Efficacy and safety of ketamine-assisted electroconvulsive therapy in major depressive episode: a systematic review and network meta-analysis.

OBJECTIVE: To meta-analyze clinical efficacy and safety of ketamine compared with other anesthetic agents in the course of electroconvulsive therapy (ECT) in major depressive episode (MDE). METHODS: PubMed/MEDLINE, Cochrane Library, Embase, GoogleScholar, and US and European trial registries were searched from inception through May 23, 2023, with no language limits. We included RCTs with (1) a diagnosis of MDE; (2) ECT intervention with ketamine and/or other anesthetic agents; and (3) measures included: depressive symptoms, cognitive performance, remission or response rates, and serious adverse events. Network meta-analysis (NMA) was performed to compare ketamine and 7 other anesthetic agents. Hedges' g standardized mean differences (SMDs) were used for continuous measures, and relative risks (RRs) were used for other binary outcomes using random-effects models. RESULTS: Twenty-two studies were included in the systematic review. A total of 2322 patients from 17 RCTs were included in the NMA. The overall pooled SMD of ketamine, as compared with propofol as a reference group, was -2.21 (95% confidence interval [CI], -3.79 to -0.64) in depressive symptoms, indicating that ketamine had better antidepressant efficacy than propofol. In a sensitivity analysis, however, ketamine-treated patients had a worse outcome in cognitive performance than propofol-treated patients (SMD, -0.18; 95% CI, -0.28 to -0.09). No other statistically significant differences were found. CONCLUSIONS: Ketamine-assisted ECT is tolerable and may be efficacious in improving depressive symptoms, but a relative adverse impact on cognition may be an important clinical consideration. Anesthetic agents should be considered based on patient profiles and/or preferences to improve effectiveness and safety of ECT use.

Structural brain plasticity and inflammation are independently related to changes in depressive symptoms six months after an index ECT course.

BACKGROUND: Electroconvulsive therapy (ECT) is effective for treatment-resistant depression and leads to short-term structural brain changes and decreases in the inflammatory response. However, little is known about how brain structure and inflammation relate to the heterogeneity of treatment response in the months following an index ECT course. METHODS: A naturalistic six-month study following an index ECT course included 20 subjects with treatment-resistant depression. Upon conclusion of the index ECT course and again after six months, structural magnetic resonance imaging scans and peripheral inflammation measures [interleukin-6 (IL-6), IL-8, tumor necrosis factor (TNF-α), and C-reactive protein] were obtained. Voxel-based morphometry processed with the CAT-12 Toolbox was used to estimate changes in gray matter volume. RESULTS: Between the end of the index ECT course and the end of follow-up, we found four clusters of significant decreases in gray matter volume (p < 0.01, FWE) and no regions of increased volume. Decreased HAM-D scores were significantly related only to reduced IL-8 level. Decreased volume in one cluster, which included the right insula and Brodmann's Area 22, was related to increased HAM-D scores over six months. IL-8 levels did not mediate or moderate the relationship between volumetric change and depression. CONCLUSIONS: Six months after an index ECT course, multiple regions of decreased gray matter volume were observed in a naturalistic setting. The independent relations between brain volume and inflammation to depressive symptoms suggest novel explanations of the heterogeneity of longer-term ECT treatment response.

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.

Glucagon-Like Peptide-1 Receptor Agonists During Electroconvulsive Therapy: Case Report With Evolving Concerns and Management Considerations.

ABSTRACT: Glucagon-like peptide-1 receptor agonists are an emerging class of medications transforming the management of diabetes mellitus and obesity, two highly prevalent and chronic medical conditions associated with significant morbidity and posing serious public health concerns. Although generally well tolerated and relatively safe to use, case reports of patients taking these medications while undergoing elective procedures with general anesthesia describe a potential heightened risk of regurgitation and pulmonary aspiration of gastric contents, deriving from the delayed gastric emptying effect of these agents. Based on increased recognition of this risk, the American Society of Anesthesiologists convened a task force to review available data, resulting in the promulgation of a new procedural management guideline for patients on these drugs and undergoing elective procedures with general anesthesia. However, this guideline pertains mostly to procedures and situations that are distinct from electroconvulsive therapy (ECT). This case report describes the experience of a patient on semaglutide, a glucagon-like peptide-1 receptor agonist for obesity, undergoing ECT, provides a general overview of this novel drug class, identifies issues specific to ECT management, and suggests potential adaptations to patient care over different phases of ECT practice.

Changes in white matter microstructure following serial ketamine infusions in treatment resistant depression.

