Electroconvulsive therapy induces rapid microstructural and macrostructural changes, but microstructural changes are longer-lasting

Electroconvulsive therapy induces rapid microstructural and macrostructural changes, but microstructural changes are longer-lasting | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Electroconvulsive therapy induces rapid microstructural and macrostructural changes, but microstructural changes are longer-lasting Joey Verdijk, Julia Pottkämper, Freek Doesschate, Laurens van de Mortel, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6295387/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Background Electroconvulsive therapy (ECT) is an effective treatment for major depressive episodes, though its mechanisms remain unclear. Its use is limited due to stigma and possible cognitive side-effects. Repeated magnetic resonance imaging (MRI) could provide further insights into the brain changes associated with ECT’s efficacy and cognitive outcomes. Methods We analyzed prospective longitudinal repeated MRI, cognitive, and efficacy data of depressed ECT-patients. Structural and diffusion tensor imaging (DTI) MRI scans were conducted at baseline, directly after initial ECT-sessions, within two weeks after the course and at three months follow-up. Test-retest effects were controlled by including 26 matched healthy controls ( n =26). Linear and nonlinear changes in grey matter (GM) volume, white matter (WM) volume, mean diffusivity (MD) and fractional anisotropy (FA) were assessed. Early brain changes were associated with cognitive and efficacy outcomes. Results After the 3 rd ECT-session ( n =19), subcortical GM volumes increased, accompanied by right lateralized decrease of MD in those areas. Two weeks post-ECT ( n =30), cortical GM volume increased which returned to baseline after three months. In WM, MD linearly increased post-ECT, without widespread FA changes, and MD did not return to baseline after three months ( n =30). ECT decreased verbal learning transiently, letter fluency, and animal category fluency tests ( n =23, p bonferroni = 0.04; n= 22, p bonferroni = 0.04; n= 62, p bonferroni = 0.02). Early brain changes were not associated with cognitive performance or efficacy. Conclusions These results suggest that ECT induces rapid changes in brain microstructure and macrostructure. But while macroscopic increases are temporary, microscopic changes in brain structure are longer-lasting. Biological sciences/Neuroscience Biological sciences/Molecular biology Electroconvulsive therapy diffusion tensor imaging cognitive side-effects major depression neuroplasticity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Major depressive disorder (MDD) is a common mental disorder, with a lifetime prevalence of up to 20% ( 1 ). Psycho- and pharmacotherapy benefit around 50% of patients, but many of them relapse and an estimated 30% of patients suffers from treatment-resistant depression (TRD) ( 2 , 3 ). A frequently used and generally effective treatment modality for TRD cases is electroconvulsive therapy (ECT) ( 4 ). Yet, its use is limited by practicalities, variation in response rate, stigma, concerns over possible (cognitive) side-effects and a lack of mechanistic insight. As a result, less than 1% of depressed patients receives ECT ( 5 , 6 , 7 , 8 ). Currently, the most common theories on the possible mechanisms of action of ECT describe an induction of immediate early genes, brain-derived neurotrophic factor, and neuroplastic effects (synaptogenesis, dendritic arborization, glial activation, angiogenesis and neurogenesis) ( 9 , 10 , 11 ). These theories are mainly derived from animal models. Clarity about the mechanisms of action and safety may help reduce fear and promote a more effective utilization. Macrostructural brain changes have been studied most extensively in ECT-patients. Using T1-weighted magnetic resonance imaging (T1W MRI), increased volumes of hippocampus and amygdala have been reported within 24 hours after a first ECT-session ( 12 , 13 ). After a completed ECT-course generalized increases of grey matter (GM) volume are found ( 9 ). These seem transient, as GM volume decreases again in three to six months after the ECT-course ( 14 , 15 ). How these macrostructural changes relate to the possible mechanisms of action of ECT is unclear, since neuroplastic effects are not expected to (fully) explain generalized increases of GM volume ( 9 ). Microstructural brain changes have so far been more sparsely studied in ECT-patients. Diffusion tensor imaging (DTI) holds potential to further elucidate the nature of microstructural changes in both GM and white matter (WM). The few studies that applied DTI report opposing findings regarding WM changes of fractional anisotropy (FA) and mean diffusivity (MD) following completion of an entire ECT-course ( 16 , 17 , 18 ). Current DTI evidence further indicates that MD decreases in hippocampal GM after the ECT-course, which has been hypothesized to be governed by neuroplastic changes ( 19 , 20 ). Until now, however, studies of diffusivity dynamics immediately following separate ECT sessions are lacking, which may provide additional insight into the nature of these microstructural changes. In daily ECT-practice, patients often show rapid improvements in mood but also develop cognitive side-effects, that can last for weeks or longer ( 21 ). These rapid clinical changes probably relate to changes in cerebral volume and diffusion measures. Repeated MRI studies, with scans between 48 hours after the tenth ECT session and one to two weeks after the ECT-course, give indications for a negative impact of volume increase of the hippocampus on cognitive outcome, and in one study, a negative impact of decrease of MD in this region ( 22 , 23 , 24 ). Additionally, volume increase of the hippocampus and amygdala has been associated with reduction of depressive symptoms tested over scans between 24 hours after the second ECT-session, though combined with scans after the ECT-course ( 12 ). Whether the same changes contribute to both cognitive side-effects and efficacy is unclear. Cerebral volume and diffusion changes assessed in multiple regions directly after initial ECT-sessions may be more specific to the reported associations of efficacy or cognitive side-effects. In this prospective longitudinal study, we therefore investigated early and later temporal changes in cerebral volume and diffusivity of MDD patients, both at several timepoints throughout the ECT-course and at three months follow-up. Data were corrected for normal test-retest variability based on a group of healthy controls (HC). We subsequently associated the early cerebral changes with cognitive and efficacy measures. Methods and materials Study design Data were included from the participants from two prospective studies in depressed patients treated with ECT between 2017 and 2023 ( 25 , 26 , 27 ). MRI scans of both studies were acquired on the same scanner with identical sequences. To correct for test-retest effects, healthy control (HC) data were included from age-, sex-, and education level ( 28 )-matched participants who were assessed prospectively as part of one of the studies with cognitive tests and MRI (Supplementary Materials). All patients and HC provided oral and written informed consent before entering the studies. Participants and timepoints of measurements ECT-patients were > 17 years-of-age, both hospitalized and non-hospitalized, treatment-resistant, currently depressed classified (according to the Dutch version of the Mini International Neuropsychiatric Interview (MINI) ( 29 ) as unipolar depressive disorder, bipolar disorder or schizoaffective disorder). MRI and clinical data of ECT-patients were gathered before starting of the course at baseline; (T0), postictal ~ 1 h each time after three separate ECT-sessions (for details, see below) (T1; separate as T1.1, T1.2 and T1.3), within two weeks after completing the ECT-course (T2) and at three months follow-up (T3) (Fig. 1 ). The HCs were > 17 years-of-age, all scored negative on all items of the MINI, and were assessed at baseline (T0), after one month (T2) and after three months (T3). 72 ECT-patients could be included. 32 of these patients were excluded due to missing MRI data. Of these,10 did not pass quality control of MRI. A further 11 patients were excluded only for the analysis of MRI during the ECT-course because of missing data (Supplementary Fig. 1). ECT-procedure ECT-sessions were administered according to Dutch guidelines, two times a week ( 30 ), using bifrontotemporal (BL) or unilateral (UL) electrode placement (Supplementary Methods). Image acquirement and preprocessing At identical timepoints as the cognitive tests, T1W and DTI MRI scans were acquired in ECT-patients as well as in HCs (T0, T2 and T3). Additionally, only in the ECT-patients, at a first timepoint during the ECT-course (T1.1; median after 3rd ECT-session [IQR 1.25]), at a second timepoint (T1.2; median after 5th ECT-session [IQR 0.75]) and at a third timepoint (T1.3; median after the 7th ECT-session [IQR 1]), MRI scans were acquired approximately one hour after the ECT-session. Acquisition parameters and preprocessing are described in the Supplementary Methods. DTI analyses We fitted a diffusion tensor model at each voxel (Supplementary Methods). For voxel-wise analysis of WM, we used the Tract-Based Spatial Statistics pipeline (TBSS; ( 31 )), part of FSL ( 32 ). To investigate MD changes in expected areas of GM volume increase ( 12 ), we chose ROIs of the hippocampus and amygdala, limited to initial volume change at T1.1. Additionally, we chose the insular cortex because of its relevance for depression ( 33 ) and possible volume increases beneath the ECT-electrodes. Clinical outcomes In MDD patients, depression severity was assessed at T0, T2 and T3 with the Hamilton Depression Rating Scale (HDRS) ( 34 ), while extensive cognitive measurements were performed as well. Global cognitive functioning was assessed using the Montreal Cognitive Assessment (MOCA) ( 35 ) or Mini-Mental State Examination (MMSE) ( 36 ). MMSE scores were converted to MOCA using a validated method ( 37 ). More specific cognitive domains were examined with the Rey Auditory Verbal Learning Test (RAVLT; immediate and delayed recall) ( 38 ), the Category Fluency of animals and occupations (CFa and CFo; executive retrograde memory) ( 39 ), the Letter Fluency (LF; executive retrograde memory) ( 39 ), the backwards digit span testing (DSB; working memory) ( 40 ), the STROOP task (processing speed) ( 41 ), the Trail Making Test A and B (TMT A/B; attention and cognitive flexibility, respectively) ( 42 ), and the Subjective Assessment of Memory Impairment (SAMI) ( 43 ). RAVLT, DSB, STROOP, TMT A/B, and SAMI were only available in one of the two included studies. We first explored changes in cognitive functions over time in the ECT-patients corrected for test-retest variability over time based on the HCs. Thereafter, we selected the tests that significantly changed in patients and used these outcomes to examine associations with (early and later) cerebral volume and diffusion changes. Statistical analyses To investigate changes during the ECT-course, we used three planned Helmert contrasts between baseline (T0) and the three available postictal timepoints (i.e., T1.1, T1.2 and T1.3), as well as between the postictal timepoints themselves. To test changes after the ECT-course over T0, T2 and T3, we used polynomial contrasts to test whether there were linear or quadratic changes, corrected for changes in HC. Voxel-wise family wise error (FWE) correction was performed using Threshold-Free Cluster Enhancement (TFCE) at a significance level of 0.05. For all analyses, we applied Bonferroni correction for multiple comparisons (i.e., for the cognitive test battery, FWE correction for 11 models). Additionally, effect sizes for the interaction terms were calculated using Pearson’s r . Further details are described in the Supplementary Materials. Results Included sample and clinical characteristics In total, 72 patients were included in the datasets. We included 30 patients for the analysis of brain changes at T0, T2 and T3, and 19 patients for T0 and T1 (Supplementary Fig. 1). Table 1 summarizes the characteristics of the included patients and HC. Due to missing data, the number of ECT-patients varied for the individual cognitive tests (see further). At group level, ECT-patients did not differ from HC regarding age, sex and education level ( p values > .05). Over time from T0 to T2 and T3, the mean HDRS-scores showed a significant quadratic decrease ([ n = 70], β = -1.8, r = 0.43, p < 0.001; Supplementary Fig. 1). Structural volume changes During the ECT-course. The GM of multiple subcortical structures (i.e., hippocampus, amygdala and insular cortices in both hemispheres) increased significantly over the three timepoints during the ECT-course (i.e., average T1.1-T1.3, compared to T0 and corrected for changes over time in HCs; see Fig. 2 , Supplementary Video 1). Notably, no significant changes in the cortex were detected. In the WM segmentation, we found significant decreases in volume adjacent to some of the GM increases. The right thalamus, erroneously automatically segmented into WM, significantly increased in volume (Fig. 2 ). Comparisons between the consecutive timepoints during the ECT-course further showed non-significant ( p > .05) GM increases between T.1.1 and T.1.3. After the ECT-course. Across T0, T2 and T3, we found widespread GM increases of cortical and subcortical structures (Fig. 2 , Supplementary Video 2), controlled for HC. These increases were quadratic, and transient (i.e., T3 returning to T0, confirmed with post-hoc t-tests of T0 versus T3, Supplementary Fig. 2) Additionally, some areas in the WM segmentation transiently increased and smaller areas of adjacent WM transiently decreased (Fig. 2 ). Brain diffusion changes During the ECT-course. Compared to baseline (T0), we detected lateralized decreases of MD in the right amygdala ( β = -0.08, r = 0.50, p bonferroni < 0.001) and right hippocampus ( β = -0.07, r = 0.48, p bonferroni < 0.001) during the ECT-course (i.e., at timepoints T1.1, T1.2 and T1.3), while the contralateral and insular structures did not change (see Supplementary Results). In the WM, MD did not significantly change postictally (at minimum a cluster with p- value of 0.051), nor did it change further in the course in the comparisons between postictal measurements. FA though, generalized throughout the WM, was significantly lower postictally (Fig. 3 , Supplementary Video 3) ( 44 ). From postictal measurement 1 to 2, FA further decreased in some clusters. From postictal measurement 2 to 3, FA did not further decrease, and instead increased in an occipitoparietal cluster. After the ECT-course. Controlled for changes in HC over time, MD in the left amygdala ( β = -0.14, r = 0.37, p bonferroni = 0.001), the right amygdala ( β = -0.12, r = 0.29, p bonferroni = 0.02), and the right hippocampus ( β = -0.12, r = 0.32, p bonferroni = 0.008) showed transient (quadratic) decreases from baseline (T0) across T2 to T3 (Fig. 4 , confirmed with post-hoc t-tests T0 with T3 p > 0.05, Supplementary Video 4). Changes in left hippocampus and both insular cortices did not reach statistical significance. In contrast, in the WM, we found persisting, widespread linear increases in MD, while FA was mostly unchanged except for one small cluster showing a linear decrease in FA in the left parietal WM tracts (Fig. 3 , Supplementary Fig. 2). To further investigate the nature of the diffusion changes in WM, we post-hoc applied NODDI-DTI on our single-shell DTI maps ( 45 ) to calculate neurite density indices (NDI) and orientation dispersion indices (ODI) from the normalized, non-skeletonized DTI maps. We used the FA distance maps from the TBSS pipeline to project NODDI maps onto the skeleton and found that the MD increases in WM over T0, T1 and T2 were accompanied by linear decreases in NDI, while ODI remained unchanged. Neuropsychological outcomes At baseline, ECT-patients scored significantly lower than HC regarding the MOCA (ECT [ n = 70] = 23.3 ± 5.1; HC = 26.6 ± 2.0, p < 0.01), CFa (ECT [ n = 62] = 42.4 ± 12.0; HC = 49.2 ± 11.4, p = 0.02), CFo (ECT [ n = 62] = 43.5 ± 11.1; HC = 54.1 ± 12.1, p < 0.01), STROOP (ECT [ n = 20] = 46.0 ± 11.7; HC = 53.2 ± 9.8, p = 0.03), DSB (ECT [ n = 20] = 42.3 ± 10.3; HC = 51.9 ± 9.9, p < 0.01) and TMT (ECT [ n = 19] = 42.3 ± 13.3; HC = 50.2 ± 9.5, p = 0.03) (see Fig. 4 and Supplementary Fig. 3). LF ( n ECT = 22) and RAVLT ( n ECT = 23, both total and imprinting) did not differ at baseline. Over T0, T1 and T2, corrected for test-retest effects in HCs, we detected transient (quadratic) decreases of the LF test ( β = -2.0, r = 0.30, p bonferroni = 0.04), the imprinting sub-score of RAVLT ( β = -2.8, r = 0.30, p bonferroni = 0.04) and the CFa test ( β = -2.5, r = 0.25, p bonferroni = 0.02). Figure 5 shows these results for ECT-patients and HCs. These cognitive tests had all recovered at the three months follow-up (T3; see Supplementary Results). Scores on the MOCA, SAMI, RAVLT (i.e., recall score corrected for total imprinted words), TMT, STROOP, DSB, and CFo did not change significantly (see Supplementary Fig. 3 and Supplementary Results) at either of the two timepoints after the ECT-course (i.e., T2 and T3, compared to T0 and corrected for test-retest effects in HC). Cerebral volume and diffusion changes in relation to cognitive and efficacy outcomes We included the LF, RAVLT (imprinting) and CFa as cognitive outcome variables to associate with our MRI outcomes, as these were the only ones to significantly change. No significant associations were found between any change in cerebral volume or diffusivity with any of the established deteriorations on these tests (i.e., when testing for associations of change (T0 – T2) of scores in LF, the imprinting sub-score of RAVLT and the CFa test, with both GM and WM volume change (T0 – T1.1), MD change within GM ROIs (T0 – T1.1), and voxel-wise diffusion changes in the WM skeleton (T0 – T1.1).) Although a lower decrease in the imprinting score of RAVLT seemed to be associated with a larger GM volume increase during the ECT-course (i.e., T0 – T1.1) in multiple clusters, this association just failed to reach significance after accounting for testing multiple brain-behavior associations (minimum p uncorrected = 0.0125, p corrected for multiple cognitive tests = 0.05; Supplementary Fig. 4). Also, change in HDRS-scores at T2 compared to baseline T0 was not associated with any of the cerebral volume or DTI parameters. Discussion In this prospective longitudinal study in ECT-patients, our novel findings reveal early microstructural changes during ECT. In GM, we found an acutely decreased diffusivity which is transient within 3 months. In contrast, in WM, we found an increased diffusivity which is longer lasting. Furthermore, we confirm earlier reported macrostructural changes of GM volume increase which is transient within 3 months. Though during the ECT-course, the GM volume increase seems more localized to subcortical structures, which after the ECT-course is generalized over the cortex. The observed micro- and macrostructural changes in patients were notably not significantly associated with the observed transient decline in cognitive functioning, nor with clinical efficacy after ECT. Interpretations of microstructural and macrostructural changes in GM Consistent with earlier findings, we found volume increases of the subcortical GM structures in ECT-treated depressed patients accompanied by decreases in MD ( 19 , 20 ). Of these structures, in particular the hippocampus and amygdala are associated with depression ( 46 ). Furthermore, we confirm earlier data showing that these volume increases are already present from the 1st to 3rd ECT-session ( 12 , 13 ). Our novel finding is that the decreases in MD already occur after the third ECT-session. Multiple interpretations are possible of the early present decreased MD and volume in GM. Cellular stress in the form of cytotoxic edema may explain our findings of acutely and relatively short-lived decreased MD, and volume increase, in GM ( 47 , 48 ). If present, we hypothesize this neuronal stress to be transient, and much less prominent than the neuropathological and/or cellular changes found after status epilepticus or chronic epilepsy in both rodent models and human postmortem brain, supported by a lack of volume loss, and lack of clinical deleterious effects. Indeed, in contrast, malformations, granule cell dispersion, mossy fiber sprouting, cornu Ammonis (CA) cell loss, blood brain barrier leakage and astrogliosis have been reported in hippocampal and extrahippocampal limbic regions of epileptic patients ( 49 , 50 ). Volume and diffusivity changes after ECT could in principle thus also relate to inflammatory changes and the activation of (astro)glia ( 51 ). Yet, the electroconvulsive shock (ECS) treatment paradigm in rodents differs from those paradigms that induce epileptic seizures, which is generally more short term. ECS initiated an immediate glial reaction, though this was already decreased four weeks later, which may fit our MD findings in GM ( 52 ). Additionally, no indications could be found for massive cell loss or glial activation in a recent study on hippocampal tissue from (chronic) ECT-treated, depressed patients ( 53 ). Hypothetically, transient neuronal stress may thus cause the transient cognitive side-effects, and consequently induce expression of early-immediate genes and neuroplasticity, leading to reduction of depressive symptoms in ECT (‘disrupt and rewire’) ( 9 , 54 ). Alternatively, primarily ensuing neuroplasticity changes have been proposed to be associated with the decreased MD in GM, a.o. in the hippocampal dentate gyrus ( 20 , 53 ). A recent study in rats supports neuroplastic effects, though other brain regions can also be involved ( 51 , 52 , 55 , 56 , 57 ). Studies inducing ECS in rodent models reported widespread neuroplasticity changes, e.g. in hippocampal neurogenesis, cortical proliferation and synaptic changes ( 58 , 59 ), while dendritic arborization and glial activation have been observed after three ECS sessions ( 57 ). The cellular changes in animal models compare to our findings of an early decrease of MD coinciding with volume increase. ECT may thus rapidly and transiently cause neuroplastic effects, that appear to be initially concentrated in depression-related subcortical structures. Microstructural changes in WM are longer lasting In contrast to our findings in GM, diffusivity in WM increases and is present longer than 3 months. Because of the differences in diffusivity and longevity of our findings, we hypothesize that we captured multiple processes in the brain throughout the ECT-course and beyond. In WM, we interpret our findings as increased extracellular free diffusion, without significant changes to microstructural organization, because of the absence of significant changes of FA after the ECT-course. Also, though preliminary, this seems supported by our findings of a coinciding decrease of neurite density (NDI), without a change in the orientation variation of neurites (ODI). In a different publication ( 44 ) on the same study sample, we find decreased FA shortly after the ECT session, which thus seems very short lived. Whether the longer present increase of diffusivity in WM contributes to the efficacy of ECT has to be further examined in future research. Lateralized decreases of MD in GM throughout