The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy

Analyzing Fractal Dimension in Electroconvulsive Therapy: Unraveling Complexity in Structural and Functional Neuroimaging

BACKGROUND

Numerous studies show that electroconvulsive therapy (ECT) induces hippocampal neuroplasticity, but findings are inconsistent regarding its clinical relevance. This study aims to investigate ECT-induced plasticity of anterior and posterior hippocampi using mathematical complexity measures in neuroimaging, namely Higuchi's fractal dimension (HFD) for fMRI time series and the fractal dimension of cortical morphology (FD-CM). Furthermore, we explore the potential of these complexity measures to predict ECT treatment response.

METHODS

Twenty patients with a current depressive episode (16 with major depressive disorder and 4 with bipolar disorder) underwent MRI-scans before and after an ECT-series. Twenty healthy controls matched for age and sex were also scanned twice for comparison purposes. Resting-state fMRI data were processed, and HFD was computed for anterior and posterior hippocampi. Group-by-time effects for HFD in anterior and posterior hippocampi were calculated and correlations between HFD changes and improvement in depression severity were examined. For FD-CM analyses, we preprocessed structural MRI with CAT12's surface-based methods. We explored group-by-time effects for FD-CM and the predictive value of baseline HFD and FD-CM for treatment outcome.

RESULTS

Patients exhibited a significant increase in bilateral hippocampal HFD from baseline to follow-up scans. Right anterior hippocampal HFD increase was associated with reductions in depression severity. We found no group differences and group-by-time effects in FD-CM. After applying a whole-brain regression analysis, we found that baseline FD-CM in the left temporal pole predicted reduction of overall depression severity after ECT. Baseline hippocampal HFD did not predict treatment outcome.

CONCLUSION

This study suggests that HFD and FD-CM are promising imaging markers to investigate ECT-induced neuroplasticity associated with treatment response.

Machine Learning in Electroconvulsive Therapy: A Systematic Review

ABSTRACT

Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine learning approaches due to the large data sets with data captured through electroencephalography (EEG) and other objective measures. A systematic review of 6 databases led to the full-text examination of 26 articles using machine learning approaches in examining data predicting response to ECT treatment. The identified articles used a wide variety of data types covering structural and functional imaging data (n = 15), clinical data (n = 5), a combination of clinical and imaging data (n = 2), EEG (n = 3), and social media posts (n = 1). The clinical indications in which response prediction was assessed were depression (n = 21) and psychosis (n = 4). Changes in multiple anatomical regions in the brain were identified as holding a predictive value for response to ECT. These primarily centered on the limbic system and associated networks. Clinical features predicting good response to ECT in depression included shorter duration, lower severity, higher medication dose, psychotic features, low cortisol levels, and positive family history. It has also been possible to predict the likelihood of relapse of readmission with psychosis after ECT treatment, including a better response if higher transfer entropy was calculated from EEG signals. A transdisciplinary approach with an international consortium collecting a wide range of retrospective and prospective data may help to refine and extend these outcomes and translate them into clinical practice.

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.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Longitudinal resting-state network connectivity changes in electroconvulsive therapy patients compared to healthy controls

OBJECTIVE

Electroconvulsive therapy (ECT) is effective for major depressive episodes. Understanding of underlying mechanisms has been increased by examining changes of brain connectivity but studies often do not correct for test-retest variability in healthy controls (HC). In this study, we investigated changes in resting-state networks after ECT in a multicenter study.

METHODS

Functional resting-state magnetic resonance imaging data, acquired before start and within one week after ECT, from 90 depressed patients were analyzed, as well as longitudinal data of 24 HC. Group-information guided independent component analysis (GIG-ICA) was used to spatially restrict decomposition to twelve canonical resting-state networks. Selected networks of interest were the default mode network (DMN), salience network (SN), and left and right frontoparietal network (LFPN, and RFPN). Whole-brain voxel-wise analyses were used to assess group differences at baseline, group by time interactions, and correlations with treatment effectiveness. In addition, between-network connectivity and within-network strengths were computed.

RESULTS

Within-network strength of the DMN was lower at baseline in ECT patients which increased after ECT compared to HC, after which no differences were detected. At baseline, ECT patients showed lower whole-brain voxel-wise DMN connectivity in the precuneus. Increase of within-network strength of the LFPN was correlated with treatment effectiveness. We did not find whole-brain voxel-wise or between-network changes.

CONCLUSION

DMN within-network connectivity normalized after ECT. Within-network increase of the LFPN in ECT patients was correlated with higher treatment effectiveness. In contrast to earlier studies, we found no whole-brain voxel-wise changes, which highlights the necessity to account for test-retest effects.

What Can We Tell About the Effect of Electroconvulsive Therapy on the Human Hippocampus?

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment, although its mechanisms of action remain unclear. Since 2010, several structural magnetic resonance imaging studies based on a neuroplastic hypothesis have consistently reported increases in the hippocampal volume following ECT. Moreover, volume increases in the human dentate gyrus, where neurogenesis occurs, have also been reported. These results are in line with the preclinical findings of ECT-induced neuroplastic changes, including neurogenesis, gliogenesis, synaptogenesis, and angiogenesis, in rodents and nonhuman primates. Despite this robust evidence of an effect of ECT on hippocampal plasticity, the clinical relevance of these human hippocampal changes continues to be questioned. This narrative review summarizes recent findings regarding ECT-induced hippocampal volume changes. Furthermore, this review also discusses methodological considerations and future directions in this field.

Neurobiological mechanisms of ECT and TMS treatment in depression: study protocol of a multimodal magnetic resonance investigation

BACKGROUND

Noninvasive neurostimulation treatments are increasingly being used to treat major depression, which is a common cause of disability worldwide. While electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) are both effective in treating depressive episodes, their mechanisms of action are, however, not completely understood. ECT is given under general anesthesia, where an electrical pulse is administered through electrodes placed on the patient's head to trigger a seizure. ECT is used for the most severe cases of depression and is usually not prescribed before other options have failed. With TMS, brain stimulation is achieved through rapidly changing magnetic fields that induce electric currents underneath a ferromagnetic coil. Its efficacy in depressive episodes has been well documented. This project aims to identify the neurobiological underpinnings of both the effects and side effects of the neurostimulation techniques ECT and TMS.

METHODS

The study will utilize a pre-post case control longitudinal design. The sample will consist of 150 subjects: 100 patients (bipolar and major depressive disorder) who are treated with either ECT (N = 50) or TMS (N = 50) and matched healthy controls (N = 50) not receiving any treatment. All participants will undergo multimodal magnetic resonance imaging (MRI) as well as neuropsychological and clinical assessments at multiple time points before, during and after treatment. Arterial spin labeling MRI at baseline will be used to test whether brain perfusion can predict outcomes. Signs of brain disruption, potentiation and rewiring will be explored with resting-state functional MRI, magnetic resonance spectroscopy and multishell diffusion weighted imaging (DWI). Clinical outcome will be measured by clinician assessed and patient reported outcome measures. Memory-related side effects will be investigated, and specific tests of spatial navigation to test hippocampal function will be administered both before and after treatment. Blood samples will be stored in a biobank for future analyses. The observation time is 6 months. Data will be explored in light of the recently proposed disrupt, potentiate and rewire (DPR) hypothesis.

