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.

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.

Links between electroconvulsive therapy responsive and cognitive impairment multimodal brain networks in late-life major depressive disorder.

BACKGROUND: Although electroconvulsive therapy (ECT) is an effective treatment for depression, ECT cognitive impairment remains a major concern. The neurobiological underpinnings and mechanisms underlying ECT antidepressant and cognitive impairment effects remain unknown. This investigation aims to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks and assesses whether they are associated with the ECT-induced electric field (E-field) with an optimal pulse amplitude estimation. METHODS: A single site clinical trial focused on amplitude (600, 700, and 800 mA) included longitudinal multimodal imaging and clinical and cognitive assessments completed before and immediately after the ECT series (n = 54) for late-life depression. Another two independent validation cohorts (n = 84, n = 260) were included. Symptom and cognition were used as references to supervise fMRI and sMRI fusion to identify ECT antidepressant-response and cognitive-impairment multimodal brain networks. Correlations between ECT-induced E-field within these two networks and clinical and cognitive outcomes were calculated. An optimal pulse amplitude was estimated based on E-field within antidepressant-response and cognitive-impairment networks. RESULTS: Decreased function in the superior orbitofrontal cortex and caudate accompanied with increased volume in medial temporal cortex showed covarying functional and structural alterations in both antidepressant-response and cognitive-impairment networks. Volume increases in the hippocampal complex and thalamus were antidepressant-response specific, and functional decreases in the amygdala and hippocampal complex were cognitive-impairment specific, which were validated in two independent datasets. The E-field within these two networks showed an inverse relationship with HDRS reduction and cognitive impairment. The optimal E-filed range as [92.7-113.9] V/m was estimated to maximize antidepressant outcomes without compromising cognitive safety. CONCLUSIONS: The large degree of overlap between antidepressant-response and cognitive-impairment networks challenges parameter development focused on precise E-field dosing with new electrode placements. The determination of the optimal individualized ECT amplitude within the antidepressant and cognitive networks may improve the treatment benefit-risk ratio. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02999269.

Ictal Theta Power as an Electroconvulsive Therapy Safety Biomarker: A Pilot Study.

OBJECTIVE: Electroconvulsive therapy (ECT) remains the benchmark for treatment resistant depression, yet its cognitive adverse effects have a negative impact on treatment. A predictive safety biomarker early in ECT treatment is needed to identify patients at cognitive risk to maximize therapeutic outcomes and minimize adverse effects. We used ictal electroencephalography frequency analysis from suprathreshold treatments to assess the relationships between ECT dose, ictal power across different frequency domains, and cognitive outcomes. METHODS: Seventeen subjects with treatment resistant depression received right unilateral ECT. Structural magnetic resonance imaging was obtained pre-ECT for electric field modeling to assess ECT dose. Serial assessments with 24-lead electroencephalography captured ictal activity. Clinical and cognitive assessments were performed before and after ECT. The primary cognitive outcome was the change in Delis Kaplan Executive Function Verbal Fluency Letter Fluency. RESULTS: Ictal theta (4-8 Hz) power in the Fp1/Fp2 channels was associated with both whole-brain electric field strength (t(2,12) = 19.5, P = 0.007)/(t(2,10) = 21.85, P = 0.02) and Delis Kaplan Executive Function Verbal Fluency Letter Fluency scores (t(2,12) = -2.05, P = 0.05)/(t(2,10) = -2.20, P = 0.01). Other frequency bands (beta, alpha, delta, and gamma) did not demonstrate this relationship. CONCLUSIONS: This pilot data identify ictal theta power as a potential safety biomarker in ECT and is related to the strength of the ECT dose. Ictal theta power could prove to be a convenient and powerful tool for clinicians to identify those patients most susceptible to cognitive impairment early in the treatment series. Additional studies are needed to assess the role of longitudinal changes in ictal theta power throughout the ECT series.

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing three latent symptom dimensions within the 17-item Hamilton Depression Rating Scale (HDRS) and use data-driven methods to relate multivariate patterns of patient clinical, demographic, and brain structural changes over electroconvulsive therapy (ECT) to dimensional changes in depressive symptoms. We included 110 ECT patients from Global ECT-MRI Research Collaboration (GEMRIC) sites who underwent structural MRI and HDRS assessments before and after treatment. Cross validated random forest regression models predicted change along symptom dimensions. HDRS symptoms clustered into dimensions of somatic disturbances (SoD), core mood and anhedonia (CMA), and insomnia. The coefficient of determination between predicted and actual changes were 22%, 39%, and 39% (all p < .01) for SoD, CMA, and insomnia, respectively. CMA and insomnia change were predicted more accurately than HDRS-6 and HDRS-17 changes (p < .05). Pretreatment symptoms, body-mass index, and age were important predictors. Important imaging predictors included the right transverse temporal gyrus and left frontal pole for the SoD dimension; right transverse temporal gyrus and right rostral middle frontal gyrus for the CMA dimension; and right superior parietal lobule and left accumbens for the insomnia dimension. Our findings support that recovery along depressive symptom dimensions is predicted more accurately than HDRS total scores and are related to unique and overlapping patterns of clinical and demographic data and volumetric changes in brain regions related to depression and near ECT electrodes.

