Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation.

OBJECTIVES: Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross-sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)-based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth. METHODS: Five different tractography methods were compared (three DTI-based and two CSD-based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver-operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes. RESULTS: Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD-based compared to DTI-based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD-based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE < .05). CONCLUSIONS: CSD-based CST tractograms were more accurate than DTI-based ones when validated using DES-based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice.

Preliminary evidence for preserved synaptic density in late-life depression.

Late-life depression has been consistently associated with lower gray matter volume, the origin of which remains largely unexplained. Recent in-vivo PET findings in early-onset depression and Alzheimer's Disease suggest that synaptic deficits contribute to the pathophysiology of these disorders and may therefore contribute to lower gray matter volume in late-life depression. Here, we investigate synaptic density in vivo for the first time in late-life depression using the synaptic vesicle glycoprotein 2A receptor radioligand 11C-UCB-J. We included 24 currently depressed adults with late-life depression (73.0 ± 6.2 years, 16 female, geriatric depression scale = 19.5 ± 6.8) and 36 age- and gender-matched healthy controls (70.4 ± 6.2 years, 21 female, geriatric depression scale = 2.7 ± 2.9) that underwent simultaneous 11C-UCB-J positron emission tomography (PET) and 3D T1- and T2-FLAIR weighted magnetic resonance (MR) imaging on a 3-tesla PET-MR scanner. We used analyses of variance to test for 11C-UCB-J binding and gray matter volumes differences in regions implicated in depression. The late-life depression group showed a trend in lower gray matter volumes in the hippocampus (p = 0.04), mesial temporal (p = 0.02) and prefrontal cortex (p = 0.02) compared to healthy control group without surviving correction for multiple comparison. However, no group differences in 11C-UCB-J binding were found in these regions nor were any associations between 11C-UCB-J and depressive symptoms. Our data suggests that, in contrast to Alzheimer's Disease, lower gray matter volume in late-life depression is not associated with synaptic density changes. From a therapeutic standpoint, preserved synaptic density in late-life depression may be an encouraging finding.

A voxel- and source-based morphometry analysis of grey matter volume differences in very-late-onset schizophrenia-like psychosis.

BACKGROUND: Very-late-onset schizophrenia-like psychosis (VLOSLP) is associated with significant burden. Its clinical importance is increasing as the global population of older adults rises, yet owing to limited research in this population, the neurobiological underpinnings of VLOSP remain insufficiently clarified. Here we address this knowledge gap using novel morphometry techniques to investigate grey matter volume (GMV) differences between VLOSLP and healthy older adults, and their correlations with neuropsychological scores. METHODS: In this cross-sectional study, we investigated whole-brain GMV differences between 35 individuals with VLOSLP (mean age 76.7, 26 female) and 36 healthy controls (mean age 75.7, 27 female) using whole-brain voxel-based morphometry (VBM) and supplementary source-based morphometry (SBM) on high resolution 3D T1-weighted MRI images. Additionally, we investigated relationships between GMV differences and cognitive function assessed with an extensive neuropsychological battery. RESULTS: VBM showed lower GMV in the thalamus, left inferior frontal gyrus and left insula in patients with VLOSLP compared to healthy controls. SBM revealed lower thalamo-temporal GMV in patients with VLOSLP. Processing speed, selective attention, mental flexibility, working memory, verbal memory, semantic fluency and confrontation naming were impaired in patients with VLOSLP. Correlations between thalamic volumes and memory function were significant within the group of individuals with VLOSLP, whereas no significant associations remained in the healthy controls. CONCLUSIONS: Lower GMV in the thalamus and fronto-temporal regions may be part of the underlying neurobiology of VLOSLP, with lower thalamic GMV contributing to memory impairment in the disorder.

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.

Acoustic stimulation as a promising technique to enhance slow-wave sleep in Alzheimer's disease: results of a pilot study.

STUDY OBJECTIVES: Sleep disturbances are common in people with Alzheimer's disease (AD), and a reduction in slow-wave activity is the most striking underlying change. Acoustic stimulation has emerged as a promising approach to enhance slow-wave activity in healthy adults and people with amnestic mild cognitive impairment. In this phase 1 study we investigated, for the first time, the feasibility of acoustic stimulation in AD and piloted the effect on slow-wave sleep (SWS). METHODS: Eleven adults with mild to moderate AD first wore the DREEM 2 headband for 2 nights to establish a baseline registration. Using machine learning, the DREEM 2 headband automatically scores sleep stages in real time. Subsequently, the participants wore the headband for 14 consecutive "stimulation nights" at home. During these nights, the device applied phase-locked acoustic stimulation of 40-dB pink noise delivered over 2 bone-conductance transducers targeted to the up-phase of the delta wave or SHAM, if it detected SWS in sufficiently high-quality data. RESULTS: Results of the DREEM 2 headband algorithm show a significant average increase in SWS (minutes) [t(3.17) = 33.57, P = .019] between the beginning and end of the intervention, almost twice as much time was spent in SWS. Consensus scoring of electroencephalography data confirmed this trend of more time spent in SWS [t(2.4) = 26.07, P = .053]. CONCLUSIONS: Our phase 1 study provided the first evidence that targeted acoustic stimuli is feasible and could increase SWS in AD significantly. Future studies should further test and optimize the effect of stimulation on SWS in AD in a large randomized controlled trial. CITATION: Van den Bulcke L, Peeters A-M, Heremans E, et al. Acoustic stimulation as a promising technique to enhance slow-wave sleep in Alzheimer's disease: results of a pilot study. J Clin Sleep Med. 2023;19(12):2107-2112.