DISCUSSION

The study will contribute data and novel analyses important for our understanding of neurostimulation as well as for the development of enhanced and more personalized treatment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05135897.

Magnetic Waves vs. Electric Shocks: A Non-Inferiority Study of Magnetic Seizure Therapy and Electroconvulsive Therapy in Treatment-Resistant Depression

Treatment-resistant depression (TRD), characterized by the failure to achieve symptomatic remission despite multiple pharmacotherapeutic treatments, poses a significant challenge for clinicians. Electroconvulsive therapy (ECT) is an effective but limited option due to its cognitive side effects. In this context, magnetic seizure therapy (MST) has emerged as a promising alternative, offering comparable antidepressant efficacy with better cognitive outcomes. However, the clinical outcomes and cognitive effects of MST require further investigation. This double-blinded, randomized, non-inferiority study aims to compare the efficacy, tolerability, cognitive adverse effects, and neurophysiological biomarkers of MST with bilateral ECT (BT ECT) in patients with TRD. This study will employ multimodal nuclear magnetic resonance imaging (MRI) and serum neurotrophic markers to gain insight into the neurobiological basis of seizure therapy. Additionally, neurophysiological biomarkers will be evaluated as secondary outcomes to predict the antidepressant and cognitive effects of both techniques. The study design, recruitment methods, ethical considerations, eligibility criteria, interventions, and blinding procedures are described. The expected outcomes will advance the field by offering a potential alternative to ECT with improved cognitive outcomes and a better understanding of the underlying pathophysiology of depression and antidepressant therapies.

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.

Electroconvulsive therapy triggers a reversible decrease in brain N-acetylaspartate

Introduction

Based on previous research on electroconvulsive therapy (ECT) we have proposed a model where disruption, potentiation, and rewiring of brain networks occur in sequence and serve as the underlying therapeutic mechanism of ECT. This model implies that a temporary disturbance of neuronal networks (disruption) is followed by a trophic effect (potentiation), which enables the rewiring of neuronal circuits to a more euthymic functioning brain. We hypothesized that disruption of neuronal networks could trigger biochemical alterations leading to a temporary decrease in N-acetylaspartate (tNAA, considered a marker of neuronal integrity), while choline (a membrane component), myo-Inositol (mI, astroglia marker), and glutamate/glutamine (Glx, excitatory neurotransmitter) were postulated to increase. Previous magnetic resonance spectroscopy studies, reporting diverse findings, have used two different referencing methods - creatine ratios and tissue corrected values referenced to water - for the quantification of brain metabolites. Changes in creatine during ECT have also been reported, which may confound estimates adopting this as an internal reference.

Methods

Using MR spectroscopy, we investigated 31 moderately to severely depressed patients and 19 healthy controls before, during, and after ECT or at similar time points (for controls). We tested whether biochemical alterations in tNAA, choline, mI, and Glx lend support to the disrupt, potentiate, and rewire hypothesis. We used both creatine ratios and water-scaled values for the quantification of brain metabolites to validate the results across referencing methods.

Results

Levels of tNAA in the anterior cingulate cortex decreased after an ECT treatment series (average 10.6 sessions) by 6% (p = 0.007, creatine ratio) and 3% (p = 0.02, water referenced) but returned to baseline 6 months after ECT. Compared to after treatment series tNAA levels at 6-month follow-up had increased in both creatine ratio (+6%, p < 0.001) and water referenced data (+7%, p < 0.001). Findings for other brain metabolites varied and could not be validated across referencing methods.

Discussion

Our findings suggest that prior research must be interpreted with care, as several referencing and processing methods have been used in the past. Yet, the results for tNAA were robust across quantification methods and concur with relevant parts of the disrupt, potentiate, and rewire model.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this common causal network (CCN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis (Principal Component Analysis, PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CCN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CCN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes. This evidence further supports that treatment interventions converge on a CCN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Electroconvulsive Therapy: Mechanisms of Action, Clinical Considerations, and Future Directions

LEARNING OBJECTIVES

• Outline and discuss the fundamental physiologic, cellular, and molecular mechanisms of ECT to devise strategies to optimize therapeutic outcomes• Summarize the overview of ECT, its efficacy in treating depression, the known effects on cognition, evidence of mechanisms, and future directions.

ABSTRACT

Electroconvulsive therapy (ECT) is the most effective treatment for a variety of psychiatric illnesses, including treatment-resistant depression, bipolar depression, mania, catatonia, and clozapine-resistant schizophrenia. ECT is a medical and psychiatric procedure whereby electrical current is delivered to the brain under general anesthesia to induce a generalized seizure. ECT has evolved a great deal since the 1930s. Though it has been optimized for safety and to reduce adverse effects on cognition, issues persist. There is a need to understand fundamental physiologic, cellular, and molecular mechanisms of ECT to devise strategies to optimize therapeutic outcomes. Clinical trials that set out to adjust parameters, electrode placement, adjunctive medications, and patient selection are critical steps towards the goal of improving outcomes with ECT. This narrative review provides an overview of ECT, its efficacy in treating depression, its known effects on cognition, evidence of its mechanisms, and future directions.

Clinical Improvement in Depression and Cognitive Deficit Following Electroconvulsive Therapy

Electroconvulsive therapy (ECT) is a long-standing treatment choice for disorders such as depression when pharmacological treatments have failed. However, a major drawback of ECT is its cognitive side effects. While numerous studies have investigated the therapeutic effects of ECT and its mechanism, much less research has been conducted regarding the mechanism behind the cognitive side effects of ECT. As both clinical remission and cognitive deficits occur after ECT, it is possible that both may share a common mechanism. This review highlights studies related to ECT as well as those investigating the mechanism of its outcomes. The process underlying these effects may lie within BDNF and NMDA signaling. Edema in the astrocytes may also be responsible for the adverse cognitive effects and is mediated by metabotropic glutamate receptor 5 and the protein Homer1a.

Sex-specifics of ECT outcome

OBJECTIVE

Electroconvulsive therapy (ECT) is the most effective treatment for patients with severe major depressive disorder (MDD). Given the known sex differences in MDD, improved knowledge may provide more sex-specific recommendations in clinical guidelines and improve outcome. In the present study we examine sex differences in ECT outcome and its predictors.

METHODS

Clinical data from 20 independent sites participating in the Global ECT-MRI Research Collaboration (GEMRIC) were obtained for analysis, totaling 500 patients with MDD (58.6 % women) with a mean age of 54.8 years. Severity of depression before and after ECT was assessed with validated depression scales. Remission was defined as a HAM-D score of 7 points or below after ECT. Variables associated with remission were selected based on literature (i.e. depression severity at baseline, age, duration of index episode, and presence of psychotic symptoms).

RESULTS

Remission rates of ECT were independent of sex, 48.0 % in women and 45.7 % in men (X²(1) = 0.2, p = 0.70). In the logistic regression analyses, a shorter index duration was identified as a sex-specific predictor for ECT outcome in women (X²(1) = 7.05, p = 0.01). The corresponding predictive margins did show overlapping confidence intervals for men and women.

CONCLUSION

The evidence provided by our study suggests that ECT as a biological treatment for MDD is equally effective in women and men. A shorter duration of index episode was an additional sex- specific predictor for remission in women. Future research should establish whether the confidence intervals for the corresponding predictive margins are overlapping, as we find, or not.