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.

Electroconvulsive Therapy Pulse Amplitude and Clinical Outcomes.

INTRODUCTION: Electroconvulsive therapy (ECT) pulse amplitude, which determines the induced electric field magnitude in the brain, is currently set at 800-900 milliamperes (mA) on modern ECT devices without any clinical or scientific rationale. The present study assessed differences in depression and cognitive outcomes for three different pulse amplitudes during an acute ECT series. We hypothesized that the lower amplitudes would maintain the antidepressant efficacy of the standard treatment and reduce the risk of neurocognitive impairment. METHODS: This double-blind investigation randomized subjects to three treatment arms: 600, 700, and 800 mA (active comparator). Clinical, cognitive, and imaging assessments were conducted pre-, mid- and post-ECT. Subjects had a diagnosis of major depressive disorder, age range between 50 and 80 years, and met clinical indication for ECT. RESULTS: The 700 and 800 mA arms had improvement in depression outcomes relative to the 600 mA arm. The amplitude groups showed no differences in the primary cognitive outcome variable, the Hopkins Verbal Learning Test-Revised (HVLT-R) retention raw score. However, secondary cognitive outcomes such as the Delis Kaplan Executive Function System Letter and Category Fluency measures demonstrated cognitive impairment in the 800 mA arm. DISCUSSION: The results demonstrated a dissociation of depression (higher amplitudes better) and cognitive (lower amplitudes better) related outcomes. Future work is warranted to elucidate the relationship between amplitude, electric field, neuroplasticity, and clinical outcomes.

Electroconvulsive therapy treatment responsive multimodal brain networks.

Electroconvulsive therapy is regarded as the most effective antidepressant treatment for severe and treatment-resistant depressive episodes. Despite the efficacy of electroconvulsive therapy, the neurobiological underpinnings and mechanisms underlying electroconvulsive therapy induced antidepressant effects remain unclear. The objective of this investigation was to identify electroconvulsive therapy treatment responsive multimodal biomarkers with the 17-item Hamilton Depression Rating Scale guided brain structure-function fusion in 118 patients with depressive episodes and 60 healthy controls. Results show that reduced fractional amplitude of low frequency fluctuations in the prefrontal cortex, insula and hippocampus, linked with increased gray matter volume in anterior cingulate, medial temporal cortex, insula, thalamus, caudate and hippocampus represent electroconvulsive therapy responsive covarying functional and structural brain networks. In addition, relative to nonresponders, responder-specific electroconvulsive therapy related brain networks occur in frontal-limbic network and are associated with successful therapeutic outcomes. Finally, electroconvulsive therapy responsive brain networks were unrelated to verbal declarative memory. Using a data-driven, supervised-learning method, we demonstrated that electroconvulsive therapy produces a remodeling of brain functional and structural covariance that was unique to antidepressant symptom response, but not linked to memory impairment.

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.

Hemodynamic response function abnormalities in schizophrenia during a multisensory detection task.

Functional magnetic resonance imaging (fMRI) of the blood oxygen level dependent (BOLD) response has commonly been used to investigate the neuropathology underlying cognitive and sensory deficits in patients with schizophrenia (SP) by examining the positive phase of the BOLD response, assuming a fixed shape for the hemodynamic response function (HRF). However, the individual phases (positive and post-stimulus undershoot (PSU)) of the HRF may be differentially affected by a variety of underlying pathologies. The current experiment used a multisensory detection task with a rapid event-related fMRI paradigm to investigate both the positive and PSU phases of the HRF in SP and healthy controls (HC). Behavioral results indicated no significant group differences during task performance. Analyses that examined the shape of the HRF indicated two distinct group differences. First, SP exhibited a reduced and/or prolonged PSU following normal task-related positive BOLD activation in secondary auditory and visual sensory areas relative to HC. Second, SP did not show task-induced deactivation in the anterior node of the default-mode network (aDMN) relative to HC. In contrast, when performing traditional analyses that focus on the positive phase, there were no group differences. Interestingly, the magnitude of the PSU in secondary auditory and visual areas was positively associated with the magnitude of task-induced deactivation within the aDMN, suggesting a possible common neural mechanism underlying both of these abnormalities (failure in neural inhibition). Results are consistent with recent views that separate neural processes underlie the two phases of the HRF and that they are differentially affected in SP. Hum Brain Mapp 37:745-755, 2016. © 2015 Wiley Periodicals, Inc.

Reproducibility of phase rotation stimulated echo acquisition mode at 3T in schizophrenia: Emphasis on glutamine.

