (“GABA+”, GABA and coedited macromolecules) in the pathophysiology and treatment of depression remain inconclusive. The aim of our study was to investigate treatment‐responsive changes of GABA+ in subjects with a depressive episode receiving electroconvulsive therapy (ECT). Methods In total, 41 depressed subjects (DEP) and 35 healthy controls (HC) were recruited at two independent sites in Norway and the USA. MEGA‐PRESS was used for investigation of GABA+ in the anterior cingulate cortex. We assessed longitudinal and cross‐sectional differences between DEP and HC, as well as the relationship between GABA+ change and change in depression severity and number of ECTs. We also assessed longitudinal differences in cognitive performance and GABA+ levels. Results Depressive episode did not show a difference in GABA+ relative to HC (t71 = −0.36, p = .72) or in longitudinal analysis (t36 = 0.97, p = .34). Remitters and nonremitters did not show longitudinal (t36 = 1.12, p = .27) or cross‐sectional differences in GABA+. GABA+ levels were not related to changes in antidepressant response (t35 = 1.12, p = .27) or treatment number (t36 = 0.05, p = .96). An association between cognitive performance and GABA+ levels was found in DEP that completed cognitive effortful testing (t18 = 2.4, p = .03). Conclusion Our results failed to support GABA as a marker for depression and abnormal mood state and provide no support for the anticonvulsant hypothesis of ECT. ECT‐induced change in GABA concentrations may be related to change in cognitive function.publishedVersio

Sequential bortezomib and temozolomide treatment promotes immunological responses in glioblastoma patients with positive clinical outcomes: A phase 1B study

Background Glioblastoma (GBM) is an aggressive malignant brain tumor where median survival is approximately 15 months after best available multimodal treatment. Recurrence is inevitable, largely due to O6 methylguanine DNA methyltransferase (MGMT) that renders the tumors resistant to temozolomide (TMZ). We hypothesized that pretreatment with bortezomib (BTZ) 48 hours prior to TMZ to deplete MGMT levels would be safe and tolerated by patients with recurrent GBM harboring unmethylated MGMT promoter. The secondary objective was to investigate whether 26S proteasome blockade may enhance differentiation of cytotoxic immune subsets to impact treatment responses measured by radiological criteria and clinical outcomes. Methods Ten patients received intravenous BTZ 1.3 mg/m2 on days 1, 4, and 7 during each 4th weekly TMZ‐chemotherapy starting on day 3 and escalated from 150 mg/m2 per oral 5 days/wk via 175 to 200 mg/m2 in cycles 1, 2, and 3, respectively. Adverse events and quality of life were evaluated by CTCAE and EQ‐5D‐5L questionnaire, and immunological biomarkers evaluated by flow cytometry and Luminex enzyme‐linked immunosorbent assay. Results Sequential BTZ + TMZ therapy was safe and well tolerated. Pain and performance of daily activities had greatest impact on patients' self‐reported quality of life and were inversely correlated with Karnofsky performance status. Patients segregated a priori into three groups, where group 1 displayed stable clinical symptoms and/or slower magnetic resonance imaging radiological progression, expanded CD4+ effector T‐cells that attenuated cytotoxic T‐lymphocyte associated protein‐4 and PD‐1 expression and secreted interferon γ and tumor necrosis factor α in situ and ex vivo upon stimulation with PMA/ionomycin. In contrast, rapidly progressing group 2 patients exhibited tolerised T‐cell phenotypes characterized by fourfold to sixfold higher interleukin 4 (IL‐4) and IL‐10 Th‐2 cytokines after BTZ + TMZ treatment, where group 3 patients exhibited intermediate clinical/radiological responses. Conclusion Sequential BTZ + TMZ treatment is safe and promotes Th1‐driven immunological responses in selected patients with improved clinical outcomes (Clinicaltrial.gov (NCT03643549)).publishedVersio

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

Background Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. Objective We investigated whether there are consistent changes in effective resting-state connectivity. Methods This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. Results Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. Conclusions A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.publishedVersio

Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: A multicenter machine learning analysis

Background Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting. Methods Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier. Results Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82–0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70–0.73 AUC). Conclusions These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible.publishedVersio

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. OBJECTIVE: We investigated whether there are consistent changes in effective resting-state connectivity. METHODS: This multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. RESULTS: Compared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. CONCLUSIONS: A beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research

Volume of the human hippocampus and clinical response following electroconvulsive therapy

BACKGROUND: Hippocampal enlargements are commonly reported after electroconvulsive therapy (ECT). To clarify mechanisms, we examined if ECT-induced hippocampal volume change relates to dose (number of ECT sessions and electrode placement) and acts as a biomarker of clinical outcome. METHODS: Longitudinal neuroimaging and clinical data from 10 independent sites participating in the Global ECT-Magnetic Resonance Imaging Research Collaboration (GEMRIC) were obtained for mega-analysis. Hippocampal volumes were extracted from structural magnetic resonance images, acquired before and after patients (n = 281) experiencing a major depressive episode completed an ECT treatment series using right unilateral and bilateral stimulation. Untreated nondepressed control subjects (n = 95) were scanned twice. RESULTS: The linear component of hippocampal volume change was 0.28% (SE 0.08) per ECT session (p < .001). Volume change varied by electrode placement in the left hippocampus (bilateral, 3.3 +/- 2.2%, d = 1.5; right unilateral, 1.6 +/- 2.1%, d = 0.8; p < .0001) but not the right hippocampus (bilateral, 3.0 +/- 1.7%, d = 1.8; right unilateral, 2.7 +/- 2.0%, d = 1.4; p = .36). Volume change for electrode placement per ECT session varied similarly by hemisphere. Individuals with greater treatment-related volume increases had poorer outcomes (Montgomery-Asberg Depression Rating Scale change -1.0 [SE 0.35], per 1% volume increase, p = .005), although the effects were not significant after controlling for ECT number (slope -0.69 [SE 0.38], p = .069). CONCLUSIONS: The number of ECT sessions and electrode placement impacts the extent and laterality of hippocampal enlargement, but volume change is not positively associated with clinical outcome. The results suggest that the high efficacy of ECT is not explained by hippocampal enlargement, which alone might not serve as a viable biomarker for treatment outcome