Electroconvulsive therapy for treatment-resistant depression

Electroconvulsive therapy (ECT), the oldest brain stimulation procedure in psychiatry, is associated with rapid response and remission in majority of patients with resistant, severe, and sometimes life-threatening depression. ECT has been included as an essential component in the definition of treatment-resistant depression (TRD) to display the course and diversification of TRD. On the other hand, ECT remains the treatment of choice for the most severe incapacitating forms of TRD and is a cost-effective treatment. In this chapter, we reviewed some essential studies, meta-analysis, and expert guidelines regarding ECT in TRD. ECT should not be considered as a treatment of last resort, and its administration should be considered on the basis of individual patient and illness factors. The clinical role of ECT vs other neurostimulation treatments for TRD, that is, repetitive transcranial magnetic stimulation, were also explored. Much effort has been directed toward the clinical and basic research about mechanisms of action of ECT in depression. A thorough understanding of the neurobiological effects of ECT may increase our understanding of its therapeutic effects, ultimately leading to improved patient care. We also showed that the distinct mechanisms of ECT in biological treatments of major depressive disorder (MDD) and some recent approaches to understand this most common psychiatric disorder. ECT should remain a standard part of modern psychiatric medicine. We recommend a more careful and thoughtful application of this traditional but effective technology.

Measurement fidelity of clinical assessment methods in a global study on identifying reproducible brain signatures of obsessive-compulsive disorder

OBJECTIVE

To describe the steps of ensuring measurement fidelity of core clinical measures in a five-country study on brain signatures of obsessive-compulsive disorder (OCD).

METHOD

We collected data using standardized instruments, which included the Yale-Brown Obsessive-Compulsive Scale (YBOCS), the Dimensional YBOCS (DYBOCS), the Brown Assessment of Beliefs Scale (BABS), the 17-item Hamilton Depression Scale (HAM-D), the Hamilton Anxiety Scale (HAM-A), and the Structured Clinical Interview for DSM-5 (SCID). Steps to ensure measurement fidelity included translating instruments, developing a clinical decision manual, and continuing reliability training with 11-13 transcripts of each instrument by 13 independent evaluators across sites over 4 years. We use multigroup confirmatory factor analysis (MGCFA) to report interrater reliability (IRR) among the evaluators and factor structure for each scale in 206 participants with OCD.

RESULTS

The overall IRR for most scales was high (ICC > 0.94) and remained good to excellent throughout the study. Consistent factor structures (configural invariance) were found for all instruments across the sites, while similarity in the factor loadings for the items (metric invariance) could be established only for the DYBOCS and the BABS.

CONCLUSIONS

It is feasible to achieve measurement fidelity of clinical measures in multisite, multilinguistic global studies, despite the challenges inherent to such endeavors. Future studies should not only report IRR but also consider reporting methods of standardization of data collection and measurement invariance to identify factor structures of core clinical measures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Consultation-Liaison Case Conference: Malignantly Catatonic and Unable to Receive Electroconvulsive Therapy

We present the case of a 65-year-old female with a past psychiatric history of obsessive-compulsive disorder and anxiety who recently underwent diagnostic laparoscopy in the setting of a recent computerized tomography scan revealing a peritoneal mass. Postoperatively, she was delirious and soon found to be malignantly catatonic. This patient's treatment was complicated by an acute stroke, which was a relative contraindication for electroconvulsive therapy. Top experts in the consultation-liaison psychiatry and electroconvulsive therapy fields provide guidance for this clinical scenario based on their experience and a review of the available literature. Key teaching points include a review of diagnosing and treating catatonia, a review of electroconvulsive therapy for the treatment of catatonia, as well as a review of the role of the consultation-liaison psychiatrist in medically complex cases. Specifically, we offer guidance in treating patients that have malignant catatonia when electroconvulsive therapy is unavailable.

Electroconvulsive therapy effects on anhedonia and reward circuitry anatomy: A dimensional structural neuroimaging approach

BACKGROUND

Anhedonia is a core symptom of major depressive disorder (MDD) resulting from maladaptive reward processing. Electroconvulsive therapy (ECT) is an effective treatment for patients with MDD. No previous neuroimaging studies have taken a dimensional approach to assess whether ECT-induced volume changes are specifically related to improvements in anhedonia and positive valence emotional constructs. We aimed to assess the relationship between ECT-induced brain volumetric changes and improvement in anhedonia and reward processing in patients with MDD.

METHODS

We evaluated 15 patients with MDD before and after ECT. We used magnetic resonance imaging, clinical scales (i.e., Quick Inventory of Depressive Symptomatology for syndromal depression severity and Snaith-Hamilton Pleasure Scale for anhedonia) and the Temporal Experience of Pleasure Scale for anticipatory and consummatory experiences of pleasure. We identified 5 regions of interest within the reward circuit and a 6th control region relevant for MDD but not core to the reward system (Brodmann Area 25).

RESULTS

Anhedonia, anticipatory and consummatory reward processing improved after ECT. Volume increases within the right reward system separated anhedonia responders and non-responders. Improvement in anticipatory (but not consummatory) reward correlated with increases in volume in hippocampus, amygdala, ventral tegmental area and nucleus accumbens.

LIMITATIONS

We evaluated a modest sample size of patients with concurrent pharmacological treatment using a subjective psychometric assessment.

CONCLUSIONS

We highlight the importance of a dimensional and circuit-based approach to understanding target engagement and the mechanism of action of ECT, with the goal to define symptom- and circuit-specific response biomarkers for device neuromodulation therapies.

National Network of Depression Centers' Recommendations on Harmonizing Clinical Documentation of Electroconvulsive Therapy

ABSTRACT

Electroconvulsive therapy (ECT) is a highly therapeutic and cost-effective treatment for severe and/or treatment-resistant major depression. However, because of the varied clinical practices, there is a great deal of heterogeneity in how ECT is delivered and documented. This represents both an opportunity to study how differences in implementation influence clinical outcomes and a challenge for carrying out coordinated quality improvement and research efforts across multiple ECT centers. The National Network of Depression Centers, a consortium of 26+ US academic medical centers of excellence providing care for patients with mood disorders, formed a task group with the goals of promoting best clinical practices for the delivery of ECT and to facilitate large-scale, multisite quality improvement and research to advance more effective and safe use of this treatment modality. The National Network of Depression Centers Task Group on ECT set out to define best practices for harmonizing the clinical documentation of ECT across treatment centers to promote clinical interoperability and facilitate a nationwide collaboration that would enable multisite quality improvement and longitudinal research in real-world settings. This article reports on the work of this effort. It focuses on the use of ECT for major depressive disorder, which accounts for the majority of ECT referrals in most countries. However, most of the recommendations on clinical documentation proposed herein will be applicable to the use of ECT for any of its indications.

The Association Between Sample and Treatment Characteristics and the Efficacy of Repetitive Transcranial Magnetic Stimulation in Depression: A Meta-analysis and Meta-regression of Sham-controlled Trials

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a form of non-invasive neuromodulation that is increasingly used to treat major depressive disorder (MDD). However, treatment with rTMS could be optimized by identifying optimal treatment parameters or characteristics of patients that are most likely to benefit. This meta-analysis and meta-regression aims to identify sample and treatment characteristics that are associated with change in depressive symptom level, treatment response and remission.