ECT, but not beyond We further detected right-sided decreases of MD in GM in the hippocampus and amygdala during the ECT-course, a lateralization that was no more present within two weeks after the ECT-course. Though this may be caused by differences in sample size over timepoints, which compromised our power to detect changes, we hypothesize that the initial lateralization could be due to the right unilateral electrode placement in a quarter of our included patients. Initially, a direct influence of the e-fields on the right side of the brain may cause microstructural changes ( 60 ), while after the ECT-course, we speculate this may lead to a cascade of neurotrophic effects, which spreads throughout the brain, again dissipating the lateralization. No associations with cognitive outcome and efficacy In our depressed patients, mood improvement and clinically relevant cognitive side-effects were seen, which were statistically significant at group level. We replicated that the cognitive side-effects are transient after 3 months ( 61 ). We did not detect associations between the transient disturbances in verbal recall and retrograde executive memory functions, and any of the observed MRI changes, nor between antidepressive efficacy and MRI measures. We hypothesize that this results from a lack of power, since voxel-wise regression analyses with a more stringent correction of multiple comparisons, require far larger sample sizes, especially of linear outcome data ( 62 ). We did detect borderline significant associations between the imprinting score of RAVLT and anatomical clusters adhering to the functional default mode and salience networks (Supplementary Fig. 4), suggesting that larger volume increases in these regions mitigate the ECT-related cognitive decline. Detected cognitive side-effects of ECT are transient The current study showed that depressed patients had lower cognitive functioning before ECT compared to healthy controls, probably as part of the disorder. Despite the stigma surrounding cognitive side-effects of ECT, we not only show that the cognitive decreases are transient after three months, we also showed that some cognitive performances improved after ECT. Moreover, we did not detect subjective cognitive side-effects after the ECT-course. Therefore, more research-substantiated information regarding (baseline) cognitive functioning and the to be expected cognitive side-effects should be given to patients, caregivers and involved professionals. This may help decrease ECT stigma. Strengths and limitations Our design has multiple strengths. First, we collected longitudinal data in ECT-patients and matched HC over three months, at several timepoints, as well as during the ECT-course in the patients. We combined multiple modalities of structural MRI data, and scanned all patients and HC in the same environment and MRI scanner. Second, we were able to additionally collect an extensive battery of cognitive functions in ECT-patients as well as in the HCs. However, our design also has limitations. First, our final sample size was relatively small. MRI data was not available for all ECT-patients during the ECT-course (i.e., at T1), which also caused heterogeneity in the number of patients per timepoint. Also, the number of patients per cognitive outcome measure was heterogeneous due to missing data, as well as differing outcome measures between the two included studies. Second, because of our relatively hypothesis-free approach, we included a multitude of outcome measures, for which we had to perform stringent FWE correction, ultimately limiting our power to detect associations. Third, apart from MD of amygdala, hippocampus and insula, we employed whole-brain voxel-wise regression to test for associations with cognitive outcome, which is less sensitive than limiting analysis to specific structures. Fourth, we post-hoc aimed to further specify the MD changes in WM using NODDI in our single-shell data, though no consensus exists whether this is feasible without multi-shell acquisitions ( 45 ). Also, while one possible hypothesized mechanism in ECT is inflammatory changes, the NODDI parameters produce mixed results in pathologically confirmed neuronal tissue where glia cells are activated ( 63 ). We therefore advise future studies to use models such as the recently developed soma and neurite density imaging (SANDI) ( 64 ), which we were unable to apply, since our data lacked the required multi-shell acquisition up to b = 6000s/mm 2 ( 65 ). In conclusion, ECT in the current cohort improved depressive symptoms until 3 months after cessation, and induced some cognitive side-effects which were transient. Further throughout and beyond the ECT-course, early - but transient – significant brain volume increases were found in subcortical gray matter structures, which were accompanied by – also transient - decreases in (local) mean diffusivity. In contrast, diffusivity increases in white matter tracts seemed to persist for at least three months after ECT. Significant verbal memory disturbances did not associate with early structural or diffusion brain changes. Our findings show that while macrostructural changes are transient, microstructural changes are divergent and longer lasting. Declarations of interest Guido van Wingen has received research funding from Biogen, Bitbrain and Philips for unrelated work. The other authors report no conflicts of interest. Declarations Declarations of interest Guido van Wingen has received research funding from Biogen, Bitbrain and Philips for unrelated work. The other authors report no conflicts of interest. Acknowledgements This complex study was not possible without all patients and participants in the healthy control group, as well as the collaborators from the departments of psychiatry (especially Oscar Buno Heslinga, ECT-nurse, and Nancy Sanders, secretary), anesthesiology and radiology (especially Marit Bles) of Rijnstate hospital Arnhem, The Netherlands. Specially mentioned should be our group of research volunteers without whom this study was not possible: Marleen Middelman, Simon de Both, Tonia Schouten, Tijn Stolk, Anna Schoonhoven, Nienke Gerards, Nicole de Kruijf, Amber Selie, Arnoud van der Meulen, Tessa Klein, Marlous Verhulst, Gijsbert Schuur, Stanley Pham, Rajco Meuleman, David van Ghroningen, Madelon Thevis, Sanédy Simon, Chantal Staring, Max Roelofs, Robyn van Vehmendahl, Stijn Donker, and Tim van Helden. PJL is supported by the Center for Urban Mental Health of the University of Amsterdam, by ZON-MW MODEM and by the ‘Institute for Chemical Neuroscience’, a gravitation grant of the Dutch Research Council NWO and the Dutch Ministery of OCW (grant nr 024.006.009). The SYNAPSE trial, which supplied a large portion of the total population, was funded by EpilepsieNL (grant number WAR 19-02). References Hasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, et al. Epidemiology of Adult DSM-5 Major Depressive Disorder and Its Specifiers in the United States. JAMA Psychiatry. 2018;75(4):336–46. Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905–17. Lundberg J, Cars T, Lööv S, Söderling J, Sundström J, Tiihonen J, et al. Association of Treatment-Resistant Depression With Patient Outcomes and Health Care Resource Utilization in a Population-Wide Study. JAMA Psychiatry. 2023;80(2):167–75. Nygren A, Reutfors J, Brandt L, Bodén R, Nordenskjöld A, Tiger M. Response to electroconvulsive therapy in treatment-resistant depression: nationwide observational follow-up study. BJPsych Open. 2023;9(2):e35. Scheepens DS, van Waarde JA, Lok A, Zantvoord JB, de Pont B, Ruhé HG, et al. [Electroconvulsion therapy for persistent depression in the Netherlands; very low application rate]. Tijdschr Psychiatr. 2019;61(1):16–21. Wilkinson ST, Agbese E, Leslie DL, Rosenheck RA. Identifying Recipients of Electroconvulsive Therapy: Data From Privately Insured Americans. Psychiatr Serv. 2018;69(5):542–8. Kellner CH, Obbels J, Sienaert P. When to consider electroconvulsive therapy (ECT). Acta Psychiatr Scand. 2020;141(4):304–15. Hebbrecht K, Dejaeger M, Giltay EJ, Birkenhäger T, Sabbe B, Verwijk E, et al. Cognitive trajectories during and after electroconvulsive therapy in patients with MDE: Taking different perspectives. J Psychiatr Res. 2022;156:132–40. Ousdal OT, Brancati GE, Kessler U, Erchinger V, Dale AM, Abbott C, et al. The Neurobiological Effects of Electroconvulsive Therapy Studied Through Magnetic Resonance: What Have We Learned, and Where Do We Go? Biol Psychiatry. 2022;91(6):540–9. Chang AD, Vaidya PV, Retzbach EP, Chung SJ, Kim U, Baselice K, et al. Narp Mediates Antidepressant-Like Effects of Electroconvulsive Seizures. Neuropsychopharmacology. 2018;43(5):1088–98. Singh A, Kar SK. How Electroconvulsive Therapy Works?: Understanding the Neurobiological Mechanisms. Clin Psychopharmacol Neurosci. 2017;15(3):210–21. Joshi SH, Espinoza RT, Pirnia T, Shi J, Wang Y, Ayers B, et al. Structural Plasticity of the Hippocampus and Amygdala Induced by Electroconvulsive Therapy in Major Depression. Biol Psychiatry. 2016;79(4):282–92. Brancati GE, Brekke N, Bartsch H, Evjenth Sørhaug OJ, Ousdal OT, Hammar Å, et al. Short and long-term effects of single and multiple sessions of electroconvulsive therapy on brain gray matter volumes. Brain Stimul. 2021;14(5):1330–9. Gbyl K, Rostrup E, Raghava JM, Carlsen JF, Schmidt LS, Lindberg U, et al. Cortical thickness following electroconvulsive therapy in patients with depression: a longitudinal MRI study. Acta Psychiatr Scand. 2019;140(3):205–16. Jehna M, Wurm W, Pinter D, Vogel K, Holl A, Hofmann P, et al. Do increases in deep grey matter volumes after electroconvulsive therapy persist in patients with major depression? A longitudinal MRI-study. Journal of Affective Disorders. 2021;281:908–17. Lyden H, Espinoza RT, Pirnia T, Clark K, Joshi SH, Leaver AM, et al. Electroconvulsive therapy mediates neuroplasticity of white matter microstructure in major depression. Transl Psychiatry. 2014;4(4):e380. Repple J, Meinert S, Bollettini I, Grotegerd D, Redlich R, Zaremba D, et al. Influence of electroconvulsive therapy on white matter structure in a diffusion tensor imaging study. Psychological Medicine. 2020;50(5):849–56. Nickl-Jockschat T, Palomero Gallagher N, Kumar V, Hoffstaedter F, Brügmann E, Habel U, et al. Are morphological changes necessary to mediate the therapeutic effects of electroconvulsive therapy? Eur Arch Psychiatry Clin Neurosci. 2016;266(3):261–7. Gyger L, Ramponi C, Mall JF, Swierkosz-Lenart K, Stoyanov D, Lutti A, et al. Temporal trajectory of brain tissue property changes induced by electroconvulsive therapy. Neuroimage. 2021;232:117895. Nuninga JO, Mandl RCW, Froeling M, Siero JCW, Somers M, Boks MP, et al. Vasogenic edema versus neuroplasticity as neural correlates of hippocampal volume increase following electroconvulsive therapy. Brain Stimulation. 2020;13(4):1080–6. Verwijk E, Comijs HC, Kok RM, Spaans HP, Tielkes CE, Scherder EJ, et al. Short- and long-term neurocognitive functioning after electroconvulsive therapy in depressed elderly: a prospective naturalistic study. Int Psychogeriatr. 2014;26(2):315–24. Gbyl K, Støttrup MM, Mitta Raghava J, Xue Jie S, Videbech P. Hippocampal volume and memory impairment after electroconvulsive therapy in patients with depression. Acta Psychiatr Scand. 2021;143(3):238–52. Jorgensen A, Magnusson P, Hanson LG, Kirkegaard T, Benveniste H, Lee H, et al. Regional brain volumes, diffusivity, and metabolite changes after electroconvulsive therapy for severe depression. Acta Psychiatr Scand. 2016;133(2):154–64. Van der AJ, De Jager JE, van Dellen E, Mandl RCW, Somers M, Boks MPM, et al. Changes in perfusion, and structure of hippocampal subfields related to cognitive impairment after ECT: A pilot study using ultra high field MRI. J Affect Disord. 