Mild Motor Signs in Healthy Aging Are Associated with Lower Synaptic Density in the Brain.

OBJECTIVE: To investigate whether mild motor signs (MMS) in old age correlate with synaptic density in the brain. BACKGROUND: Normal aging is associated with a decline in movement quality and quantity, commonly termed "mild parkinsonian signs" or more recently MMS. Whether MMS stem from global brain aging or pathology within motor circuits remains unresolved. The synaptic vesicle glycoprotein 2A positron emission tomography (PET) ligand 11 C-UCB-J allows the investigation of brain-motor associations at the synaptic level in vivo. METHOD: Fifty-eight healthy older adults (≥50 years) were included from two monocentric control cohorts. Brain magnetic resonance imaging and 11 C-UCB-J PET data were available in 54 participants. 11 C-UCB-J PET binding was quantified by standardized uptake value ratio (SUVR) values in grey matter (GM) volumes of interest (VOIs): caudate, putamen, globus pallidus, substantia nigra, thalamus, cerebellum, and the frontal, parietal, temporal, and occipital cortex. Multiple linear regression analyses were performed with Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score measuring MMS as the dependent variable and mean SUVR values in each VOI as the independent variable with age, Fazekas score (white matter lesion [WML] load), VOI and cohort as covariates. RESULTS: Participants (68 ± 7.5 years; 52% female) had an average MDS-UPDRS part III score of 3.3 ± 2.8. The MDS-UPDRS part III score was inversely associated with synaptic density, independently of WML load or GM volume, in the caudate, substantia nigra, thalamus, cerebellum, and parietal, occipital, temporal cortex. Cohen's f2 showed moderate effect sizes for subcortical (range, 0.30-0.35), cortical (0.28-0.35) and cerebellar VOIs (0.31). CONCLUSION: MMS in healthy aging are associated with lower synaptic density throughout the brain. © 2023 International Parkinson and Movement Disorder Society.

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

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

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

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

The neurobiological basis of affect is consistent with psychological construction theory and shares a common neural basis across emotional categories.

Affective experience colours everyday perception and cognition, yet its fundamental and neurobiological basis is poorly understood. The current debate essentially centers around the communalities and specificities across individuals, events, and emotional categories like anger, sadness, and happiness. Using fMRI during the experience of these emotions, we critically compare the two dominant conflicting theories on human affect. Basic emotion theory posits emotions as discrete universal entities generated by dedicated emotion category-specific neural circuits, while psychological construction theory claims emotional events as unique, idiosyncratic, and constructed by psychological primitives like core affect and conceptualization, which underlie each emotional event and operate in a predictive framework. Based on the findings of 8 a priori-defined model-specific prediction tests on the neural response amplitudes and patterns, we conclude that the neurobiological basis of affect is primarily characterized by idiosyncratic mechanisms and a common neural basis shared across emotion categories, consistent with psychological construction theory. The findings provide further insight into the organizational principles of the neural basis of affect and brain function in general. Future studies in clinical populations with affective symptoms may reveal the corresponding underlying neural changes from a psychological construction perspective.

An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI.

Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals.

An optimized MRI and PET based clinical protocol for improving the differential diagnosis of geriatric depression and Alzheimer's disease.

Amyloid positron emission tomography (PET) and hippocampal volume derived from magnetic resonance imaging may be useful clinical biomarkers for differentiating between geriatric depression and Alzheimer's disease (AD). Here we investigated the incremental value of using hippocampal volume and 18F-flutemetmol amyloid PET measures in tandem and sequentially to improve discrimination in unclassified participants. Two approaches were compared in 41 participants with geriatric depression and 27 participants with probable AD: (1) amyloid and hippocampal volume combined in one model and (2) classification based on hippocampal volume first and then subsequent stratification using standardized uptake value ratio (SUVR)-determined amyloid positivity. Hippocampal volume and amyloid SUVR were significant diagnostic predictors of depression (sensitivity: 95%, specificity: 89%). 51% of participants were correctly classified according to clinical diagnosis based on hippocampal volume alone, increasing to 87% when adding amyloid data (sensitivity: 94%, specificity: 78%). Our results suggest that hippocampal volume may be a useful gatekeeper for identifying depressed individuals at risk for AD who would benefit from additional amyloid biomarkers when available.