METHODS

The databases PubMed, Embase, Web of Science and Cochrane library were searched for randomized controlled trials (RCTs) reporting on the therapeutic efficacy of high-frequent, low-frequent, or bilateral rTMS for MDD compared to sham. Study and sample characteristics as well as rTMS parameters and outcome variables were extracted. Effect sizes were calculated for change in depression score and risk ratios for response and remission.

RESULTS

Sixty-five RCTs with a total of 2982 subjects were included in this meta-analysis. Active rTMS resulted in a larger depressive symptom reduction than sham protocol (Hedges' g = -0.791 95% CI -0.977; -0.605). Risk ratios for response and remission were 2.378 (95% CI 1.882; 3.005) and 2.450 (95% CI 1.779; 3.375), respectively. We found no significant association between sample and treatment parameters and rTMS efficacy.

CONCLUSIONS

rTMS is an efficacious treatment for MDD. No associations between sample or treatment characteristics and efficacy were found, for which we caution that publication bias, heterogeneity and lack of consistency in the definition of remission might bias these latter null findings. Our results are clinically relevant and support the use of rTMS as a non-invasive and effective treatment option for depression.

Parsing the Network Mechanisms of Electroconvulsive Therapy

Electroconvulsive therapy (ECT) is one of the oldest and most effective forms of neurostimulation, wherein electrical current is used to elicit brief, generalized seizures under general anesthesia. When electrodes are positioned to target frontotemporal cortex, ECT is arguably the most effective treatment for severe major depression, with response rates and times superior to other available antidepressant therapies. Neuroimaging research has been pivotal in improving the field's mechanistic understanding of ECT, with a growing number of magnetic resonance imaging studies demonstrating hippocampal plasticity after ECT, in line with evidence of upregulated neurotrophic processes in the hippocampus in animal models. However, the precise roles of the hippocampus and other brain regions in antidepressant response to ECT remain unclear. Seizure physiology may also play a role in antidepressant response to ECT, as indicated by early positron emission tomography, single-photon emission computed tomography, and electroencephalography research and corroborated by recent magnetic resonance imaging studies. In this review, we discuss the evidence supporting neuroplasticity in the hippocampus and other brain regions during and after ECT, and their associations with antidepressant response. We also offer a mechanistic, circuit-level model that proposes that core mechanisms of antidepressant response to ECT involve thalamocortical and cerebellar networks that are active during seizure generalization and termination over repeated ECT sessions, and their interactions with corticolimbic circuits that are dysfunctional prior to treatment and targeted with the electrical stimulus.

Structural and Functional MRI Brain Changes in Patients with Schizophrenia Following Electroconvulsive Therapy: A Systematic Review

BACKGROUND

Schizophrenia (SZ) is a severe psychiatric disorder typically characterized by multidimensional psychotic syndromes. Electroconvulsive therapy (ECT) is a treatment option for medication-resistant patients with SZ or treating acute symptoms. Although the efficacy of ECT has been demonstrated in clinical use, its therapeutic mechanisms in the brain remain elusive.

OBJECTIVE

This study aimed to summarize brain changes on structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) after ECT.

METHODS

According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was carried out. The PubMed and Medline databases were systematically searched using the following medical subject headings (MeSH): (electroconvulsive therapy OR ECT) AND (schizophrenia) AND (MRI OR fMRI OR DTI OR DWI).

RESULTS

This review yielded 12 MRI studies, including 4 with sMRI, 5 with fMRI and 3 with multimodal MRI. Increases in volumes of the hippocampus and its adjacent regions (parahippocampal gyrus and amygdala), as well as the insula and frontotemporal regions, were noted after ECT. fMRI studies found ECT-induced changes in different brain regions/networks, including the hippocampus, amygdala, default model network, salience network and other regions/networks that are thought to highly correlate with the pathophysiologic characteristics of SZ. The results of the correlation between brain changes and symptom remissions are inconsistent.

CONCLUSION

Our review provides evidence supporting ECT-induced brain changes on sMRI and fMRI in SZ and explores the relationship between these changes and symptom remission.

Electroconvulsive therapy, electric field, neuroplasticity, and clinical outcomes

Electroconvulsive therapy (ECT) remains the gold-standard treatment for patients with depressive episodes, but the underlying mechanisms for antidepressant response and procedure-induced cognitive side effects have yet to be elucidated. Such mechanisms may be complex and involve certain ECT parameters and brain regions. Regarding parameters, the electrode placement (right unilateral or bitemporal) determines the geometric shape of the electric field (E-field), and amplitude determines the E-field magnitude in select brain regions (e.g., hippocampus). Here, we aim to determine the relationships between hippocampal E-field strength, hippocampal neuroplasticity, and antidepressant and cognitive outcomes. We used hippocampal E-fields and volumes generated from a randomized clinical trial that compared right unilateral electrode placement with different pulse amplitudes (600, 700, and 800 mA). Hippocampal E-field strength was variable but increased with each amplitude arm. We demonstrated a linear relationship between right hippocampal E-field and right hippocampal neuroplasticity. Right hippocampal neuroplasticity mediated right hippocampal E-field and antidepressant outcomes. In contrast, right hippocampal E-field was directly related to cognitive outcomes as measured by phonemic fluency. We used receiver operating characteristic curves to determine that the maximal right hippocampal E-field associated with cognitive safety was 112.5 V/m. Right hippocampal E-field strength was related to the whole-brain ratio of E-field strength per unit of stimulation current, but this whole-brain ratio was unrelated to antidepressant or cognitive outcomes. We discuss the implications of optimal hippocampal E-field dosing to maximize antidepressant outcomes and cognitive safety with individualized amplitudes.

Current progress in neuroimaging research for the treatment of major depression with electroconvulsive therapy

Electroconvulsive therapy (ECT) uses a certain amount of electric current to pass through the head of the patient, causing convulsions throughout the body, to relieve the symptoms of the disease and achieve the purpose of treatment. ECT can effectively improve the clinical symptoms of patients with major depression, but its therapeutic mechanism is still unclear. With the rapid development of neuroimaging technology, it is necessary to explore the neurobiological mechanism of major depression from the aspects of brain structure, brain function and brain metabolism, and to find that ECT can improve the brain function, metabolism and even brain structure of patients to a certain extent. Currently, an increasing number of neuroimaging studies adopt various neuroimaging techniques including functional magnetic resonance imaging (MRI), positron emission tomography, magnetic resonance spectroscopy, structural MRI, and diffusion tensor imaging to reveal the neural effects of ECT. This article reviews the recent progress in neuroimaging research on ECT for major depression. The results suggest that the neurobiological mechanism of ECT may be to modulate the functional activity and connectivity or neural structural plasticity in specific brain regions to the normal level, to achieve the therapeutic effect.