2023;325:321–8. Pottkämper JCM, Verdijk J, Stuiver S, Aalbregt E, Ten Doesschate F, Verwijk E, et al. Exploring postictal recovery with acetaminophen or nimodipine: A randomized-controlled crossover trial. Ann Clin Transl Neurol. 2024. Verdijk J, Pottkämper JCM, Verwijk E, van Wingen GA, van Putten M, Hofmeijer J, et al. Study of effect of nimodipine and acetaminophen on postictal symptoms in depressed patients after electroconvulsive therapy (SYNAPSE). Trials. 2022;23(1):324. Scheepens DS, van Waarde JA, Ten Doesschate F, Westra M, Kroes MCW, Schene AH, et al. Negative cognitive schema modification as mediator of symptom improvement after electroconvulsive therapy in major depressive disorder. J Affect Disord. 2022;310:156–61. Verhage F. Intelligentie en leeftijd bij volwassenen en bejaarden: Koninklijke Van Gorcum; 1964. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22–33;quiz 4–57. Psychiatrie NVv. Richtlijn Electroconvulsietherapie (ECT): Federatie Medisch Specialisten; 2021 [ Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31(4):1487–505. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23 Suppl 1:S208-19. Schnellbächer GJ, Rajkumar R, Veselinović T, Ramkiran S, Hagen J, Shah NJ, et al. Structural alterations of the insula in depression patients - A 7-Tesla-MRI study. Neuroimage Clin. 2022;36:103249. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62. Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98. Fasnacht JS, Wueest AS, Berres M, Thomann AE, Krumm S, Gutbrod K, et al. Conversion between the Montreal Cognitive Assessment and the Mini-Mental Status Examination. J Am Geriatr Soc. 2023;71(3):869–79. Rey A. L'examen clinique en psychologie. 1958. Luteijn F, Van der Ploeg FAE. Groninger Intelligentie Test (GIT). Lisse, Netherlands: Swets & Zeitlinger; 1983. Ramsay MC, Reynolds CR. Separate digits tests: a brief history, a literature review, and a reexamination of the factor structure of the Test of Memory and Learning (TOMAL). Neuropsychol Rev. 1995;5(3):151–71. Strauss E, Sherman EMS, Spreen O. Compendium of Neuropsychological Test: Administration, Norms, and Commentary. New York, NY: Oxford University Press; 2006. Reitan RM. Trail-Making Test. Arizona: Reitan Neuropsychology Laboratory; 1979. Kumar DR, Han HK, Tiller J, Loo CK, Martin DM. A Brief Measure for Assessing Patient Perceptions of Cognitive Side Effects After Electroconvulsive Therapy: The Subjective Assessment of Memory Impairment. J ect. 2016;32(4):256–61. Verdijk JPAJ, Schouten TAL, Pottkämper JCM, van de Mortel LA, ten Doesschate F, Stuiver S, et al. Postictal agitation is associated with brain-wide postictal microstructural changes after electroconvulsive therapy-induced seizures. Under review. Edwards LJ, Pine KJ, Ellerbrock I, Weiskopf N, Mohammadi S. NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter. Front Neurosci. 2017;11:720. Jacob Y, Morris LS, Verma G, Rutter SB, Balchandani P, Murrough JW. Altered hippocampus and amygdala subregion connectome hierarchy in major depressive disorder. Translational Psychiatry. 2022;12(1):209. Ito J, Marmarou A, Barzó P, Fatouros P, Corwin F. Characterization of edema by diffusion-weighted imaging in experimental traumatic brain injury. J Neurosurg. 1996;84(1):97–103. Briellmann RS, Wellard RM, Jackson GD. Seizure-associated abnormalities in epilepsy: evidence from MR imaging. Epilepsia. 2005;46(5):760–6. Gorter JA, van Vliet EA, Aronica E, Lopes da Silva FH. Progression of spontaneous seizures after status epilepticus is associated with mossy fibre sprouting and extensive bilateral loss of hilar parvalbumin and somatostatin-immunoreactive neurons. Eur J Neurosci. 2001;13(4):657–69. van Vliet EA, Aronica E, Gorter JA. Blood-brain barrier dysfunction, seizures and epilepsy. Semin Cell Dev Biol. 2015;38:26–34. Cano M, Camprodon JA. Understanding the Mechanisms of Action of Electroconvulsive Therapy: Revisiting Neuroinflammatory and Neuroplasticity Hypotheses. JAMA Psychiatry. 2023;80(6):643–4. Jansson L, Wennström M, Johanson A, Tingström A. Glial cell activation in response to electroconvulsive seizures. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2009;33(7):1119–28. Loef D, Tendolkar I, van Eijndhoven PFP, Hoozemans JJM, Oudega ML, Rozemuller AJM, et al. Electroconvulsive therapy is associated with increased immunoreactivity of neuroplasticity markers in the hippocampus of depressed patients. Transl Psychiatry. 2023;13(1):355. Ashayeri Ahmadabad R, Khaleghi Ghadiri M, Gorji A. The role of Toll-like receptor signaling pathways in cerebrovascular disorders: the impact of spreading depolarization. Journal of Neuroinflammation. 2020;17(1):108. De Jager JE, Boesjes R, Roelandt GHJ, Koliaki I, Sommer IEC, Schoevers RA, et al. Shared effects of electroconvulsive shocks and ketamine on neuroplasticity: A systematic review of animal models of depression. Neurosci Biobehav Rev. 2024;164:105796. Nuninga JO, Mandl RCW, Boks MP, Bakker S, Somers M, Heringa SM, et al. Volume increase in the dentate gyrus after electroconvulsive therapy in depressed patients as measured with 7T. Mol Psychiatry. 2020;25(7):1559–68. Abe Y, Yokoyama K, Kato T, Yagishita S, Tanaka KF, Takamiya A. Neurogenesis-independent mechanisms of MRI-detectable hippocampal volume increase following electroconvulsive stimulation. Neuropsychopharmacology. 2024. Madsen TM, Treschow A, Bengzon J, Bolwig TG, Lindvall O, Tingström A. Increased neurogenesis in a model of electroconvulsive therapy. Biol Psychiatry. 2000;47(12):1043–9. Warner-Schmidt JL, Madsen TM, Duman RS. Electroconvulsive seizure restores neurogenesis and hippocampus-dependent fear memory after disruption by irradiation. Eur J Neurosci. 2008;27(6):1485–93. Fridgeirsson EA, Deng ZD, Denys D, van Waarde JA, van Wingen GA. Electric field strength induced by electroconvulsive therapy is associated with clinical outcome. Neuroimage Clin. 2021;30:102581. Loef D, van Eijndhoven P, van den Munckhof E, Hoogendoorn A, Manten R, Spaans H-P, et al. Pre-treatment predictors of cognitive side-effects after treatment with electroconvulsive therapy in patients with depression: A multicenter study. Journal of Affective Disorders. 2024;349:321–31. Oltedal L, Bartsch H, Sørhaug OJ, Kessler U, Abbott C, Dols A, et al. The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy. Neuroimage Clin. 2017;14:422–32. Kamiya K, Hori M, Aoki S. NODDI in clinical research. Journal of Neuroscience Methods. 2020;346:108908. Palombo M, Ianus A, Guerreri M, Nunes D, Alexander DC, Shemesh N, et al. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. NeuroImage. 2020;215:116835. Schiavi S, Palombo M, Zacà D, Tazza F, Lapucci C, Castellan L, et al. Mapping tissue microstructure across the human brain on a clinical scanner with soma and neurite density image metrics. Hum Brain Mapp. 2023;44(13):4792–811. Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations Yes GvW has received research funding from Biogen, Bitbrain and Philips for unrelated work. PJL is supported by the Center for Urban Mental Health of the University of Amsterdam, by ZON-MW MODEM and by the ‘Institute for Chemical Neuroscience’, a gravitation grant of the Dutch Research Council NWO and the Dutch Ministery of OCW (grant nr 024.006.009). The other authors report no conflicts of interest. Supplementary Files table110032025.xlsx Table 1 Supplementary24032025.docx Supplemental Materials VolumechangesduringECT.mov Supplementary Video 1 VolumechangesafterECT.mov Supplementary Video 2 FAMDduringECT.mp4 Supplementary Video 3 FAMDafterECT.mp4 Supplementary Video 4 Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6295387","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":439963768,"identity":"4589d753-5b0a-4b78-8f95-cc81c27e71d4","order_by":0,"name":"Joey Verdijk","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYBACxgYwxQYmJRJ4EuQQcuxEajGGsBOAmJkIKyWAShMbCGlhbuA9wPCDgY/B4HjvwxsPZNLSN9zvMXxc+MOGwRyHFsYGvgTGHqBjDM4cN7ZI4MnJ3XCMx9h4RkIag2UzLi08Bgw8QC2SM9LYgH6pAGrh3SbNk3CYweAwbi2Mf0Ba5j8Da0k3OMa7/TdPwn+8WphBtvBLsIG05CQAtWxj5kk4gFtLM1/CYRkDNh5+njRmoF/SDGcey/8szZOWzINLi2F778GHbyqOybGxH2O8+bMnWZ7v8LHEzzw2dnIGxxuwa2nmYQC64RgPxM4ehAwPdjsYGOQhUjVQ7g9c6kbBKBgFo2AkAwCqH021eLz6lQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Twente","correspondingAuthor":true,"prefix":"","firstName":"Joey","middleName":"","lastName":"Verdijk","suffix":""},{"id":439963769,"identity":"ba840ce7-2f5d-40ac-921d-33fa548f664b","order_by":1,"name":"Julia Pottkämper","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"","lastName":"Pottkämper","suffix":""},{"id":439963770,"identity":"fa77561e-ad3e-4513-a7c4-1f68d8616134","order_by":2,"name":"Freek Doesschate","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Freek","middleName":"","lastName":"Doesschate","suffix":""},{"id":439963771,"identity":"8148f8a1-df36-4c7a-a292-9c8f5ea73de7","order_by":3,"name":"Laurens van de Mortel","email":"","orcid":"","institution":"Amsterdam UMC location University of Amsterdam","correspondingAuthor":false,"prefix":"","firstName":"Laurens","middleName":"van","lastName":"de Mortel","suffix":""},{"id":439963772,"identity":"fe79cc7e-10de-45ef-863a-b5af9775fff3","order_by":4,"name":"Sven Stuiver","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Sven","middleName":"","lastName":"Stuiver","suffix":""},{"id":439963773,"identity":"b59203d6-d8cc-4f0f-ac64-bf3cc321824b","order_by":5,"name":"Leif Oltedal","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Leif","middleName":"","lastName":"Oltedal","suffix":""},{"id":439963774,"identity":"4bc75ee5-cce7-41e9-95cd-06dd8ba9c55b","order_by":6,"name":"Paul Lucassen","email":"","orcid":"https://orcid.org/0000-0001-9708-9133","institution":"Swammerdam Institute for Life Sciences, University of Amsterdam,","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Lucassen","suffix":""},{"id":439963775,"identity":"7493c3e0-19fa-453d-ae1c-317597e05dae","order_by":7,"name":"Esmee Verwijk","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Esmee","middleName":"","lastName":"Verwijk","suffix":""},{"id":439963776,"identity":"2eb75b13-3ee0-4519-8ef8-747e11984fae","order_by":8,"name":"Michel van Putten","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Michel","middleName":"van","lastName":"Putten","suffix":""},{"id":439963777,"identity":"4ca855a3-c3f3-4cf9-94a1-2cbc74428309","order_by":9,"name":"Jeannette Hofmeijer","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jeannette","middleName":"","lastName":"Hofmeijer","suffix":""},{"id":439963778,"identity":"b086459c-9d9e-4a32-b6fc-ccf609c75321","order_by":10,"name":"Guido van Wingen","email":"","orcid":"","institution":"Amsterdam UMC","correspondingAuthor":false,"prefix":"","firstName":"Guido","middleName":"van","lastName":"Wingen","suffix":""},{"id":439963779,"identity":"102b2ec9-f9a1-480f-9dc8-877e601d46ff","order_by":11,"name":"Jeroen Van Waarde","email":"","orcid":"https://orcid.org/0000-0001-6792-5727","institution":"Rijnstate","correspondingAuthor":false,"prefix":"","firstName":"Jeroen","middleName":"Van","lastName":"Waarde","suffix":""}],"badges":[],"createdAt":"2025-03-24 12:35:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6295387/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6295387/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82300521,"identity":"f27c0c96-0118-45df-865d-dbf61b8fccdd","added_by":"auto","created_at":"2025-05-08 20:48:20","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116621,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic depiction of the timepoints. T0 = within 2 weeks before start of electroconvulsive therapy (ECT). T1.1 = first magnetic resonance imaging (MRI) directly after median session 3 (interquartile range [IQR] = 2). T1.2 = second MRI directly after median session 5 (IQR = 1.75). T1.3 = third MRI directly after median session 7 (IQR = 2). T2 = MRI within two weeks after completing the ECT-course. T3 = MRI at three months follow-up.