Electroconvulsive therapy (ECT), ketamine infusion (KI), and total sleep deprivation (TSD) are effective and fast in treating patients with treatment-resistant depression (TRD). However, it remains unclear whether the three treatments have the same effect on clinical symptom improvement and have common brain structural mechanisms.

The current study included 127 TRD patients and 37 healthy controls, which were obtained from the Perturbation of the Treatment Resistant Depression Connectome Project. We aimed to investigate the shared and distinct brain structural changes underlying clinical symptom improvement among ECT, KI, and TSD treatments.

All of the three treatments significantly reduced the depressive symptoms in TRD patients, but they differently affected other clinical measurements. Neuroimaging results also revealed that all of ECT, KI, and TSD treatments significantly increased gray matter volume of left caudate after treatment in TRD patients. However, the gray matter volume of other brain regions including hippocampus, parahippocampus, amygdala, insula, fusiform gyrus, several occipital and temporal areas was increased only after ECT treatment. Still, the baseline or the change of gray matter volume did not correlate with the depressive symptom improvement for all of the three treatments.

A higher sample size would be required to further validate our findings.

The results observed in the current study suggested that the ECT, KI, and TSD treatments differently affected clinical measurements and brain structures in TRD patients, though all of them were effective in depressive symptom improvement, which might facilitate the development of personalized treatment protocol for this disease.

Severe depression is associated with accelerated brain aging. BrainAge gap, the difference between predicted and observed BrainAge, was investigated in patients with late-life depression (LLD). We aimed to examine BrainAge gap in LLD and its associations with clinical characteristics indexing LLD chronicity, current severity, prior to electroconvulsive therapy (ECT) and ECT outcome.

Data was analyzed from the Mood Disorders in Elderly treated with Electroconvulsive Therapy (MODECT) study. A previously established BrainAge algorithm (BrainAge R by James Cole, (https://github.com/james-cole/brainageR)) was applied to pre-ECT T1-weighted structural MRI-scans of 42 patients who underwent ECT.

A BrainAge gap of 1.8 years (SD = 5.5) was observed, Cohen's d = 0.3. No significant associations between BrainAge gap, number of previous episodes, current episode duration, age of onset, depression severity, psychotic symptoms or ECT outcome were observed.

Limited sample size.

Our initial findings suggest an older BrainAge than chronological age in patients with severe LLD referred for ECT, however with high degree of variability and direction of the gap. No associations were found with clinical measures. Larger samples are needed to better understand brain aging and to evaluate the usability of BrainAge gap as potential biomarker of prognosis an treatment-response in LLD.

ClinicalTrials.gov identifier: NCT02667353.

Major depressive disorder (MDD) is accompanied by alterations in grey matter volume. However, the biological processes associated with regional structural perturbations remain elusive.

We applied integrative omics analysis to investigate specialized transcriptome signatures and translational determinants associated with regional grey matter variations in 2737 MDD patients relative to 3098 controls by summarizing the results from gene co-expression network analysis of Allen human brain transcriptome profiles in six donors, enrichment analysis of gene-sets and cellular structure from rodents and mediation analysis of BrainSpan proteome profile in six donors.

We found convergent alterations of grey matter volume in MDD were associated with transcriptome profiles enriched for synaptic transmission, metabolism, immune processes and transmembrane transport. Genes with abnormal expression in post-mortem tissue in MDD were also associated with transcriptome signatures. Further gene co-expression network and enrichment analysis of MDD-related genes in these signatures revealed the modules with higher neuronal expression were enriched in the medial temporal cortex and temporo-parietal junction with genes differentially associated with neuronal development and metabolism. Also, the modules with higher non-neuronal (e.g. astrocyte and oligodendrocyte) expression were concentrated in the rostral and dorsal anterior cingulate cortex and were separately associated with immune response and transmembrane transport. Moreover, proteins as the gene expression products mediated the association between transcriptome signatures and brain volume changes in the visual and dorsolateral prefrontal cortex.

Our multidimensional analyses offer a novel approach to detect specific biological pathways that capture regional structural variations in MDD, which suggests structural endophenotypes associated with MDD.