Shape and volume changes of the superior lateral ventricle after electroconvulsive therapy measured with ultra-high field MRI

The subventricular zone (SVZ) of the lateral ventricles harbors neuronal stem cells in adult mammals. Rodent studies report neurogenic effects in the SVZ of electroconvulsive stimulation. We hypothesize that if this finding translates to depressed patients undergoing electroconvulsive therapy (ECT), this would be reflected in shape changes at the SVZ. Using T1-weighted MR images acquired at ultra-high field strength (7T), the shape and volume of the ventricles were compared from pre to post ECT after 10 ECT sessions (in patients twice weekly) or 5 weeks apart (controls) using linear mixed models with age and gender as covariates. Ventricle shape significantly changed and volume significantly decreased over time in patients for the left ventricle, but not in controls. The decrease in volume of the ventricles was associated to a decrease in depression scores, and an increase in the left dentate gyrus, However, the shape changes of the ventricles were not restricted to the neurogenic niche in the lateral walls of the ventricles, providing no clear evidence for neurogenesis as sole explanation of volume changes in the ventricles after ECT.

ECT-induced cognitive side effects are associated with hippocampal enlargement

Electroconvulsive therapy (ECT) is of the most effective treatments available for treatment-resistant depression, yet it is underutilized in part due to its reputation of causing cognitive side effects in a significant number of patients. Despite intensive neuroimaging research on ECT in the past two decades, the underlying neurobiological correlates of cognitive side effects remain elusive. Because the primary ECT-related cognitive deficit is memory impairment, it has been suggested that the hippocampus may play a crucial role. In the current study, we investigated 29 subjects with longitudinal MRI and detailed neuropsychological testing in two independent cohorts (N = 15/14) to test if volume changes were associated with cognitive side effects. The two cohorts underwent somewhat different ECT study protocols reflected in electrode placements and the number of treatments. We used longitudinal freesurfer algorithms (6.0) to obtain a bias-free estimate of volume changes in the hippocampus and tested its relationship with neurocognitive score changes. As an exploratory analysis and to evaluate how specific the effects were to the hippocampus, we also calculated this relationship in 41 other areas. In addition, we also analyzed cognitive data from a group of healthy volunteers (N = 29) to assess practice effects. Our results supported the hypothesis that hippocampus enlargement was associated with worse cognitive outcomes, and this result was generalizable across two independent cohorts with different diagnoses, different electrode placements, and a different number of ECT sessions. We found, in both cohorts, that treatment robustly increased the volume size of the hippocampus (Cohort 1: t = 5.07, Cohort 2: t = 4.82; p < 0.001), and the volume increase correlated with the neurocognitive T-score change. (Cohort 1: r = -0.68, p = 0.005; Cohort 2: r = -0.58; p = 0.04). Overall, our research indicates that novel treatment methods serving to avoid hippocampal volume increase may result in a better side effect profile.

The Neurobiological Basis of Cognitive Side Effects of Electroconvulsive Therapy: A Systematic Review

Decades of research have consistently demonstrated the efficacy of electroconvulsive therapy (ECT) for the treatment of major depressive disorder (MDD), but its clinical use remains somewhat restricted because of its cognitive side effects. The aim of this systematic review is to comprehensively summarize current evidence assessing potential biomarkers of ECT-related cognitive side effects. Based on our systematic search of human studies indexed in PubMed, Scopus, and Web of Knowledge, a total of 29 studies evaluating patients with MDD undergoing ECT were reviewed. Molecular biomarkers studies did not consistently identify concentration changes in plasma S-100 protein, neuron-specific enolase (NSE), or Aβ peptides significantly associated with cognitive performance after ECT. Importantly, these findings suggest that ECT-related cognitive side effects cannot be explained by mechanisms of neural cell damage. Notwithstanding, S-100b protein and Aβ40 peptide concentrations, as well as brain-derived neurotrophic factor (BDNF) polymorphisms, have been suggested as potential predictive biomarkers of cognitive dysfunction after ECT. In addition, recent advances in brain imaging have allowed us to identify ECT-induced volumetric and functional changes in several brain structures closely related to memory performance such as the hippocampus. We provide a preliminary framework to further evaluate neurobiological cognitive vulnerability profiles of patients with MDD treated with ECT.

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy

BACKGROUND

Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT.

METHODS

To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc.

RESULTS

Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT.

LIMITATIONS

Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change.

CONCLUSION

Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.

Combining transcranial magnetic stimulation with functional magnetic resonance imaging for probing and modulating neural circuits relevant to affective disorders

Combining transcranial magnetic stimulation (TMS) with functional magnetic resonance imaging offers an unprecedented tool for studying how brain networks interact in vivo and how repetitive trains of TMS modulate those networks among patients diagnosed with affective disorders. TMS compliments neuroimaging by allowing the interrogation of causal control among brain circuits. Together with TMS, neuroimaging can provide valuable insight into the mechanisms underlying treatment effects and downstream circuit communication. Here we provide a background of the method, review relevant study designs, consider methodological and equipment options, and provide statistical recommendations. We conclude by describing emerging approaches that will extend these tools into exciting new applications. This article is categorized under: Psychology > Emotion and Motivation Psychology > Theory and Methods Neuroscience > Clinical Neuroscience.

Meta-analysis of brain structural changes after electroconvulsive therapy in depression

BACKGROUND

Increases in the volume of the amygdala and hippocampus after electroconvulsive therapy (ECT) are among the most robust effects known to the brain-imaging field. Recent advances in the segmentation of substructures of these regions allow for novel insights on the relationship between brain structure and clinical outcomes of ECT.

OBJECTIVE

We aimed to provide a comprehensive synthesis of evidence available on changes in brain structure after ECT, including recently published data on hippocampal subfields.

METHODS

A meta-analysis of published studies was carried out using random-effects models of standardized mean change of regional brain volumes measured with longitudinal magnetic resonance imaging of depressive patients before and after a series of ECT.

RESULTS

Data from 21 studies (543 depressed patients) were analysed, including 6 studies (118 patients) on hippocampal subfields. Meta-analyses could be carried out for seven brain regions for which data from at least three published studies was available. We observed increases in left and right hippocampi, amygdalae, cornua ammonis (CA) 1, CA 2/3, dentate gyri (DG) and subicula with standardized mean change scores ranging between 0.34 and 1.15. The model did not reveal significant volume increases in the caudate. Meta-regression indicated a negative relationship between the reported increases in the DG and relative symptom improvement (-0.27 (SE: 0.09) per 10%).

CONCLUSIONS

ECT is accompanied by significant volume increases in the bilateral hippocampus and amygdala that are not associated with treatment outcome. Among hippocampal subfields, the most robust volume increases after ECT were measured in the dentate gyrus. The indicated negative correlation of this effect with antidepressant efficacy warrants replication in data of individual patients.

Gradient of electro-convulsive therapy's antidepressant effects along the longitudinal hippocampal axis

Despite decades of successful treatment of therapy-resistant depression and major scientific advances in the field, our knowledge about electro-convulsive therapy's (ECT) mechanisms of action is still scarce. Building on strong empirical evidence for ECT-induced hippocampus anatomy changes, we sought to test the hypothesis that ECT has a differential impact along the hippocampus longitudinal axis. We acquired behavioural and brain anatomy magnetic resonance imaging (MRI) data in patients with depressive episode undergoing ECT (n = 9) or pharmacotherapy (n = 24) and healthy controls (n = 30) at two time points 3 months apart. Using whole-brain voxel-based statistical parametric mapping and topographic analysis focused on the hippocampus, we observed ECT-induced gradient of grey matter volume increase along the hippocampal longitudinal axis with predominant impact on its anterior portion. Clinical outcome measures showed strong correlations with both baseline volume and rate of ECT-induced change exclusively for the anterior, but not posterior hippocampus. We interpret our findings confined to the anterior hippocampus and amygdala as additional evidence of the regional specific impact of ECT that unfolds its beneficial effect on depression via the "limbic" system. Main limitations of the study are patients' polypharmacy, heterogeneity of psychiatric diagnosis, and long-time interval between scans.