Ketamine produces fast-acting antidepressant effects in treatment resistant depression (TRD). Though prior studies report ketamine-related changes in brain activity in TRD, understanding of ketamine's effect on white matter (WM) microstructure remains limited. We thus sought to examine WM neuroplasticity and associated clinical improvements following serial ketamine infusion (SKI) in TRD. TRD patients (N = 57, 49.12% female, mean age: 39.9) received four intravenous ketamine infusions (0.5 mg/kg) 2-3 days apart. Diffusion-weighted scans and clinical assessments (Hamilton Depression Rating Scale [HDRS-17]; Snaith Hamilton Pleasure Scale [SHAPS]) were collected at baseline and 24-h after SKI. WM measures including the neurite density index (NDI) and orientation dispersion index (ODI) from the neurite orientation dispersion and density imaging (NODDI) model, and fractional anisotropy (FA) from the diffusion tensor model were compared voxelwise pre- to post-SKI after using Tract-Based Spatial Statistics workflows to align WM tracts across subjects/time. Correlations between change in WM metrics and clinical measures were subsequently assessed. Following SKI, patients showed significant improvements in HDRS-17 (p-value = 1.8 E-17) and SHAPS (p-value = 1.97 E-10). NDI significantly decreased in occipitotemporal WM pathways (p < .05, FWER/TFCE corrected). ΔSHAPS significantly correlated with ΔNDI in the left internal capsule and left superior longitudinal fasciculus (r = -0.614, p-value = 6.24E-09). No significant changes in ODI or FA were observed. SKI leads to significant changes in the microstructural features of neurites within occipitotemporal tracts, and changes in neurite density within tracts connecting the basal ganglia, thalamus, and cortex relate to improvements in anhedonia. NODDI may be more sensitive for detecting ketamine-induced WM changes than DTI.

Modulation of brain networks during MR-compatible transcranial direct current stimulation.

Transcranial direct current stimulation (tDCS) can influence performance on behavioral tasks and improve symptoms of brain conditions. Yet, it remains unclear precisely how tDCS affects brain function and connectivity. Here, we measured changes in functional connectivity (FC) metrics in blood-oxygenation-level-dependent (BOLD) fMRI data acquired during MR-compatible tDCS in a whole-brain analysis with corrections for false discovery rate. Volunteers (n = 64) received active tDCS, sham tDCS, and rest (no stimulation), using one of three previously established electrode tDCS montages targeting left dorsolateral prefrontal cortex (DLPFC, n = 37), lateral temporoparietal area (LTA, n = 16), or superior temporal cortex (STC, n = 11). In brain networks where simulated E field was highest in each montage, connectivity with remote nodes decreased during active tDCS. During active DLPFC-tDCS, connectivity decreased between a fronto-parietal network and subgenual ACC, while during LTA-tDCS connectivity decreased between an auditory-somatomotor network and frontal operculum. Active DLPFC-tDCS was also associated with increased connectivity within an orbitofrontal network overlapping subgenual ACC. Irrespective of montage, FC metrics increased in sensorimotor and attention regions during both active and sham tDCS, which may reflect the cognitive-perceptual demands of tDCS. Taken together, these results indicate that tDCS may have both intended and unintended effects on ongoing brain activity, stressing the importance of including sham, stimulation-absent, and active comparators in basic science and clinical trials of tDCS.

Anterior default mode network and posterior insular connectivity is predictive of depressive symptom reduction following serial ketamine infusion.

BACKGROUND: Ketamine is a rapidly-acting antidepressant treatment with robust response rates. Previous studies have reported that serial ketamine therapy modulates resting state functional connectivity in several large-scale networks, though it remains unknown whether variations in brain structure, function, and connectivity impact subsequent treatment success. We used a data-driven approach to determine whether pretreatment multimodal neuroimaging measures predict changes along symptom dimensions of depression following serial ketamine infusion. METHODS: Patients with depression (n = 60) received structural, resting state functional, and diffusion MRI scans before treatment. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale (HDRS-17), the Inventory of Depressive Symptomatology (IDS-C), and the Rumination Response Scale (RRS) before and 24 h after patients received four (0.5 mg/kg) infusions of racemic ketamine over 2 weeks. Nineteen unaffected controls were assessed at similar timepoints. Random forest regression models predicted symptom changes using pretreatment multimodal neuroimaging and demographic measures. RESULTS: Two HDRS-17 subscales, the HDRS-6 and core mood and anhedonia (CMA) symptoms, and the RRS: reflection (RRSR) scale were predicted significantly with 19, 27, and 1% variance explained, respectively. Increased right medial prefrontal cortex/anterior cingulate and posterior insula (PoI) and lower kurtosis of the superior longitudinal fasciculus predicted reduced HDRS-6 and CMA symptoms following treatment. RRSR change was predicted by global connectivity of the left posterior cingulate, left insula, and right superior parietal lobule. CONCLUSIONS: Our findings support that connectivity of the anterior default mode network and PoI may serve as potential biomarkers of antidepressant outcomes for core depressive symptoms.