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/1a8586363d998aef247965fa.jpeg"},{"id":82300518,"identity":"0e1d4f90-1715-4524-81bb-0517519949fd","added_by":"auto","created_at":"2025-05-08 20:48:20","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":967861,"visible":true,"origin":"","legend":"\u003cp\u003eVolume changes in grey (GM) and white matter (WM) segmentation. During the ECT-course, volume increases seem more confined to subcortical GM structures (i.e., hippocampus, amygdala). After the ECT-course, volume increases are generalized over the cortex, though transient after three months (displayed results are a quadratic contrast over T0, T1, and T2). GM increases are depicted in red, WM increases in yellow, and WM decreases in blue. No statistically significant GM decreases were found. All \u003cem\u003ep two-sided \u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/21e566c9d0f107204e3d1784.jpeg"},{"id":82301300,"identity":"f7113502-8e06-4540-a6f7-4925c8b85648","added_by":"auto","created_at":"2025-05-08 20:56:21","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":886610,"visible":true,"origin":"","legend":"\u003cp\u003eDuring the ECT course, fractional anisotropy (FA) decreases (blue) in white matter (WM) tracts. In contrast, after the ECT course, FA is largely unchanged, and mean diffusivity (MD) increases (red) linearly over timepoints T2 (\u0026lt; 2 weeks after the ECT course) and T3 (3 months after ECT course). All \u003cem\u003ep two-sided \u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/47d921815ad9899f88b5d121.jpeg"},{"id":82300529,"identity":"85a13660-0e82-4787-ac76-ddd63353b118","added_by":"auto","created_at":"2025-05-08 20:48:21","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1297503,"visible":true,"origin":"","legend":"\u003cp\u003eMean diffusivity significantly decreases in the left and right amygdala, and right hippocampus in ECT patients, but not in the left hippocampus, or insula. Timepoint of during ECT is first MRI sessions during course, i.e. median after 3\u003csup\u003erd\u003c/sup\u003e ECT session.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/b60d1006738164356b74b70e.jpeg"},{"id":82300527,"identity":"328881de-81ab-43fb-997a-8f066f25fa7c","added_by":"auto","created_at":"2025-05-08 20:48:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1374325,"visible":true,"origin":"","legend":"\u003cp\u003eThe letter fluency test (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.04), the imprinting sub-score of Rey Auditory Verbal Learning Test (RAVLT; \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.04) and the Category Fluency of animals test (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.02) transiently decreased after electroconvulsive therapy, corrected for test-retest in healthy controls.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/64e38d32af41d8c0d6fe455f.png"},{"id":82301863,"identity":"f4f8e9dc-f47d-454f-a7af-bd50dd5788f8","added_by":"auto","created_at":"2025-05-08 21:12:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5260585,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/fe54fdbe-007d-458a-a0c0-5c8ac243be86.pdf"},{"id":82300517,"identity":"0c27101e-3316-4a23-8f64-206ae9df91de","added_by":"auto","created_at":"2025-05-08 20:48:20","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14249,"visible":true,"origin":"","legend":"Table 1","description":"","filename":"table110032025.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/ff9e98bfc5abff093e2fae26.xlsx"},{"id":82301303,"identity":"487a8c90-3c33-4d7d-a8ec-2204133845fd","added_by":"auto","created_at":"2025-05-08 20:56:21","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":3941091,"visible":true,"origin":"","legend":"Supplemental Materials","description":"","filename":"Supplementary24032025.docx","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/7982f5b542c0550cebfcc4f7.docx"},{"id":82301302,"identity":"88264abd-a203-4074-ad59-b5c66c64dce0","added_by":"auto","created_at":"2025-05-08 20:56:21","extension":"mov","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":6032860,"visible":true,"origin":"","legend":"Supplementary Video 1","description":"","filename":"VolumechangesduringECT.mov","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/327e733d9422f7000b640f78.mov"},{"id":82300534,"identity":"219efb3c-bdc0-449a-a20e-61577d01a2ec","added_by":"auto","created_at":"2025-05-08 20:48:21","extension":"mov","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5497948,"visible":true,"origin":"","legend":"Supplementary Video 2","description":"","filename":"VolumechangesafterECT.mov","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/c81e759b7f87f8f9a7eb2c32.mov"},{"id":82300543,"identity":"e806a19a-95f8-4a86-8e33-ef0968075b72","added_by":"auto","created_at":"2025-05-08 20:48:21","extension":"mp4","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":31361405,"visible":true,"origin":"","legend":"Supplementary Video 3","description":"","filename":"FAMDduringECT.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/f1a16fef9d3717eadba1dc58.mp4"},{"id":82301306,"identity":"0ace8cbc-53a0-43a9-891d-5776904d3c98","added_by":"auto","created_at":"2025-05-08 20:56:22","extension":"mp4","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":31094791,"visible":true,"origin":"","legend":"Supplementary Video 4","description":"","filename":"FAMDafterECT.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6295387/v1/97a0b6bf49c9f65f663f5d04.mp4"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e\nGvW has received research funding from Biogen, Bitbrain and Philips for unrelated work. PJL is supported by the Center for Urban Mental Health of the University of Amsterdam, by ZON-MW MODEM and by the ‘Institute for Chemical Neuroscience’, a gravitation grant of the Dutch Research Council NWO and the Dutch Ministery of OCW (grant nr 024.006.009). The other authors report no conflicts of interest.","formattedTitle":"Electroconvulsive therapy induces rapid microstructural and macrostructural changes, but microstructural changes are longer-lasting","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMajor depressive disorder (MDD) is a common mental disorder, with a lifetime prevalence of up to 20% (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Psycho- and pharmacotherapy benefit around 50% of patients, but many of them relapse and an estimated 30% of patients suffers from treatment-resistant depression (TRD) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). A frequently used and generally effective treatment modality for TRD cases is electroconvulsive therapy (ECT) (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Yet, its use is limited by practicalities, variation in response rate, stigma, concerns over possible (cognitive) side-effects and a lack of mechanistic insight. As a result, less than 1% of depressed patients receives ECT (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently, the most common theories on the possible mechanisms of action of ECT describe an induction of immediate early genes, brain-derived neurotrophic factor, and neuroplastic effects (synaptogenesis, dendritic arborization, glial activation, angiogenesis and neurogenesis) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). These theories are mainly derived from animal models. Clarity about the mechanisms of action and safety may help reduce fear and promote a more effective utilization.\u003c/p\u003e \u003cp\u003eMacrostructural brain changes have been studied most extensively in ECT-patients. Using T1-weighted magnetic resonance imaging (T1W MRI), increased volumes of hippocampus and amygdala have been reported within 24 hours after a first ECT-session (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). After a completed ECT-course generalized increases of grey matter (GM) volume are found (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). These seem transient, as GM volume decreases again in three to six months after the ECT-course (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). How these macrostructural changes relate to the possible mechanisms of action of ECT is unclear, since neuroplastic effects are not expected to (fully) explain generalized increases of GM volume (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicrostructural brain changes have so far been more sparsely studied in ECT-patients. Diffusion tensor imaging (DTI) holds potential to further elucidate the nature of microstructural changes in both GM and white matter (WM). The few studies that applied DTI report opposing findings regarding WM changes of fractional anisotropy (FA) and mean diffusivity (MD) following completion of an entire ECT-course (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Current DTI evidence further indicates that MD decreases in hippocampal GM after the ECT-course, which has been hypothesized to be governed by neuroplastic changes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Until now, however, studies of diffusivity dynamics immediately following separate ECT sessions are lacking, which may provide additional insight into the nature of these microstructural changes.\u003c/p\u003e \u003cp\u003eIn daily ECT-practice, patients often show rapid improvements in mood but also develop cognitive side-effects, that can last for weeks or longer (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). These rapid clinical changes probably relate to changes in cerebral volume and diffusion measures. Repeated MRI studies, with scans between 48 hours after the tenth ECT session and one to two weeks after the ECT-course, give indications for a negative impact of volume increase of the hippocampus on cognitive outcome, and in one study, a negative impact of decrease of MD in this region (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Additionally, volume increase of the hippocampus and amygdala has been associated with reduction of depressive symptoms tested over scans between 24 hours after the second ECT-session, though combined with scans after the ECT-course (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Whether the same changes contribute to both cognitive side-effects and efficacy is unclear. Cerebral volume and diffusion changes assessed in multiple regions directly after initial ECT-sessions may be more specific to the reported associations of efficacy or cognitive side-effects.\u003c/p\u003e \u003cp\u003eIn this prospective longitudinal study, we therefore investigated early and later temporal changes in cerebral volume and diffusivity of MDD patients, both at several timepoints throughout the ECT-course and at three months follow-up. Data were corrected for normal test-retest variability based on a group of healthy controls (HC). We subsequently associated the early cerebral changes with cognitive and efficacy measures.\u003c/p\u003e "},{"header":"Methods and materials","content":"\n\u003ch3\u003eStudy design\u003c/h3\u003e\n\u003cp\u003eData were included from the participants from two prospective studies in depressed patients treated with ECT between 2017 and 2023 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). MRI scans of both studies were acquired on the same scanner with identical sequences. To correct for test-retest effects, healthy control (HC) data were included from age-, sex-, and education level (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)-matched participants who were assessed prospectively as part of one of the studies with cognitive tests and MRI (Supplementary Materials). All patients and HC provided oral and written informed consent before entering the studies.