Electroconvulsive therapy (ECT) is an established treatment choice for severe, treatment-resistant depression, yet its mechanisms of action remain elusive. Magnetic resonance imaging (MRI) of the human brain before and after treatment has been crucial to aid our comprehension of the ECT neurobiological effects. However, to date, a majority of MRI studies have been underpowered and have used heterogeneous patient samples as well as different methodological approaches, altogether causing mixed results and poor clinical translation. Hence, an association between MRI markers and therapeutic response remains to be established. Recently, the availability of large datasets through a global collaboration has provided the statistical power needed to characterize whole-brain structural and functional brain changes after ECT. In addition, MRI technological developments allow new aspects of brain function and structure to be investigated. Finally, more recent studies have also investigated immediate and long-term effects of ECT, which may aid in the separation of the therapeutically relevant effects from epiphenomena. The goal of this review is to outline MRI studies (T1, diffusion-weighted imaging, proton magnetic resonance spectroscopy) of ECT in depression to advance our understanding of the ECT neurobiological effects. Based on the reviewed literature, we suggest a model whereby the neurobiological effects can be understood within a framework of disruption, neuroplasticity, and rewiring of neural circuits. An improved characterization of the neurobiological effects of ECT may increase our understanding of ECT's therapeutic effects, ultimately leading to improved patient care.

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.

Although electroconvulsive therapy (ECT) is a safe and effective treatment for patients with severe late life depression (LLD), transient cognitive impairment can be a reason to discontinue the treatment. The aim of the current study was to evaluate the association between structural brain characteristics and general cognitive function during and after ECT.

A total of 80 patients with LLD from the prospective naturalistic follow-up Mood Disorders in Elderly treated with Electroconvulsive Therapy study were examined. Magnetic resonance imaging scans were acquired before ECT. Overall brain morphology (white and grey matter) was evaluated using visual rating scales. Cognitive functioning before, during, and after ECT was measured using the Mini Mental State Examination (MMSE). A linear mixed-model analysis was performed to analyze the association between structural brain alterations and cognitive functioning over time.

Patients with moderate to severe white matter hyperintensities (WMH) showed significantly lower MMSE scores than patients without severe WMH (F(1,75.54) = 5.42, p = 0.02) before, during, and post-ECT, however their trajectory of cognitive functioning was similar as no time × WMH interaction effect was observed (F(4,65.85) = 1.9, p = 0.25). Transient cognitive impairment was not associated with medial temporal or global cortical atrophy (MTA, GCA).

All patients showed a significant drop in cognitive functioning during ECT, which however recovered above baseline levels post-ECT and remained stable until at least 6 months post-ECT, independently of severity of WMH, GCA, or MTA. Therefore, clinicians should not be reluctant to start or continue ECT in patients with severe structural brain alterations.

Psychotic major depression (PMD) is hypothesized to be a distinct clinical entity from nonpsychotic major depression (NPMD). However, neurobiological evidence supporting this notion is scarce. The aim of this study is to identify gray matter volume (GMV) differences between PMD and NPMD and their longitudinal change following electroconvulsive therapy (ECT). Structural magnetic resonance imaging (MRI) data from 8 independent sites in the Global ECT-MRI Research Collaboration (GEMRIC) database (n = 108; 56 PMD and 52 NPMD; mean age 71.7 in PMD and 70.2 in NPMD) were analyzed. All participants underwent MRI before and after ECT. First, cross-sectional whole-brain voxel-wise GMV comparisons between PMD and NPMD were conducted at both time points. Second, in a flexible factorial model, a main effect of time and a group-by-time interaction were examined to identify longitudinal effects of ECT on GMV and longitudinal differential effects of ECT between PMD and NPMD, respectively. Compared with NPMD, PMD showed lower GMV in the prefrontal, temporal and parietal cortex before ECT; PMD showed lower GMV in the medial prefrontal cortex (MPFC) after ECT. Although there was a significant main effect of time on GMV in several brain regions in both PMD and NPMD, there was no significant group-by-time interaction. Lower GMV in the MPFC was consistently identified in PMD, suggesting this may be a trait-like neural substrate of PMD. Longitudinal effect of ECT on GMV may not explain superior ECT response in PMD, and further investigation is needed.