Modulation of the functional connectome in major depressive disorder by ketamine therapy.

BACKGROUND: Subanesthetic ketamine infusion therapy can produce fast-acting antidepressant effects in patients with major depression. How single and repeated ketamine treatment modulates the whole-brain functional connectome to affect clinical outcomes remains uncharacterized. METHODS: Data-driven whole brain functional connectivity (FC) analysis was used to identify the functional connections modified by ketamine treatment in patients with major depressive disorder (MDD). MDD patients (N = 61, mean age = 38, 19 women) completed baseline resting-state (RS) functional magnetic resonance imaging and depression symptom scales. Of these patients, n = 48 and n = 51, completed the same assessments 24 h after receiving one and four 0.5 mg/kg intravenous ketamine infusions. Healthy controls (HC) (n = 40, 24 women) completed baseline assessments with no intervention. Analysis of RS FC addressed effects of diagnosis, time, and remitter status. RESULTS: Significant differences (p < 0.05, corrected) in RS FC were observed between HC and MDD at baseline in the somatomotor network and between association and default mode networks. These disruptions in FC in MDD patients trended toward control patterns with ketamine treatment. Furthermore, following serial ketamine infusions, significant decreases in FC were observed between the cerebellum and salience network (SN) (p < 0.05, corrected). Patient remitters showed increased FC between the cerebellum and the striatum prior to treatment that decreased following treatment, whereas non-remitters showed the opposite pattern. CONCLUSION: Results support that ketamine treatment leads to neurofunctional plasticity between distinct neural networks that are shown as disrupted in MDD patients. Cortico-striatal-cerebellar loops that encompass the SN could be a potential biomarker for ketamine treatment.

Hippocampal subregions and networks linked with antidepressant response to electroconvulsive therapy.

Electroconvulsive therapy (ECT) has been repeatedly linked to hippocampal plasticity. However, it remains unclear what role hippocampal plasticity plays in the antidepressant response to ECT. This magnetic resonance imaging (MRI) study tracks changes in separate hippocampal subregions and hippocampal networks in patients with depression (n = 44, 23 female) to determine their relationship, if any, with improvement after ECT. Voxelwise analyses were restricted to the hippocampus, amygdala, and parahippocampal cortex, and applied separately for responders and nonresponders to ECT. In analyses of arterial spin-labeled (ASL) MRI, nonresponders exhibited increased cerebral blood flow (CBF) in bilateral anterior hippocampus, while responders showed CBF increases in right middle and left posterior hippocampus. In analyses of gray matter volume (GMV) using T1-weighted MRI, GMV increased throughout bilateral hippocampus and surrounding tissue in nonresponders, while responders showed increased GMV in right anterior hippocampus only. Using CBF loci as seed regions, BOLD-fMRI data from healthy controls (n = 36, 19 female) identified spatially separable neurofunctional networks comprised of different brain regions. In graph theory analyses of these networks, functional connectivity within a hippocampus-thalamus-striatum network decreased only in responders after two treatments and after index. In sum, our results suggest that the location of ECT-related plasticity within the hippocampus may differ according to antidepressant outcome, and that larger amounts of hippocampal plasticity may not be conducive to positive antidepressant response. More focused targeting of hippocampal subregions and/or circuits may be a way to improve ECT outcome.

Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls.

PURPOSE: Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations. METHODS: Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners. RESULTS: After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm3, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS. CONCLUSIONS: These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.

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.

Modulation of amygdala reactivity following rapidly acting interventions for major depression.