PURPOSE: To determine the reproducibility and reliability of glutamine (Gln), measured with a very short echo time phase rotation stimulated echo acquisition mode (VTE-PR STEAM) sequence at 3T, in subjects with schizophrenia. METHODS: Seven subjects with schizophrenia were scanned twice with VTE-PR STEAM in a Siemens 3T TIM Trio scanner with a 32-channel head coil. Spectroscopic data were collected from two voxels in gray matter, one in the dorsal anterior cingulate and the other in the medial occipital cortex. Reproducibility was assessed using coefficients of variation (CVs) and reliability with standard error of measurement and intraclass correlations (ICCs). Phantoms containing increasing concentrations of Gln in a physiologic solution of other neurometabolites with overlapping resonances were scanned to assess the validity of spectral Gln measurement. RESULTS: Very good reliability and reproducibility for Gln in both regions of interest were supported by CVs of ≤10.0% and ICCs of ≥0.6, respectively. Phantom studies documented a robust correspondence between known Gln concentrations and VTE-PR STEAM measurements of this metabolite (R(2) = 0.988). CONCLUSION: The VTE-PR STEAM approach at 3T permits the longitudinal assessment of Gln and other (1) H MR spectroscopy neurometabolites in a clinically plausible setting.

Post-electroconvulsive therapy recovery and reorientation time with methohexital and ketamine: a randomized, longitudinal, crossover design trial.

OBJECTIVES: Methohexital, a barbiturate anesthetic commonly used for electroconvulsive therapy (ECT), possesses dose-dependent anticonvulsant properties, and its use can interfere with effective seizure therapy in patients with high seizure thresholds. Ketamine, an N-methyl-d-aspartate antagonist with epileptogenic properties not broadly used for ECT inductions, is a commonly used induction agent for general anesthesia. Recent studies suggest that the use of ketamine is effective in allowing successful ECT treatment in patients with high seizure thresholds without an increase in adverse effects. In this preliminary study, we directly compared the recovery and reorientation times of subjects receiving ketamine and methohexital for ECTs. METHODS: Twenty patients were randomized in a crossover design to receive methohexital and ketamine for ECT inductions in alternating fashion in 6 trials. Primary outcome measures were recovery time (voluntary movement, respiratory effort, blood pressure, consciousness, and O2 saturation) and reorientation time. Secondary outcome measures were individual recovery variables, adverse effect occurrence, and seizure duration. RESULTS: Overall recovery time was not significantly different between the 2 treatment arms (F(1, 17) = 0.72; P = 0.41). Reorientation time was faster in the methohexital arm (F(1, 17) = 9.23; P = 0.007). CONCLUSION: Ketamine inductions resulted in higher number of adverse effects, higher subject dropout rates, and a longer reorientation time with respect to methohexital inductions. No significant difference in postanesthesia recovery time was found between the ketamine and methohexital arms. Intolerability to ketamine affected a significant proportion of subjects and suggests that ketamine should remain as an alternative or adjunctive agent for patients with high seizure thresholds.

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia.

Although a number of recent studies have examined functional connectivity at rest, few have assessed differences between connectivity both during rest and across active task paradigms. Therefore, the question of whether cortical connectivity patterns remain stable or change with task engagement continues to be unaddressed. We collected multi-scan fMRI data on healthy controls (N=53) and schizophrenia patients (N=42) during rest and across paradigms arranged hierarchically by sensory load. We measured functional network connectivity among 45 non-artifactual distinct brain networks. Then, we applied a novel analysis to assess cross paradigm connectivity patterns applied to healthy controls and patients with schizophrenia. To detect these patterns, we fit a group by task full factorial ANOVA model to the group average functional network connectivity values. Our approach identified both stable (static effects) and state-based differences (dynamic effects) in brain connectivity providing a better understanding of how individuals' reactions to simple sensory stimuli are conditioned by the context within which they are presented. Our findings suggest that not all group differences observed during rest are detectable in other cognitive states. In addition, the stable differences of heightened connectivity between multiple brain areas with thalamus across tasks underscore the importance of the thalamus as a gateway to sensory input and provide new insight into schizophrenia.

A review of longitudinal electroconvulsive therapy: neuroimaging investigations.

Electroconvulsive therapy (ECT) is the most effective treatment for a depressive episode but the mechanism of action and neural correlates of response are poorly understood. Different theories have suggested that anticonvulsant properties or neurotrophic effects are related to the unique mechanism of action of ECT. This review assessed longitudinal imaging investigations (both structural and functional) associated with ECT response published from 2002 to August 2013. We identified 26 investigations that used a variety of different imaging modalities and data analysis methods. Despite these methodological differences, we summarized the major findings of each investigation and identified common patterns that exist across multiple investigations. The ECT response is associated with decreased frontal perfusion, metabolism, and functional connectivity and increased volume and neuronal chemical metabolites. The general collective of longitudinal neuroimaging investigations support both the anticonvulsant and the neurotrophic effects of ECT. We propose a conceptual framework that integrates these seemingly contradictory hypotheses.