Several neuroimaging studies have investigated localized aberrations in brain structure, function or connectivity in late-life depression, but the ensuing results are equivocal and often conflicting. Here, we provide a quantitative consolidation of neuroimaging in late-life depression using coordinate-based meta-analysis by searching multiple databases up to March 2020. Our search revealed 3252 unique records, among which we identified 32 eligible whole-brain neuroimaging publications comparing 674 patients with 568 controls. The peak coordinates of group comparisons between the patients and the controls were extracted and then analyzed using activation likelihood estimation method. Our sufficiently powered analysis on all the experiments, and more homogenous subsections of the data (patients > controls, controls > patients, and functional imaging experiments) revealed no significant convergent regional abnormality in late-life depression. This inconsistency might be due to clinical and biological heterogeneity of LLD, as well as experimental (e.g., choice of tasks, image modalities) and analytic flexibility (e.g., preprocessing and analytic parameters), and distributed patterns of neural abnormalities. Our findings highlight the importance of clinical/biological heterogeneity of late-life depression, in addition to the need for more reproducible research by using pre-registered and standardized protocols on more homogenous populations to identify potential consistent brain abnormalities in late-life depression.

Electroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of ECT in a non-randomized prospective study focusing on white matter changes over time.

Twenty-nine severely depressed patients receiving ECT in addition to inpatient treatment, 69 severely depressed patients with inpatient treatment (NON-ECT) and 52 healthy controls (HC) took part in a non-randomized prospective study. Participants were scanned twice, approximately 6 weeks apart, using diffusion tensor imaging, applying tract-based spatial statistics. Additional correlational analyses were conducted in the ECT subsample to investigate the effects of seizure duration and therapeutic response.

Mean diffusivity (MD) increased after ECT in the right hemisphere, which was an ECT-group-specific effect. Seizure duration was associated with decreased fractional anisotropy (FA) following ECT. Longitudinal changes in ECT were not associated with therapy response. However, within the ECT group only, baseline FA was positively and MD negatively associated with post-ECT symptomatology.

Our data suggest that ECT changes white matter integrity, possibly reflecting increased permeability of the blood-brain barrier, resulting in disturbed communication of fibers. Further, baseline diffusion metrics were associated with therapy response. Coherent fiber structure could be a prerequisite for a generalized seizure and inhibitory brain signaling necessary to successfully inhibit increased seizure activity.

Electroconvulsive therapy (ECT) has been shown to be effective in schizophrenia, particularly when rapid symptom reduction is needed or in cases of resistance to drug treatment. However, there are no markers available to predict response to ECT. Here, we examine whether multi-parametric magnetic resonance imaging (MRI)-based radiomic features can predict response to ECT for individual patients. A total of 57 treatment-resistant schizophrenia patients, or schizophrenia patients with an acute episode or suicide attempts were randomly divided into primary (42 patients) and test (15 patients) cohorts. We collected T1-weighted structural MRI and diffusion MRI for 57 patients before receiving ECT and extracted 600 radiomic features for feature selection and prediction. To predict a continuous improvement in symptoms (ΔPANSS), the prediction process was performed with a support vector regression model based on a leave-one-out cross-validation framework in primary cohort and was tested in test cohort. The multi-parametric MRI-based radiomic model, including four structural MRI feature from left inferior frontal gyrus, right insula, left middle temporal gyrus and right superior temporal gyrus respectively and six diffusion MRI features from tracts connecting frontal or temporal gyrus possessed a low root mean square error of 15.183 in primary cohort and 14.980 in test cohort. The Pearson's correlation coefficients between predicted and actual values were 0.671 and 0.777 respectively. These results demonstrate that multi-parametric MRI-based radiomic features may predict response to ECT for individual patients. Such features could serve as prognostic neuroimaging biomarkers that provide a critical step toward individualized treatment response prediction in schizophrenia.