Do increases in deep grey matter volumes after electroconvulsive therapy persist in patients with major depression? A longitudinal MRI-study

BACKGROUND

Previous MRI studies reported deep grey matter volume increases after electroconvulsive therapy (ECT) in patients with major depressive disorder (MDD). However, the clinical correlates of these changes are still unclear. It remains debated whether such volume changes are transient, and if they correlate with affective changes over time. We here investigated if ECT induces deep grey matter volume increases in MDD-patients; and, if so, whether volume changes persist over more than 9 months and whether they are related to the clinical outcome.

METHODS

We examined 16 MDD-patients with 3Tesla MRI before (baseline) and after an ECT-series and followed 12 of them up for 10-36 months. Patients' data were compared to 16 healthy controls. Affective scales were used to investigate the relationship between therapy-outcome and MRI changes.

RESULTS

At baseline, MDD-patients had lower values in global brain volume, white matter and peripheral grey matter compared to healthy controls, but we observed no significant differences in deep grey matter volumes. After ECT, the differences in peripheral grey matter disappeared, and patients demonstrated significant volume increases in the right hippocampus and both thalami, followed by subsequent decreases after 10-36 months, especially in ECT-responders. Controls did not show significant changes over time.

LIMITATIONS

Beside the relatively small, yet carefully characterized cohort, we address the variability in time between the third scanning session and the baseline.

CONCLUSIONS

ECT-induced deep grey matter volume increases are transient. Our results suggest that the thalamus might be a key region for the understanding of the mechanisms of ECT action.

Volume of hippocampal subregions and clinical improvement following electroconvulsive therapy in patients with depression

It is thought that the hippocampal neurogenesis is an important mediator of the antidepressant effect of electroconvulsive therapy (ECT). However, most previous studies failed to demonstrate the relationship between the increase in the hippocampal volume and the antidepressant effect. We reinvestigated this relationship by looking at distinct hippocampal subregions and applying repeated measures correlation. Using a 3 Tesla MRI-scanner, we scanned 22 severely depressed in-patients at three time points: before the ECT series, after the series, and at six-month follow-up. The depression severity was assessed by the 17-item Hamilton Rating Scale for Depression (HAMD-17). The hippocampus was segmented into subregions using Freesurfer software. The dentate gyrus (DG) was the primary region of interest (ROI), due to the role of this region in neurogenesis. The other major hippocampal subregions were the secondary ROIs (n = 20). The general linear mixed model and the repeated measures correlation were used for statistical analyses. Immediately after the ECT series, a significant volume increase was present in the right DG (Cohen's d = 1.7) and the left DG (Cohen's d = 1.5), as well as 15 out of 20 secondary ROIs. The clinical improvement, i.e., the decrease in HAMD-17 score, was correlated to the increase in the right DG volume (r_rm = -0.77, df = 20, p < .001), and the left DG volume (r_rm = -0.75, df = 20, p < .001). Similar correlations were observed in 14 out of 20 secondary ROIs. Thus, ECT induces an increase not only in the volume of the DG, but also in the volume of other major hippocampal subregions. The volumetric increases may reflect a neurobiological process that may be related to the ECT's antidepressant effect. Further investigation of the relationship between hippocampal subregions and the antidepressant effect is warranted. A statistical approach taking the repeated measurements into account should be preferred in the analyses.

International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic)

Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment-resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side-effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side-effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT, and the National Network of Depression Centers have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.

Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach

OBJECTIVE

To identify important clinical or imaging features predictive of an individual's response to electroconvulsive therapy (ECT) by utilizing a machine learning approach.

METHODS

Twenty-seven depressed patients who received ECT were recruited. Clinical demographics and pretreatment structural magnetic resonance imaging (MRI) data were used as candidate features to build models to predict remission and post-ECT Hamilton Depression Rating Scale scores. Support vector machine and support vector regression with elastic-net regularization were used to build models using (i) only clinical features, (ii) only MRI features, and (iii) both clinical and MRI features. Consistently selected features across all individuals were identified through leave-one-out cross-validation.

RESULTS

Compared with models that include only clinical variables, the models including MRI data improved the prediction of ECT remission: the prediction accuracy improved from 70% to 93%. Features selected consistently across all individuals included volumes in the gyrus rectus, the right anterior lateral temporal lobe, the cuneus, and the third ventricle, as well as 2 clinical features: psychotic features and family history of mood disorder.

CONCLUSIONS

Pretreatment structural MRI data improved the individual predictive accuracy of ECT remission, and only a small subset of features was important for prediction.

Volume increase in the dentate gyrus after electroconvulsive therapy in depressed patients as measured with 7T

Electroconvulsive therapy (ECT) is the most effective treatment for depression, yet its working mechanism remains unclear. In the animal analog of ECT, neurogenesis in the dentate gyrus (DG) of the hippocampus is observed. In humans, volume increase of the hippocampus has been reported, but accurately measuring the volume of subfields is limited with common MRI protocols. If the volume increase of the hippocampus in humans is attributable to neurogenesis, it is expected to be exclusively present in the DG, whereas other processes (angiogenesis, synaptogenesis) also affect other subfields. Therefore, we acquired an optimized MRI scan at 7-tesla field strength allowing sensitive investigation of hippocampal subfields. A further increase in sensitivity of the within-subjects measurements is gained by automatic placement of the field of view. Patients receive two MRI scans: at baseline and after ten bilateral ECT sessions (corresponding to a 5-week interval). Matched controls are also scanned twice, with a similar 5-week interval. A total of 31 participants (23 patients, 8 controls) completed the study. A large and significant increase in DG volume was observed after ECT (M = 75.44 mm³, std error = 9.65, p < 0.001), while other hippocampal subfields were unaffected. We note that possible type II errors may be present due to the small sample size. In controls no changes in volume were found. Furthermore, an increase in DG volume was related to a decrease in depression scores, and baseline DG volume predicted clinical response. These findings suggest that the volume change of the DG is related to the antidepressant properties of ECT, and may reflect neurogenesis.

Subcallosal Cingulate Structural Connectivity Differs in Responders and Nonresponders to Electroconvulsive Therapy

BACKGROUND

Subcallosal cingulate (SCC) activity is associated with treatment response in major depressive disorder (MDD). Using electroconvulsive therapy (ECT) as a treatment model in this exploratory study, we addressed whether pretreatment SCC structural connectivity with corticolimbic-striatal circuitry relates to therapeutic outcome and whether these connectivity patterns change with treatment.

METHODS

Diffusion magnetic resonance imaging scans were acquired in 43 patients with MDD (mean [SD] age = 41 [13] years; men/women: 18/25) before and within 1 week of completing an ECT index series and in 31 healthy control subjects scanned twice (mean [SD] age = 38 [11] years; men/women: 17/18). Probabilistic tractography from subject-specific anatomically defined SCC seed regions to the ventral striatum (VS), anterior cingulate cortex (ACC), and bilateral medial prefrontal cortex (mPFC) was used to estimate structural connectivity in the target network.