Electroconvulsive therapy (ECT) and ketamine treatment both induce rapidly acting antidepressant effects in patients with major depressive disorder unresponsive to standard treatments, yet their specific impact on emotion processing is unknown. Here, we examined the neural underpinnings of emotion processing within and across patients (N = 44) receiving either ECT (N = 17, mean age: 36.8, 11.0 SD) or repeated subanesthetic (0.5 mg/kg) intravenous ketamine therapy (N = 27, mean age: 37.3, 10.8 SD) using a naturalistic study design. MRI and clinical data were collected before (TP1) and after treatment (TP2); healthy controls (N = 31, mean age: 34.5, 13.5 SD) completed one MRI session (TP1). An fMRI face-matching task probed negative- and positive-valence systems. Whole-brain analysis, comparing neurofunctional changes within and across treatment groups, targeted brain regions involved in emotional facial processing, and included regions-of-interest analysis of amygdala responsivity. Main findings revealed a decrease in amygdalar reactivity after both ECT and ketamine for positive and negative emotional face processing (p < .05 family wise-error (FWE) corrected). Subthreshold changes were observed between treatments within the dorsolateral prefrontal cortex and insula (p < .005, uncorrected). BOLD change for positive faces in the inferior parietal cortex significantly correlated with overall symptom improvement, and BOLD change in frontal regions correlated with anxiety for negative faces, and anhedonia for positive faces (p < .05 FWE corrected). Both serial ketamine and ECT treatment modulate amygdala response, while more subtle treatment-specific changes occur in the larger functional network. Findings point to both common and differential mechanistic upstream systems-level effects relating to fast-acting antidepressant response, and symptoms of anxiety and anhedonia, for the processing of emotionally valenced stimuli.

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.

Inflammation and depression treatment response to electroconvulsive therapy: Sex-specific role of interleukin-8.

Females suffer from depression at twice the rate of males and have differential neural and emotional responses to inflammation. However, sex-specific evaluation of relationships between inflammation and response to depression treatments are lacking. Some data suggest that interleukin(IL)-8 predicts treatment response to antidepressants and has a relationship with depressive symptom severity. This study examines whether IL-8 predicts treatment response to electroconvulsive therapy (ECT), and whether there are sex specific effects. In 40 depressed patients (22 female), plasma levels of IL-8, as well as other markers of inflammation including IL-6, IL-10, tumor necrosis factor (TNF)-α, and C-reactive protein (CRP) were obtained prior to administration of ECT and after completion of the index treatment series. Depression treatment response was defined as ≥ 50% reduction in Hamilton Depression Rating Scale (HAM-D) Score. Baseline levels of IL-8 differed by responder status, depending on sex (group × sex interaction: ß = -0.571, p = 0.04), with female responders having lower levels of IL-8 at baseline as compared to female non-responders [t(20) = 2.37, p = 0.03]. Further, IL-8 levels from baseline to end of treatment differed by responder status, depending on sex (group × sex × time interaction: [F(1,36) = 9.48, p = 0.004]), and change in IL-8 from baseline to end of treatment was negatively correlated with percentage change in HAM-D score in females (ß = -0.458, p = 0.03), but not in males (ß = 0.315, p = 0.20). Other inflammatory markers did not differ in relation to responder status and sex. Further evaluation of sex differences in the relationship between IL-8, depression, and treatment response, across disparate treatment modalities, may inform mechanisms of response and aid in development of personalized medicine strategies.

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.

Acute changes in cerebral blood flow after single-infusion ketamine in major depression: a pilot study.

BACKGROUND: Ketamine provides rapid antidepressant response in those struggling with major depressive disorder (MDD). This study measured acute changes in brain activity over 24 hours after a single infusion of ketamine using arterial spin labeled (ASL) functional magnetic resonance imaging (fMRI) in patients with MDD. ASL is a novel technique that provides quantitative values to measure cerebral blood flow (CBF). METHODS: A single sub-anesthetic dose (0.5 mg/kg) of ketamine was delivered intravenously. Treatment-refractory patients (n=11) were assessed at: Baseline (pre-infusion), and approximately 1hr, 6hrs, and 24hrs post-infusion. Linear mixed-effects models detected changes in CBF with respect to treatment outcome, and results were corrected for false discovery rate (FDR). RESULTS: After ketamine infusion, increased CBF was observed in the thalamus, while decreased CBF was observed in lateral occipital cortex in all patients. Time-by-response interactions were noted in ventral basal ganglia and medial prefrontal cortex, where CBF change differed according to antidepressant response. LIMITATIONS: Modest sample size is a limitation of this pilot study; strict statistical correction and visualization of single-subject data attempted to ameliorate this issue. CONCLUSION: In this pilot study, a sub-anesthetic dose of ketamine was associated with acute neurofunctional changes that may be consistent with altered attention, specifically increased thalamus activity coupled with decreased cortical activity. By contrast, antidepressant response to ketamine was associated with changes in reward-system regions, specifically ventral basal ganglia and medial prefrontal cortex. Further work is needed to determine whether these results generalize to larger samples and/or serial ketamine infusions associated with longer-lasting clinical effects.