Major depressive disorder is a frequent and disabling disease and can be treated with antidepressant drugs. When faced with severe or resistant major depressive disorder, however, psychiatrists may resort to electroconvulsive therapy (ECT). Although very effective, the response falls short of 100%. A recent meta-analysis established clinical and biological predictive factors of the response to ECT. We decided to explore neuroimaging biomarkers that could be predictors of the ECT response.

We performed a systematic literature review up to January 1, 2018, using a Boolean combination of MeSH terms. We included 19 studies matching our inclusion criteria.

Lower hippocampal, increased amygdala, and subgenual cingulate gyrus volumes were predictive for a better ECT response. Functional magnetic resonance imaging also found that the connectivity between the dorsolateral prefrontal cortex and posterior default-mode network is predictive of increased efficacy. Conversely, deep white matter hyperintensities in basal ganglia and Virchow-Robin spaces, medial temporal atrophy, ratio of left superior frontal to left rostral middle frontal cortical thickness, cingulate isthmus thickness asymmetry, and a wide range of gray and white matter anomalies were predictive for a poorer response.

Our review addresses the positive or negative predictive value of neuroimaging biomarkers for the ECT response, indispensable in a personalized medicine dynamic. These data could reduce the risk of nonresponders or resistance with earlier effective management. It might also help researchers elucidate the complex pathophysiology of depressive disorders and the functioning of ECT.

Gray matter volume decrease, white matter vascular pathology and amyloid accumulation are age-related brain changes that have been related to the pathogenesis of late life depression (LLD). Furthermore, lower hippocampal volume and more white matter hyperintensities (WMH) may contribute to poor response to electroconvulsive therapy (ECT) in severely depressed older adults. We hypothesized that the accumulation of age-related brain changes negatively affects outcome following ECT in LLD.

34 elderly patients with severe LLD were treated twice weekly with ECT until remission. All had both 3T structural magnetic resonance imaging (MRI) and β-amyloid positron emission tomography (PET) imaging using 18F-flutemetamol at baseline. MADRS and MMSE were obtained weekly which included 1 week prior to ECT (T0), after the sixth ECT (T1), and one week (T2) after the last ECT as well as at four weeks (T3) and 6 months (T4) after the last ECT. We conducted a multiple logistic regression analysis and a survival analysis with neuroimaging measures as predictors, and response, remission and relapse as outcome variable.

We did not find any association between baseline hippocampal volume, white matter hyperintensity volume and total amyloid load and response or remission at 1 and 4 weeks post ECT, nor with relapse at week 4.

The present exploratory study was conducted at a single center academic hospital, the sample size was small, the focus was on hippocampal volume and the predictive effect of structural and molecular changes associated with aging were used.

Our study shows no evidence of relationship between response to ECT and age-related structural or molecular brain changes, implying that ECT can be applied effectively in depressed patients irrespective of accumulating age-related brain changes.

Current practice for selecting pharmacological and non-pharmacological antidepressant treatments has yielded low response and remission rates in Major Depressive Disorder (MDD). Neuroimaging biomarkers of brain structure and function may be useful in guiding treatment selection by predicting response vs. non-response outcomes.

In this review, we summarize data from studies examining predictors of treatment response using structural and functional neuroimaging modalities, as they pertain to pharmacotherapy, psychotherapy, and stimulation treatment strategies. A literature search was conducted in OVID Medline, EMBASE, and PsycINFO databases with coverage from January 1990 to January 2017.

Several imaging biomarkers of therapeutic response in MDD emerged: frontolimbic regions, including the prefrontal cortex, anterior cingulate cortex, hippocampus, amygdala, and insula were regions of interest. Since these sub-regions are implicated in the etiology of MDD, their association with response outcomes may be the result of treatments having a normalizing effect on structural or activation abnormalities.

The direction of findings is inconsistent in studies examining these biomarkers, and variation across 'biotypes' within MDD may account for this. Limitations in sample size and differences in methodology likely also contribute.

The identification of accurate, reliable neuroimaging biomarkers of treatment response holds promise toward improving treatment outcomes and reducing burden of illness for patients with MDD. However, before these biomarkers can be translated into clinical practice, they will need to be replicated and validated in large, independent samples, and integrated with data from other biological systems.