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and timepoints of measurements\u003c/h2\u003e \u003cp\u003eECT-patients were \u0026gt;\u0026thinsp;17 years-of-age, both hospitalized and non-hospitalized, treatment-resistant, currently depressed classified (according to the Dutch version of the Mini International Neuropsychiatric Interview (MINI) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) as unipolar depressive disorder, bipolar disorder or schizoaffective disorder). MRI and clinical data of ECT-patients were gathered before starting of the course at baseline; (T0), postictal\u0026thinsp;~\u0026thinsp;1 h each time after three separate ECT-sessions (for details, see below) (T1; separate as T1.1, T1.2 and T1.3), within two weeks after completing the ECT-course (T2) and at three months follow-up (T3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe HCs were \u0026gt;\u0026thinsp;17 years-of-age, all scored negative on all items of the MINI, and were assessed at baseline (T0), after one month (T2) and after three months (T3). 72 ECT-patients could be included. 32 of these patients were excluded due to missing MRI data. Of these,10 did not pass quality control of MRI. A further 11 patients were excluded only for the analysis of MRI during the ECT-course because of missing data (Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eECT-procedure\u003c/h3\u003e\n\u003cp\u003eECT-sessions were administered according to Dutch guidelines, two times a week (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), using bifrontotemporal (BL) or unilateral (UL) electrode placement (Supplementary Methods).\u003c/p\u003e\n\u003ch3\u003eImage acquirement and preprocessing\u003c/h3\u003e\n\u003cp\u003eAt identical timepoints as the cognitive tests, T1W and DTI MRI scans were acquired in ECT-patients as well as in HCs (T0, T2 and T3). Additionally, only in the ECT-patients, at a first timepoint during the ECT-course (T1.1; median after 3rd ECT-session [IQR 1.25]), at a second timepoint (T1.2; median after 5th ECT-session [IQR 0.75]) and at a third timepoint (T1.3; median after the 7th ECT-session [IQR 1]), MRI scans were acquired approximately one hour after the ECT-session. Acquisition parameters and preprocessing are described in the Supplementary Methods.\u003c/p\u003e\n\u003ch3\u003eDTI analyses\u003c/h3\u003e\n\u003cp\u003eWe fitted a diffusion tensor model at each voxel (Supplementary Methods). For voxel-wise analysis of WM, we used the Tract-Based Spatial Statistics pipeline (TBSS; (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)), part of FSL (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). To investigate MD changes in expected areas of GM volume increase (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), we chose ROIs of the hippocampus and amygdala, limited to initial volume change at T1.1. Additionally, we chose the insular cortex because of its relevance for depression (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) and possible volume increases beneath the ECT-electrodes.\u003c/p\u003e\n\u003ch3\u003eClinical outcomes\u003c/h3\u003e\n\u003cp\u003eIn MDD patients, depression severity was assessed at T0, T2 and T3 with the Hamilton Depression Rating Scale (HDRS) (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), while extensive cognitive measurements were performed as well. Global cognitive functioning was assessed using the Montreal Cognitive Assessment (MOCA) (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) or Mini-Mental State Examination (MMSE) (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). MMSE scores were converted to MOCA using a validated method (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). More specific cognitive domains were examined with the Rey Auditory Verbal Learning Test (RAVLT; immediate and delayed recall) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), the Category Fluency of animals and occupations (CFa and CFo; executive retrograde memory) (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), the Letter Fluency (LF; executive retrograde memory) (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), the backwards digit span testing (DSB; working memory) (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e), the STROOP task (processing speed) (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), the Trail Making Test A and B (TMT A/B; attention and cognitive flexibility, respectively) (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), and the Subjective Assessment of Memory Impairment (SAMI) (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). RAVLT, DSB, STROOP, TMT A/B, and SAMI were only available in one of the two included studies.\u003c/p\u003e \u003cp\u003eWe first explored changes in cognitive functions over time in the ECT-patients corrected for test-retest variability over time based on the HCs. Thereafter, we selected the tests that significantly changed in patients and used these outcomes to examine associations with (early and later) cerebral volume and diffusion changes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eTo investigate changes \u003cem\u003eduring\u003c/em\u003e the ECT-course, we used three planned Helmert contrasts between baseline (T0) and the three available postictal timepoints (i.e., T1.1, T1.2 and T1.3), as well as between the postictal timepoints themselves. To test changes \u003cem\u003eafter\u003c/em\u003e the ECT-course over T0, T2 and T3, we used polynomial contrasts to test whether there were linear or quadratic changes, corrected for changes in HC. Voxel-wise family wise error (FWE) correction was performed using Threshold-Free Cluster Enhancement (TFCE) at a significance level of 0.05. For all analyses, we applied Bonferroni correction for multiple comparisons (i.e., for the cognitive test battery, FWE correction for 11 models). Additionally, effect sizes for the interaction terms were calculated using Pearson\u0026rsquo;s \u003cem\u003er\u003c/em\u003e. Further details are described in the Supplementary Materials.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eIncluded sample and clinical characteristics\u003c/h2\u003e \u003cp\u003eIn total, 72 patients were included in the datasets. We included 30 patients for the analysis of brain changes at T0, T2 and T3, and 19 patients for T0 and T1 (Supplementary Fig.\u0026nbsp;1). Table\u0026nbsp;1 summarizes the characteristics of the included patients and HC. Due to missing data, the number of ECT-patients varied for the individual cognitive tests (see further). At group level, ECT-patients did not differ from HC regarding age, sex and education level (\u003cem\u003ep\u003c/em\u003e values\u0026thinsp;\u0026gt;\u0026thinsp;.05). Over time from T0 to T2 and T3, the mean HDRS-scores showed a significant quadratic decrease ([\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;70], \u003cem\u003eβ\u003c/em\u003e = -1.8, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.43, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStructural volume changes\u003c/h2\u003e \u003cp\u003e \u003cem\u003eDuring the ECT-course.\u003c/em\u003e The GM of multiple subcortical structures (i.e., hippocampus, amygdala and insular cortices in both hemispheres) increased significantly over the three timepoints during the ECT-course (i.e., average T1.1-T1.3, compared to T0 and corrected for changes over time in HCs; see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Video 1). Notably, no significant changes in the cortex were detected. In the WM segmentation, we found significant decreases in volume adjacent to some of the GM increases. The right thalamus, erroneously automatically segmented into WM, significantly increased in volume (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Comparisons between the consecutive timepoints during the ECT-course further showed non-significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.05) GM increases between T.1.1 and T.1.3.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAfter the ECT-course.\u003c/em\u003e Across T0, T2 and T3, we found widespread GM increases of cortical and subcortical structures (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Supplementary Video 2), controlled for HC. These increases were quadratic, and transient (i.e., T3 returning to T0, confirmed with post-hoc t-tests of T0 versus T3, Supplementary Fig.\u0026nbsp;2) Additionally, some areas in the WM segmentation transiently increased and smaller areas of adjacent WM transiently decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBrain diffusion changes\u003c/h2\u003e \u003cp\u003e \u003cem\u003eDuring the ECT-course.\u003c/em\u003e Compared to baseline (T0), we detected lateralized decreases of MD in the right amygdala (\u003cem\u003eβ\u003c/em\u003e = -0.08, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.50, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001) and right hippocampus (\u003cem\u003eβ\u003c/em\u003e = -0.07, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.48, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001) during the ECT-course (i.e., at timepoints T1.1, T1.2 and T1.3), while the contralateral and insular structures did not change (see Supplementary Results). In the WM, MD did not significantly change postictally (at minimum a cluster with \u003cem\u003ep-\u003c/em\u003evalue of 0.051), nor did it change further in the course in the comparisons between postictal measurements. FA though, generalized throughout the WM, was significantly lower postictally (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Video 3) (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). From postictal measurement 1 to 2, FA further decreased in some clusters. From postictal measurement 2 to 3, FA did not further decrease, and instead increased in an occipitoparietal cluster.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eAfter the ECT-course.\u003c/em\u003e Controlled for changes in HC over time, MD in the left amygdala (\u003cem\u003eβ\u003c/em\u003e = -0.14, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.001), the right amygdala (\u003cem\u003eβ\u003c/em\u003e = -0.12, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.29, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.02), and the right hippocampus (\u003cem\u003eβ\u003c/em\u003e = -0.12, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.32, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.008) showed transient (quadratic) decreases from baseline (T0) across T2 to T3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, confirmed with post-hoc t-tests T0 with T3 \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Supplementary Video 4). Changes in left hippocampus and both insular cortices did not reach statistical significance. In contrast, in the WM, we found persisting, widespread linear increases in MD, while FA was mostly unchanged except for one small cluster showing a linear decrease in FA in the left parietal WM tracts (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further investigate the nature of the diffusion changes in WM, we post-hoc applied NODDI-DTI on our single-shell DTI maps (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e) to calculate neurite density indices (NDI) and orientation dispersion indices (ODI) from the normalized, non-skeletonized DTI maps. We used the FA distance maps from the TBSS pipeline to project NODDI maps onto the skeleton and found that the MD increases in WM over T0, T1 and T2 were accompanied by linear decreases in NDI, while ODI remained unchanged.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eNeuropsychological outcomes\u003c/h2\u003e \u003cp\u003eAt baseline, ECT-patients scored significantly lower than HC regarding the MOCA (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;70]\u0026thinsp;=\u0026thinsp;23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1; HC\u0026thinsp;=\u0026thinsp;26.