Neural Substrates of Psychotic Depression: Findings From the Global ECT-MRI Research Collaboration.

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.

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

Lower regional gray matter volume in the absence of higher cortical amyloid burden in late-life depression.

Late-life depression (LLD) is associated with a risk of developing Alzheimer's disease (AD). However, the role of AD-pathophysiology in LLD, and its association with clinical symptoms and cognitive function are elusive. In this study, one hundred subjects underwent amyloid positron emission tomography (PET) imaging with [18F]-flutemetamol and structural MRI: 48 severely depressed elderly subjects (age 74.1 ± 7.5 years, 33 female) and 52 age-/gender-matched healthy controls (72.4 ± 6.4 years, 37 female). The Geriatric Depression Scale (GDS) and Rey Auditory Verbal Learning Test (RAVLT) were used to assess the severity of depressive symptoms and episodic memory function respectively. Amyloid deposition was quantified using the standardized uptake value ratio. Whole-brain voxel-wise comparisons of amyloid deposition and gray matter volume (GMV) between LLD and controls were performed. Multivariate analysis of covariance was conducted to investigate the association of regional differences in amyloid deposition and GMV with clinical factors, including GDS and RAVLT. As a result, there were no significant group differences in amyloid deposition. In contrast, LLD showed significant lower GMV in the left temporal and parietal region. GMV reduction in the left temporal region was associated with episodic memory dysfunction, but not with depression severity. Regional GMV reduction was not associated with amyloid deposition. LLD is associated with lower GMV in regions that overlap with AD-pathophysiology, and which are associated with episodic memory function. The lack of corresponding associations with amyloid suggests that lower GMV driven by non-amyloid pathology may play a central role in the neurobiology of LLD presenting as a psychiatric disorder.Trial registration: European Union Drug Regulating Authorities Clinical Trials identifier: EudraCT 2009-018064-95.

Diffusion kurtosis imaging of white matter in bipolar disorder.

White matter pathology likely contributes to the pathogenesis of bipolar disorder (BD). Most studies of white matter in BD have used diffusion tensor imaging (DTI), but the advent of more advanced multi-shell diffusion MRI imaging offers the possibility to investigate other aspects of white matter microstructure. Diffusion kurtosis imaging (DKI) extends the DTI model and provides additional measures related to diffusion restriction. Here, we investigated white matter in BD by applying whole-brain voxel-based analysis (VBA) and a network-based connectivity approach using constrained spherical deconvolution tractography to assess differences in DKI and DTI metrics between BD (n = 25) and controls (n = 24). The VBA showed lower mean kurtosis in the corona radiata and posterior association fibers in BD. Regional differences in connectivity were indicated by lower mean kurtosis and kurtosis anisotropy in streamlines traversing the temporal and occipital lobes, and lower mean axial kurtosis in the right cerebellar, thalamo-subcortical pathways in BD. Significant differences were not seen in DTI metrics following FDR-correction. The DKI findings indicate altered connectivity across cortical, subcortical and cerebellar areas in BD. DKI is sensitive to different microstructural properties and is a useful complementary technique to DTI to more fully investigate white matter in BD.

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.

Biophysical mechanisms of electroconvulsive therapy-induced volume expansion in the medial temporal lobe: A longitudinal in vivo human imaging study.

BACKGROUND: Electroconvulsive therapy (ECT) applies electric currents to the brain to induce seizures for therapeutic purposes. ECT increases gray matter (GM) volume, predominantly in the medial temporal lobe (MTL). The contribution of induced seizures to this volume change remains unclear. METHODS: T1-weighted structural MRI was acquired from thirty patients with late-life depression (mean age 72.5 ± 7.9 years, 19 female), before and one week after one course of right unilateral ECT. Whole brain voxel-/deformation-/surface-based morphometry analyses were conducted to identify tissue-specific (GM, white matter: WM), and cerebrospinal fluid (CSF) and cerebral morphometry changes following ECT. Whole-brain voxel-wise electric field (EF) strength was estimated to investigate the association of EF distribution and regional brain volume change. The association between percentage volume change in the right MTL and ECT-related parameters (seizure duration, EF, and number of ECT sessions) was investigated using multiple regression. RESULTS: ECT induced widespread GM volume expansion with corresponding contraction in adjacent CSF compartments, and limited WM change. The regional EF was strongly correlated with the distance from the electrodes, but not with regional volume change. The largest volume expansion was identified in the right MTL, and this was correlated with the total seizure duration. CONCLUSIONS: Right unilateral ECT induces widespread, bilateral regional volume expansion and contraction, with the largest change in the right MTL. This dynamic volume change cannot be explained by the effect of electrical stimulation alone and is related to the cumulative effect of ECT-induced seizures.