Owing to the rapid and robust clinical effects, electroconvulsive therapy (ECT) represents an optimal model to develop and test treatment predictors for major depressive disorders (MDDs), whereas imaging markers can be informative in identifying MDD patients who will respond to a specific antidepressant treatment or not. Here we aim to predict post-ECT depressive rating changes and remission status using pre-ECT gray matter (GM) in 38 MDD patients and validate in two independent data sets. Six GM regions including the right hippocampus/parahippocampus, right orbitofrontal gyrus, right inferior temporal gyrus (ITG), left postcentral gyrus/precuneus, left supplementary motor area, and left lingual gyrus were identified as predictors of ECT response, achieving accuracy of 89, 90 and 86% for remission prediction in three independent, age-matched data sets, respectively. For MDD patients, GM density increases only in the left supplementary motor cortex and left postcentral gyrus/precuneus after ECT. These results suggest that treatment-predictive and treatment-responsive regions may be anatomically different but functionally related in the context of ECT response. To the best of our knowledge, this is the first attempt to quantitatively identify and validate the ECT treatment biomarkers using multi-site GM data. We address a major clinical challenge and provide potential opportunities for more effective and timely interventions for electroconvulsive treatment.

Mood and anxiety disorders are very commonly experienced by older adults and are becoming a growing concern due to the rapidly aging global population. Recent advances in neuroimaging may help in improving outcomes in late-life mood and anxiety disorders. The elucidation of mechanisms contributing to late-life mental health disorders may ultimately lead to the identification of novel therapeutic interventions. Alternatively, clinically validated imaging biomarkers may allow for the prediction of treatment response and identification of better therapeutic approaches in late-life mood and anxiety disorders.

In community samples, late-life depression and late-life generalized anxiety disorder occur up to 38 and 15%, respectively, while late-life bipolar disorder is less common and occur in approximately 0.5% of the population. There are significant challenges in treating and improving outcome in late-life mood and anxiety disorders. Time to treatment response and treatment resistance are increased in older adults. Novel neuroimaging techniques have the potential to improve diagnostic and therapeutic outcome in late-life mood and anxiety disorders either through "personalized pharmacotherapy" or through identifying dysfunction regions/networks to be subsequently used for direct interventions such as transcranial magnetic stimulation. This review will provide an overview of recent literature that substantiates the potential role of neuroimaging in clinical practice, as well as the barriers that must be overcome prior to clinical translation.

Electroconvulsive therapy (ECT) is considered to be the most effective treatment in severe major depression. The identification of reliable predictors of ECT response could contribute to a more targeted patient selection and consequently increased ECT response rates. Aims To investigate the predictive value of age, depression severity, psychotic and melancholic features for ECT response and remission in major depression.

A meta-analysis was conducted according to the PRISMA statement. A literature search identified recent studies that reported on at least one of the potential predictors.

Of the 2193 articles screened, 34 have been included for meta-analysis. Presence of psychotic features is a predictor of ECT remission (odds ratio (OR) = 1.47, P = 0.001) and response (OR = 1.69, P < 0.001), as is older age (standardised mean difference (SMD) = 0.26 for remission and 0.35 for response (P < 0.001)). The severity of depression predicts response (SMD = 0.19, P = 0.001), but not remission. Data on melancholic symptoms were inconclusive.

ECT is particularly effective in patients with depression with psychotic features and in elderly people with depression. More research on both biological and clinical predictors is needed to further evaluate the position of ECT in treatment protocols for major depression. Declaration of interest None.

Electroconvulsive therapy (ECT) is a non-pharmacological treatment that is effective in treating severe and treatment-resistant depression. Although the efficacy of ECT has been demonstrated to treat major depressive disorder (MDD), the brain mechanisms underlying this process remain unclear. Structural-functional changes occur with the use of ECT as a treatment for depression based on magnetic resonance imaging (MRI). For this reason, we have tried to identify the changes that were identified by MRI to try to clarify some operating mechanisms of ECT. We focus to brain changes on MRI [structural MRI (sMRI), functional MRI (fMRI) and diffusion tensor imging (DTI)] after ECT.