RESULTS

SCC-mPFC connectivity was lower in responders (>50% symptom improvement) than nonresponders both before (p < .014) (difference 37%-96% left and right hemispheres) and after (p = .023) (difference 100% right hemisphere) treatment. SCC-mPFC connectivity in responders was also decreased compared with control subjects both at baseline (p = .012) and after ECT (p = .006), whereas nonresponders had SCC-right mPFC connectivity similar to that of control subjects. Subjects with MDD also showed decreased SCC-ACC connectivity compared with control subjects (baseline: p < .003, after ECT: p = .001), although SCC-ACC connectivity did not distinguish responders from nonresponders. Bilateral SCC-VS connectivity decreased (11%) with ECT (p = .021) regardless of treatment response.

CONCLUSIONS

While SCC-ACC connectivity may be a hallmark of MDD compared with control subjects, lower pretreatment SCC-mPFC connectivity in ECT responders (compared with nonresponders and control subjects) suggests that connectivity in this pathway may serve as a potential biomarker of therapeutic outcome and be relevant for treatment selection.

Depressive Symptom Dimensions in Treatment-Resistant Major Depression and Their Modulation With Electroconvulsive Therapy

OBJECTIVE

Symptom heterogeneity in major depressive disorder obscures diagnostic and treatment-responsive biomarker identification. Whether symptom constellations are differentially changed by electroconvulsive therapy (ECT) remains unknown. We investigate the clustering of depressive symptoms over the ECT index and whether ECT differentially influences symptom clusters.

METHODS

The 17-item Hamilton Depression Rating Scale (HDRS-17) was collected from 111 patients with current depressive episode before and after ECT from 4 independent participating sites of the Global ECT-MRI Research Collaboration. Exploratory factor analysis of HDRS-17 items pre- and post-ECT treatment identified depressive symptom dimensions before and after ECT. A 2-way analysis of covariance was used to determine whether baseline symptom clusters were differentially changed by ECT between treatment remitters (defined as patients with posttreatment HDRS-17 total score ≤8) and nonremitters while controlling for pulse width, titration method, concurrent antidepressant treatment, use of benzodiazepine, and demographic variables.

RESULTS

A 3-factor solution grouped pretreatment HDRS-17 items into core mood/anhedonia, somatic, and insomnia dimensions. A 2-factor solution best described the symptoms at posttreatment despite poorer separation of items. Among remitters, core mood/anhedonia symptoms were significantly more reduced than somatic and insomnia dimensions. No differences in symptom dimension trajectories were observed among nonremitting patients.

CONCLUSIONS

Electroconvulsive therapy targets the underlying source of depressive symptomatology and may confer differential degrees of improvement in certain core depressive symptoms. Our findings of differential trajectories of symptom clusters over the ECT index might help related predictive biomarker studies to refine their approaches by identifying predictors of change along each latent symptom dimension.

Precision non-implantable neuromodulation therapies: a perspective for the depressed brain

Current first-line treatments for major depressive disorder (MDD) include pharmacotherapy and cognitive-behavioral therapy. However, one-third of depressed patients do not achieve remission after multiple medication trials, and psychotherapy can be costly and time-consuming. Although non-implantable neuromodulation (NIN) techniques such as transcranial magnetic stimulation, transcranial direct current stimulation, electroconvulsive therapy, and magnetic seizure therapy are gaining momentum for treating MDD, the efficacy of non-convulsive techniques is still modest, whereas use of convulsive modalities is limited by their cognitive side effects. In this context, we propose that NIN techniques could benefit from a precision-oriented approach. In this review, we discuss the challenges and opportunities in implementing such a framework, focusing on enhancing NIN effects via a combination of individualized cognitive interventions, using closed-loop approaches, identifying multimodal biomarkers, using computer electric field modeling to guide targeting and quantify dosage, and using machine learning algorithms to integrate data collected at multiple biological levels and identify clinical responders. Though promising, this framework is currently limited, as previous studies have employed small samples and did not sufficiently explore pathophysiological mechanisms associated with NIN response and side effects. Moreover, cost-effectiveness analyses have not been performed. Nevertheless, further advancements in clinical trials of NIN could shift the field toward a more “precision-oriented” practice.

Brain Changes Induced by Electroconvulsive Therapy Are Broadly Distributed

BACKGROUND

Electroconvulsive therapy (ECT) is associated with volumetric enlargements of corticolimbic brain regions. However, the pattern of whole-brain structural alterations following ECT remains unresolved. Here, we examined the longitudinal effects of ECT on global and local variations in gray matter, white matter, and ventricle volumes in patients with major depressive disorder as well as predictors of ECT-related clinical response.

METHODS

Longitudinal magnetic resonance imaging and clinical data from the Global ECT-MRI Research Collaboration (GEMRIC) were used to investigate changes in white matter, gray matter, and ventricle volumes before and after ECT in 328 patients experiencing a major depressive episode. In addition, 95 nondepressed control subjects were scanned twice. We performed a mega-analysis of single subject data from 14 independent GEMRIC sites.

RESULTS

Volumetric increases occurred in 79 of 84 gray matter regions of interest. In total, the cortical volume increased by mean ± SD of 1.04 ± 1.03% (Cohen's d = 1.01, p < .001) and the subcortical gray matter volume increased by 1.47 ± 1.05% (d = 1.40, p < .001) in patients. The subcortical gray matter increase was negatively associated with total ventricle volume (Spearman's rank correlation ρ = -.44, p < .001), while total white matter volume remained unchanged (d = -0.05, p = .41). The changes were modulated by number of ECTs and mode of electrode placements. However, the gray matter volumetric enlargements were not associated with clinical outcome.

CONCLUSIONS

The findings suggest that ECT induces gray matter volumetric increases that are broadly distributed. However, gross volumetric increases of specific anatomically defined regions may not serve as feasible biomarkers of clinical response.

Structural changes induced by electroconvulsive therapy are associated with clinical outcome

BACKGROUND

Electroconvulsive therapy (ECT) is the most effective treatment option for major depressive disorder, so understanding whether its clinical effect relates to structural brain changes is vital for current and future antidepressant research.

OBJECTIVE

To determine whether clinical response to ECT is related to structural volumetric changes in the brain as measured by structural magnetic resonance imaging (MRI) and, if so, which regions are related to this clinical effect. We also determine whether a similar model can be used to identify regions associated with electrode placement (unilateral versus bilateral ECT).

METHODS

Longitudinal MRI and clinical data (Hamilton Depression Rating Scale) was collected from 10 sites as part of the Global ECT-MRI research collaboration (GEMRIC). From 192 subjects, relative changes in 80 (sub)cortical areas were used as potential features for classifying treatment response. We used recursive feature elimination to extract relevant features, which were subsequently used to train a linear classifier. As a validation, the same was done for electrode placement. We report accuracy as well as the structural coefficients of regions included in the discriminative spatial patterns obtained.

RESULTS

A pattern of structural changes in cortical midline, striatal and lateral prefrontal areas discriminates responders from non-responders (75% accuracy, p < 0.001) while left-sided mediotemporal changes discriminate unilateral from bilateral electrode placement (81% accuracy, p < 0.001).

CONCLUSIONS

The identification of a multivariate discriminative pattern shows that structural change is relevant for clinical response to ECT, but this pattern does not include mediotemporal regions that have been the focus of electroconvulsive therapy research so far.