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), CFa (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;62]\u0026thinsp;=\u0026thinsp;42.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0; HC\u0026thinsp;=\u0026thinsp;49.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02), CFo (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;62]\u0026thinsp;=\u0026thinsp;43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.1; HC\u0026thinsp;=\u0026thinsp;54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), STROOP (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;20]\u0026thinsp;=\u0026thinsp;46.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7; HC\u0026thinsp;=\u0026thinsp;53.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), DSB (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;20]\u0026thinsp;=\u0026thinsp;42.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3; HC\u0026thinsp;=\u0026thinsp;51.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and TMT (ECT [\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;19]\u0026thinsp;=\u0026thinsp;42.3\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3; HC\u0026thinsp;=\u0026thinsp;50.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Supplementary Fig.\u0026nbsp;3). LF (\u003cem\u003en\u003c/em\u003e ECT\u0026thinsp;=\u0026thinsp;22) and RAVLT (\u003cem\u003en\u003c/em\u003e ECT\u0026thinsp;=\u0026thinsp;23, both total and imprinting) did not differ at baseline.\u003c/p\u003e \u003cp\u003eOver T0, T1 and T2, corrected for test-retest effects in HCs, we detected transient (quadratic) decreases of the LF test (\u003cem\u003eβ\u003c/em\u003e = -2.0, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.30, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.04), the imprinting sub-score of RAVLT (\u003cem\u003eβ\u003c/em\u003e = -2.8, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.30, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.04) and the CFa test (\u003cem\u003eβ\u003c/em\u003e = -2.5, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.25, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.02). Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows these results for ECT-patients and HCs. These cognitive tests had all recovered at the three months follow-up (T3; see Supplementary Results). Scores on the MOCA, SAMI, RAVLT (i.e., recall score corrected for total imprinted words), TMT, STROOP, DSB, and CFo did not change significantly (see Supplementary Fig.\u0026nbsp;3 and Supplementary Results) at either of the two timepoints after the ECT-course (i.e., T2 and T3, compared to T0 and corrected for test-retest effects in HC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCerebral volume and diffusion changes in relation to cognitive and efficacy outcomes\u003c/h2\u003e \u003cp\u003eWe included the LF, RAVLT (imprinting) and CFa as cognitive outcome variables to associate with our MRI outcomes, as these were the only ones to significantly change. No significant associations were found between any change in cerebral volume or diffusivity with any of the established deteriorations on these tests (i.e., when testing for associations of change (T0 \u0026ndash; T2) of scores in LF, the imprinting sub-score of RAVLT and the CFa test, with both GM and WM volume change (T0 \u0026ndash; T1.1), MD change within GM ROIs (T0 \u0026ndash; T1.1), and voxel-wise diffusion changes in the WM skeleton (T0 \u0026ndash; T1.1).)\u003c/p\u003e \u003cp\u003eAlthough a lower decrease in the imprinting score of RAVLT seemed to be associated with a larger GM volume increase during the ECT-course (i.e., T0 \u0026ndash; T1.1) in multiple clusters, this association just failed to reach significance after accounting for testing multiple brain-behavior associations (minimum \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003euncorrected\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e=\u003c/em\u003e 0.0125, \u003cem\u003ep corrected for multiple cognitive tests\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05; Supplementary Fig.\u0026nbsp;4). Also, change in HDRS-scores at T2 compared to baseline T0 was not associated with any of the cerebral volume or DTI parameters.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective longitudinal study in ECT-patients, our novel findings reveal early microstructural changes during ECT. In GM, we found an acutely decreased diffusivity which is transient within 3 months. In contrast, in WM, we found an increased diffusivity which is longer lasting. Furthermore, we confirm earlier reported macrostructural changes of GM volume increase which is transient within 3 months. Though during the ECT-course, the GM volume increase seems more localized to subcortical structures, which after the ECT-course is generalized over the cortex. The observed micro- and macrostructural changes in patients were notably not significantly associated with the observed transient decline in cognitive functioning, nor with clinical efficacy after ECT.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eInterpretations of microstructural and macrostructural changes in GM\u003c/h2\u003e \u003cp\u003eConsistent with earlier findings, we found volume increases of the subcortical GM structures in ECT-treated depressed patients accompanied by decreases in MD (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Of these structures, in particular the hippocampus and amygdala are associated with depression (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). Furthermore, we confirm earlier data showing that these volume increases are already present from the 1st to 3rd ECT-session (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Our novel finding is that the decreases in MD already occur after the third ECT-session.\u003c/p\u003e \u003cp\u003eMultiple interpretations are possible of the early present decreased MD and volume in GM. Cellular stress in the form of cytotoxic edema may explain our findings of acutely and relatively short-lived decreased MD, and volume increase, in GM (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). If present, we hypothesize this neuronal stress to be transient, and much less prominent than the neuropathological and/or cellular changes found after status epilepticus or chronic epilepsy in both rodent models and human postmortem brain, supported by a lack of volume loss, and lack of clinical deleterious effects. Indeed, in contrast, malformations, granule cell dispersion, mossy fiber sprouting, cornu Ammonis (CA) cell loss, blood brain barrier leakage and astrogliosis have been reported in hippocampal and extrahippocampal limbic regions of epileptic patients (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Volume and diffusivity changes after ECT could in principle thus also relate to inflammatory changes and the activation of (astro)glia (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Yet, the electroconvulsive shock (ECS) treatment paradigm in rodents differs from those paradigms that induce epileptic seizures, which is generally more short term. ECS initiated an immediate glial reaction, though this was already decreased four weeks later, which may fit our MD findings in GM (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e). Additionally, no indications could be found for massive cell loss or glial activation in a recent study on hippocampal tissue from (chronic) ECT-treated, depressed patients (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). Hypothetically, transient neuronal stress may thus cause the transient cognitive side-effects, and consequently induce expression of early-immediate genes and neuroplasticity, leading to reduction of depressive symptoms in ECT (\u0026lsquo;disrupt and rewire\u0026rsquo;) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlternatively, primarily ensuing neuroplasticity changes have been proposed to be associated with the decreased MD in GM, a.o. in the hippocampal dentate gyrus (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). A recent study in rats supports neuroplastic effects, though other brain regions can also be involved (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Studies inducing ECS in rodent models reported widespread neuroplasticity changes, e.g. in hippocampal neurogenesis, cortical proliferation and synaptic changes (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), while dendritic arborization and glial activation have been observed after three ECS sessions (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). The cellular changes in animal models compare to our findings of an early decrease of MD coinciding with volume increase. ECT may thus rapidly and transiently cause neuroplastic effects, that appear to be initially concentrated in depression-related subcortical structures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMicrostructural changes in WM are longer lasting\u003c/h2\u003e \u003cp\u003eIn contrast to our findings in GM, diffusivity in WM increases and is present longer than 3 months. Because of the differences in diffusivity and longevity of our findings, we hypothesize that we captured multiple processes in the brain throughout the ECT-course and beyond. In WM, we interpret our findings as increased extracellular free diffusion, without significant changes to microstructural organization, because of the absence of significant changes of FA after the ECT-course. Also, though preliminary, this seems supported by our findings of a coinciding decrease of neurite density (NDI), without a change in the orientation variation of neurites (ODI). In a different publication (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) on the same study sample, we find decreased FA shortly after the ECT session, which thus seems very short lived. Whether the longer present increase of diffusivity in WM contributes to the efficacy of ECT has to be further examined in future research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eLateralized decreases of MD in GM throughout ECT, but not beyond\u003c/h2\u003e \u003cp\u003eWe further detected right-sided decreases of MD in GM in the hippocampus and amygdala during the ECT-course, a lateralization that was no more present within two weeks after the ECT-course. Though this may be caused by differences in sample size over timepoints, which compromised our power to detect changes, we hypothesize that the initial lateralization could be due to the right unilateral electrode placement in a quarter of our included patients. Initially, a direct influence of the e-fields on the right side of the brain may cause microstructural changes (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e), while after the ECT-course, we speculate this may lead to a cascade of neurotrophic effects, which spreads throughout the brain, again dissipating the lateralization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eNo associations with cognitive outcome and efficacy\u003c/h2\u003e \u003cp\u003eIn our depressed patients, mood improvement and clinically relevant cognitive side-effects were seen, which were statistically significant at group level. We replicated that the cognitive side-effects are transient after 3 months (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e). We did not detect associations between the transient disturbances in verbal recall and retrograde executive memory functions, and any of the observed MRI changes, nor between antidepressive efficacy and MRI measures. We hypothesize that this results from a lack of power, since voxel-wise regression analyses with a more stringent correction of multiple comparisons, require far larger sample sizes, especially of linear outcome data (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). We did detect borderline significant associations between the imprinting score of RAVLT and anatomical clusters adhering to the functional default mode and salience networks (Supplementary Fig.