A systematic search of the international literature was performed using the bibliographic search engines PubMed and Embase. The research focused on papers published up to 30 September 2015. The following Medical Subject Headings (MESH) terms were used: electroconvulsive therapy AND (MRI OR fMRI OR DTI). Papers published in English were included. Four authors searched the database using a predefined strategy to identify potentially eligible studies.

There were structural changes according to the sMRI performed before and after ECT treatment. These changes do not seem to be entirely due to oedema. This investigation assessed the functional network connectivity associated with the ECT response in MDD. ECT response reverses the relationship from negative to positive between the two pairs of networks.

We found structural-functional changes in MRI post-ECT. Because of the currently limited MRI data on ECT in the literature, it is necessary to conduct further investigations using other MRI technology.

We systematically reviewed and meta-analyzed the association of late-life depression (LLD) with hippocampal volume (HCV) and total brain volume (TBV), and of cortisol levels with HCV, including subgroup analyses of depression characteristics and methodological aspects.

We searched PubMed and Embase for original studies that examined the cross-sectional relationship between LLD and HCV or TBV, and 46 studies fulfilled the inclusion criteria. Standardized mean differences (Hedges' g) between LLD and control subjects were calculated from crude or adjusted brain volumes using random effects. Standardized Fisher transformations of the correlations between cortisol levels and HCVs were calculated using random effects.

We included 2702 LLD patients and 11,165 control subjects from 35 studies examining HCV. Relative to control subjects, patients had significantly smaller HCVs (standardized mean difference = -0.32 [95% confidence interval, -0.44 to -0.19]). Subgroup analyses showed that late-onset depression was more strongly associated with HCV than early-onset depression. In addition, effect sizes were larger for case-control studies, studies with lower quality, and studies with small sample size, and were almost absent in cohort studies and studies with larger sample sizes. For TBV, 2523 patients and 7880 control subjects from 31 studies were included. The standardized mean difference in TBV between LLD and control subjects was -0.10 (95% confidence interval, -0.16 to -0.04). Of the 12 studies included, higher levels of cortisol were associated with smaller HCV (correlation = -0.11 [95% confidence interval, -0.18 to -0.04]).

While an overall measure of LLD may be associated with smaller HCVs, differentiating clinical aspects of LLD and examining methodological issues show that this relationship is not straightforward.

The clinical profile of late-life depression (LLD) is frequently associated with cognitive impairment, aging-related brain changes, and somatic comorbidity. This two-site naturalistic longitudinal study aimed to explore differences in clinical and brain characteristics and response to electroconvulsive therapy (ECT) in early- (EOD) versus late-onset (LOD) late-life depression (respectively onset <55 and ≥55 years).

Between January 2011 and December 2013, 110 patients aged 55 years and older with ECT-treated unipolar depression were included in The Mood Disorders in Elderly treated with ECT study. Clinical profile and somatic health were assessed. Magnetic resonance imaging (MRI) scans were performed before the first ECT and visually rated.

Response rate was 78.2% and similar between the two sites but significantly higher in LOD compared with EOD (86.9 versus 67.3%). Clinical, somatic, and brain characteristics were not different between EOD and LOD. Response to ECT was associated with late age at onset and presence of psychotic symptoms and not with structural MRI characteristics. In EOD only, the odds for a higher response were associated with a shorter index episode.

The clinical profile, somatic comorbidities, and brain characteristics in LLD were similar in EOD and LOD. Nevertheless, patients with LOD showed a superior response to ECT compared with patients with EOD. Our results indicate that ECT is very effective in LLD, even in vascular burdened patients.

The aims of this naturalistic study are to examine psychiatric rehospitalization rates in geriatric compared to nongeriatric patients who receive electroconvulsive therapy (ECT) and to characterize the sustained effectiveness of ECT for treatment of depression.