Common increased hippocampal volume but specific changes in functional connectivity in schizophrenia patients in remission and non-remission following electroconvulsive therapy: A preliminary study

Electroconvulsive therapy (ECT) is considered a treatment option in patients with drug-resistant schizophrenia (SZ). However, approximately one-third of patients do not benefit from ECT in the clinic. Thus, it is critical to investigate differences between ECT responders and non-responders. Accumulated evidence has indicated that one region of ECT action is the hippocampus, which also plays an important role in SZ pathophysiology. To date, no studies have investigated differences in ECT effects in the hippocampus between treatment responders and non-responders. This study recruited twenty-one SZ patients treated for four weeks with ECT (MSZ, n = 21) and twenty-one SZ patients who received pharmaceutical therapy (DSZ, n = 21). The MSZ group was further categorized into responders (MSR, n = 10) or non-responders (MNR, n = 11) based on treatment outcomes by the criterion of a 50% reduction in the Positive and Negative Syndrome Scale total scores. Using structural and resting-state functional MRI, we measured the hippocampal volume and functional connectivity (FC) in all SZ patients (before and after treatment) and 23 healthy controls. In contrast to pharmaceutical therapy, ECT induced bilateral hippocampal volume increases in the MSZ. Both the MSR and MNR exhibited hippocampal expansion after ECT, whereas a lower baseline volume in one of hippocampal subfield (hippocampus-amygdala transition area) was found in the MNR. After ECT, increased FC between the hippocampus and brain networks associated with cognitive function was only observed in the MSR. The mechanism of action of ECT in schizophrenia is complex. A combination of baseline impairment level, ECT-introduced morphological changes and post-ECT FC increases in the hippocampus may jointly contribute to the post-ECT symptom improvements in patients with SZ.

Grey Matter changes in treatment-resistant depression during electroconvulsive therapy

INTRODUCTION

20-30% of depressed patients experience Treatment Resistant Depression (TRD). Electroconvulsive Therapy (ECT) remains the treatment of choice for TRD. However, the exact mechanism of ECT remains unclear. We aim to assess grey matter changes in patients with TRD undergoing bilateral ECT treatment at different points during and after treatment.

METHODS

Patients are recruited at the University Hospital of Toulouse. Eligibility criteria include a diagnosis of TRD and an age between 50 and 70 years old. Patients received clinical assessments (Hamilton Depression Rating Scale) and structural scans (MRI) at three points: baseline (within 48 h before the first ECT); V2 (after the first ECT considered effective); and V3 (within 1 week of completing ECT).

RESULTS

At baseline, controls had significantly higher cortical thickness than patients in the fusiform gyrus, the inferior, middle and superior temporal gyrus, the parahippocampal gyrus and the transverse temporal gyrus (respectively: t(35)=2.7, p = 0.02; t(35)=2.89, p = 0.017; t(35)=3.1, p = 0.015; t(35)=3.6, p = 0.009; t(35)=2.37, p = 0.031; t(35)=2.46, p = 0.03). This difference was no longer significant after ECT. We showed an increase in cortical thickness in superior temporal gyrus between (i) baseline and V3 (t(62)=-3.43 p = 0.009) and (ii) V2 and V3 (t(62)=-3.42 p = 0.009). We showed an increase in hippocampal volume between (i) baseline and V3 (t(62)=-5.23 p < 0.001) and (ii) V2 and V3 (t(62)=-5.3 p < 0.001).

CONCLUSION

We highlight that there are grey matter changes during ECT treatment in a population with TRD compared to a healthy control population. These changes seem to occur after several rounds of ECT.

Electric field causes volumetric changes in the human brain

Recent longitudinal neuroimaging studies in patients with electroconvulsive therapy (ECT) suggest local effects of electric stimulation (lateralized) occur in tandem with global seizure activity (generalized). We used electric field (EF) modeling in 151 ECT treated patients with depression to determine the regional relationships between EF, unbiased longitudinal volume change, and antidepressant response across 85 brain regions. The majority of regional volumes increased significantly, and volumetric changes correlated with regional electric field (t = 3.77, df = 83, r = 0.38, p=0.0003). After controlling for nuisance variables (age, treatment number, and study site), we identified two regions (left amygdala and left hippocampus) with a strong relationship between EF and volume change (FDR corrected p<0.01). However, neither structural volume changes nor electric field was associated with antidepressant response. In summary, we showed that high electrical fields are strongly associated with robust volume changes in a dose-dependent fashion.

Electroconvulsive therapy, or ECT for short, can be an effective treatment for severe depression. Many patients who do not respond to medication find that their symptoms improve after ECT. During an ECT session, the patient is placed under general anesthesia and two electrodes are attached to the scalp to produce an electric field that generates currents within the brain. These currents activate neurons and make them fire, causing a seizure, but it remains unclear how this reduces symptoms of depression.

For many years, researchers thought that the induced seizure must be key to the beneficial effects of ECT, but recent studies have cast doubt on this idea. They show that increasing the strength of the electric field alters the clinical effects of ECT, without affecting the seizure. This suggests that the benefits of ECT depend on the electric field itself.

Argyelan et al. now show that electric fields affect the brain by making a part of the brain known as the gray matter expand. In a large multinational study, 151 patients with severe depression underwent brain scans before and after a course of ECT. The scans revealed that the gray matter of the patients’ brains expanded during the treatment. The patients who experienced the strongest electric fields showed the largest increase in brain volume, and individual brain areas expanded if the electric field within them exceeded a certain threshold. This effect was particularly striking in two areas, the hippocampus and the amygdala. Both of these areas are critical for mood and memory.

Further studies are needed to determine why the brain expands after ECT, and how long the effect lasts. Another puzzle is why the improvements in depression that the patients reported after their treatment did not correlate with changes in brain volume. Disentangling the relationships between ECT, brain volume and depression will ultimately help develop more robust treatments for this disabling condition.

Thalamic volume, resting-state activity, and their association with the efficacy of electroconvulsive therapy

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment. Biological predictors of clinical outcome to ECT are valuable. We aimed to examine multimodal magnetic resonance imaging (MRI) data that correlates to the efficacy of ECT. Structural and resting-state functional MRI data were acquired from 46 individuals (25 depressed individuals who received ECT, and 21 healthy controls). Whole-brain grey matter volume (GMV) and fractional amplitude of low frequency fluctuations (fALFF) were investigated to identify brain regions associated with post-ECT Hamilton Depression Rating Scale (HAM-D) total scores. GMV and fALFF values were compared with those in healthy controls using analysis of covariance (ANCOVA). Remission was defined by HAM-D ≤7. A multiple regression analysis revealed that pretreatment smaller GMV in the left thalamus was associated with worse response to ECT (i.e. higher post-ECT HAM-D). Pretreatment higher fALFF in the right anterior insula, and lower fALFF in the left thalamus and the cerebellum were associated with worse outcomes. The left thalamus was identified in both GMV and fALFF analyses. Nonremitters showed significantly smaller thalamic GMV compared to remitters and controls. We found that pretreatment thalamic volume and resting-state activity were associated with the efficacy of ECT. Our results highlight the importance of the thalamus as a possible biological predictor and its role in the underlying mechanisms of ECT action.

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-Åsberg 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.