Retrospective review of electronic medical records at a tertiary care center for patients with major depressive disorder who received an acute course of ECT at an index psychiatric hospitalization over a 5-year period. Data for subsequent psychiatric and primary care encounters were ascertained by chart review. Outcomes of interest included between-group differences in rates of psychiatric rehospitalization, time to rehospitalization, rates of other types of clinical follow-up care, and effect of demographic variables on clinical outcome.

Of 482 total patients, there were 210 (44%) geriatric patients (≥65 years). These patients experienced lower overall rates of psychiatric rehospitalization after ECT (6.2% vs 22%; P < 0.0001) compared to the nongeriatric group. Cox proportional hazard models indicated that older age, assessed both as a dichotomous and continuous variable, was associated with lower risk of rehospitalization. The majority (76.9%) of detected rehospitalizations among geriatric patients occurred within 6 months. In comparison, rates of outpatient primary care and psychiatric follow-up after ECT did not differ as a function of age.

Our findings suggest that geriatric patients with major depression receive greater long-term benefit from an acute course of ECT than do nongeriatric patients. Much more research is needed on this topic to rigorously evaluate the long-term efficacy of ECT in geriatric populations.

The evidence on the mechanisms of action of electroconvulsive therapy (ECT) has grown over the past decades. Recent studies show an ECT-related increase in hippocampal, amygdala and subgenual cortex volume. We examined grey matter volume changes following ECT using voxel-based morphometry (VBM) whole brain analysis in patients with severe late life depression (LLD).

Elderly patients with unipolar depression were treated twice weekly with right unilateral ECT until remission on the Montgomery-Åsberg Depression Rating Scale (MADRS) was achieved. Cognition (Mini Mental State Examination) and psychomotor changes (CORE Assessment) were monitored at baseline and 1 week after the last session of ECT. We performed 3 T structural MRI at both time points. We used the VBM8 toolbox in SPM8 to study grey matter volume changes. Paired t tests were used to compare pre- and post-ECT grey matter volume (voxel-level family-wise error threshold p < 0.05) and to assess clinical response.

Twenty-eight patients (mean age 71.9 ± 7.8 yr, 8 men) participated in our study. Patients received a mean of 11.2 ± 4 sessions of ECT. The remission rate was 78.6%. Cognition, psychomotor agitation and psychomotor retardation improved significantly (p < 0.001). Right-hemispheric grey matter volume was increased in the caudate nucleus, medial temporal lobe (including hippocampus and amygdala), insula and posterior superior temporal regions but did not correlate with MADRS score. Grey matter volume increase in the caudate nucleus region correlated significantly with total CORE Assessment score (r = 0.63; p < 0.001).

Not all participants were medication-free.

Electroconvulsive therapy in patients with LLD is associated with significant grey matter volume increase, which is most pronounced ipsilateral to the stimulation side.

Depression is frequent in old age and its prognosis is poorer than in younger populations. The use of pharmacological treatments in geriatric depression is limited by specific pharmacodynamic age-related factors that can diminish tolerability and increase the risk of drug interactions. The possibility of modulating cerebral activity using brain stimulation techniques could result in treating geriatric depression more effectively while reducing systemic side effects and medication interactions. This may subsequently improve treatment adherence and overall prognosis in the older patient. Among clinically available neuromodulatory techniques, electroconvulsive therapy (ECT) remains the gold standard for the treatment of severe depression in the elderly. Studies have proven that ECT is more effective and has a faster onset of action than antidepressants in the treatment of severe, unipolar, geriatric depression and that older age is a predictor of rapid ECT response and remission. The application of novel and more tolerable forms of ECT for geriatric depression is currently being examined. Preliminary results suggest that right unilateral ultrabrief ECT (RUL-UB ECT) is a promising intervention, with similar efficacy to brief-pulse ECT and fewer adverse cognitive effects. Overall findings in repetitive transcranial magnetic stimulation (rTMS) suggest that it is a safe intervention in geriatric depression. Higher rTMS stimulation intensity and more treatments may need to be given in the elderly to achieve optimal results. There is no specific data on vagus nerve stimulation in the elderly. Transcranial direct current stimulation, magnetic seizure therapy and deep brain stimulation are currently experimental, and more data from geriatric samples is needed.