\u0026nbsp;4), suggesting that larger volume increases in these regions mitigate the ECT-related cognitive decline.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eDetected cognitive side-effects of ECT are transient\u003c/h2\u003e \u003cp\u003eThe current study showed that depressed patients had lower cognitive functioning before ECT compared to healthy controls, probably as part of the disorder. Despite the stigma surrounding cognitive side-effects of ECT, we not only show that the cognitive decreases are transient after three months, we also showed that some cognitive performances improved after ECT. Moreover, we did not detect subjective cognitive side-effects after the ECT-course. Therefore, more research-substantiated information regarding (baseline) cognitive functioning and the to be expected cognitive side-effects should be given to patients, caregivers and involved professionals. This may help decrease ECT stigma.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eOur design has multiple strengths. First, we collected longitudinal data in ECT-patients and matched HC over three months, at several timepoints, as well as during the ECT-course in the patients. We combined multiple modalities of structural MRI data, and scanned all patients and HC in the same environment and MRI scanner. Second, we were able to additionally collect an extensive battery of cognitive functions in ECT-patients as well as in the HCs. However, our design also has limitations. First, our final sample size was relatively small. MRI data was not available for all ECT-patients during the ECT-course (i.e., at T1), which also caused heterogeneity in the number of patients per timepoint. Also, the number of patients per cognitive outcome measure was heterogeneous due to missing data, as well as differing outcome measures between the two included studies. Second, because of our relatively hypothesis-free approach, we included a multitude of outcome measures, for which we had to perform stringent FWE correction, ultimately limiting our power to detect associations. Third, apart from MD of amygdala, hippocampus and insula, we employed whole-brain voxel-wise regression to test for associations with cognitive outcome, which is less sensitive than limiting analysis to specific structures. Fourth, we post-hoc aimed to further specify the MD changes in WM using NODDI in our single-shell data, though no consensus exists whether this is feasible without multi-shell acquisitions (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Also, while one possible hypothesized mechanism in ECT is inflammatory changes, the NODDI parameters produce mixed results in pathologically confirmed neuronal tissue where glia cells are activated (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe therefore advise future studies to use models such as the recently developed soma and neurite density imaging (SANDI) (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e), which we were unable to apply, since our data lacked the required multi-shell acquisition up to \u003cem\u003eb\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6000s/mm\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, ECT in the current cohort improved depressive symptoms until 3 months after cessation, and induced some cognitive side-effects which were transient. Further throughout and beyond the ECT-course, early - but transient \u0026ndash; significant brain volume increases were found in subcortical gray matter structures, which were accompanied by \u0026ndash; also transient - decreases in (local) mean diffusivity. In contrast, diffusivity increases in white matter tracts seemed to persist for at least three months after ECT. Significant verbal memory disturbances did not associate with early structural or diffusion brain changes. Our findings show that while macrostructural changes are transient, microstructural changes are divergent and longer lasting.\u003c/p\u003e \u003cp\u003eDeclarations of interest\u003c/p\u003e \u003cp\u003eGuido van Wingen has received research funding from Biogen, Bitbrain and Philips for unrelated work. The other authors report no conflicts of interest.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eDeclarations of interest\u003c/p\u003e\n\u003cp\u003eGuido van Wingen has received research funding from Biogen, Bitbrain and Philips for unrelated work. The other authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThis complex study was not possible without all patients and participants in the healthy control group, as well as the collaborators from the departments of psychiatry (especially Oscar Buno Heslinga, ECT-nurse, and Nancy Sanders, secretary), anesthesiology and radiology (especially Marit Bles) of Rijnstate hospital Arnhem, The Netherlands. Specially mentioned should be our group of research volunteers without whom this study was not possible: Marleen Middelman, Simon de Both, Tonia Schouten, Tijn Stolk, Anna Schoonhoven, Nienke Gerards, Nicole de Kruijf, Amber Selie, Arnoud van der Meulen, Tessa Klein, Marlous Verhulst, Gijsbert Schuur, Stanley Pham, Rajco Meuleman, David van Ghroningen, Madelon Thevis, Sanédy Simon, Chantal Staring, Max Roelofs, Robyn van Vehmendahl, Stijn Donker, and Tim van Helden.\u003c/p\u003e\n\u003cp\u003ePJL is supported by the Center for Urban Mental Health of the University of Amsterdam, by ZON-MW MODEM and by the ‘Institute for Chemical Neuroscience’, a gravitation grant of the Dutch Research Council NWO and the Dutch Ministery of OCW (grant nr 024.006.009).\u003c/p\u003e\n\u003cp\u003eThe SYNAPSE trial, which supplied a large portion of the total population, was funded by EpilepsieNL (grant number WAR 19-02).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, et al. Epidemiology of Adult DSM-5 Major Depressive Disorder and Its Specifiers in the United States. JAMA Psychiatry. 2018;75(4):336\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, et al. Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry. 2006;163(11):1905\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLundberg J, Cars T, L\u0026ouml;\u0026ouml;v S, S\u0026ouml;derling J, Sundstr\u0026ouml;m J, Tiihonen J, et al. Association of Treatment-Resistant Depression With Patient Outcomes and Health Care Resource Utilization in a Population-Wide Study. JAMA Psychiatry. 2023;80(2):167\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNygren A, Reutfors J, Brandt L, Bod\u0026eacute;n R, Nordenskj\u0026ouml;ld A, Tiger M. Response to electroconvulsive therapy in treatment-resistant depression: nationwide observational follow-up study. BJPsych Open. 2023;9(2):e35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheepens DS, van Waarde JA, Lok A, Zantvoord JB, de Pont B, Ruh\u0026eacute; HG, et al. [Electroconvulsion therapy for persistent depression in the Netherlands; very low application rate]. Tijdschr Psychiatr. 2019;61(1):16\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilkinson ST, Agbese E, Leslie DL, Rosenheck RA. Identifying Recipients of Electroconvulsive Therapy: Data From Privately Insured Americans. Psychiatr Serv. 2018;69(5):542\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKellner CH, Obbels J, Sienaert P. When to consider electroconvulsive therapy (ECT). Acta Psychiatr Scand. 2020;141(4):304\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHebbrecht K, Dejaeger M, Giltay EJ, Birkenh\u0026auml;ger T, Sabbe B, Verwijk E, et al. Cognitive trajectories during and after electroconvulsive therapy in patients with MDE: Taking different perspectives. J Psychiatr Res. 2022;156:132\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOusdal OT, Brancati GE, Kessler U, Erchinger V, Dale AM, Abbott C, et al. The Neurobiological Effects of Electroconvulsive Therapy Studied Through Magnetic Resonance: What Have We Learned, and Where Do We Go? Biol Psychiatry. 2022;91(6):540\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang AD, Vaidya PV, Retzbach EP, Chung SJ, Kim U, Baselice K, et al. Narp Mediates Antidepressant-Like Effects of Electroconvulsive Seizures. Neuropsychopharmacology. 2018;43(5):1088\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh A, Kar SK. How Electroconvulsive Therapy Works?: Understanding the Neurobiological Mechanisms. Clin Psychopharmacol Neurosci. 2017;15(3):210\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoshi SH, Espinoza RT, Pirnia T, Shi J, Wang Y, Ayers B, et al. Structural Plasticity of the Hippocampus and Amygdala Induced by Electroconvulsive Therapy in Major Depression. Biol Psychiatry. 2016;79(4):282\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrancati GE, Brekke N, Bartsch H, Evjenth S\u0026oslash;rhaug OJ, Ousdal OT, Hammar \u0026Aring;, et al. Short and long-term effects of single and multiple sessions of electroconvulsive therapy on brain gray matter volumes. Brain Stimul. 2021;14(5):1330\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGbyl K, Rostrup E, Raghava JM, Carlsen JF, Schmidt LS, Lindberg U, et al. Cortical thickness following electroconvulsive therapy in patients with depression: a longitudinal MRI study. Acta Psychiatr Scand. 2019;140(3):205\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJehna M, Wurm W, Pinter D, Vogel K, Holl A, Hofmann P, et al. Do increases in deep grey matter volumes after electroconvulsive therapy persist in patients with major depression? A longitudinal MRI-study. Journal of Affective Disorders. 2021;281:908\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyden H, Espinoza RT, Pirnia T, Clark K, Joshi SH, Leaver AM, et al. Electroconvulsive therapy mediates neuroplasticity of white matter microstructure in major depression. Transl Psychiatry. 2014;4(4):e380.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRepple J, Meinert S, Bollettini I, Grotegerd D, Redlich R, Zaremba D, et al. Influence of electroconvulsive therapy on white matter structure in a diffusion tensor imaging study. Psychological Medicine. 2020;50(5):849\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNickl-Jockschat T, Palomero Gallagher N, Kumar V, Hoffstaedter F, Br\u0026uuml;gmann E, Habel U, et al. Are morphological changes necessary to mediate the therapeutic effects of electroconvulsive therapy? Eur Arch Psychiatry Clin Neurosci. 2016;266(3):261\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGyger L, Ramponi C, Mall JF, Swierkosz-Lenart K, Stoyanov D, Lutti A, et al. Temporal trajectory of brain tissue property changes induced by electroconvulsive therapy. Neuroimage. 2021;232:117895.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuninga JO, Mandl RCW, Froeling M, Siero JCW, Somers M, Boks MP, et al. Vasogenic edema versus neuroplasticity as neural correlates of hippocampal volume increase following electroconvulsive therapy. Brain Stimulation. 2020;13(4):1080\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerwijk E, Comijs HC, Kok RM, Spaans HP, Tielkes CE, Scherder EJ, et al. Short- and long-term neurocognitive functioning after electroconvulsive therapy in depressed elderly: a prospective naturalistic study. Int Psychogeriatr. 2014;26(2):315\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGbyl K, St\u0026oslash;ttrup MM, Mitta Raghava J, Xue Jie S, Videbech P. Hippocampal volume and memory impairment after electroconvulsive therapy in patients with depression. Acta Psychiatr Scand. 2021;143(3):238\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJorgensen A, Magnusson P, Hanson LG, Kirkegaard T, Benveniste H, Lee H, et al. Regional brain volumes, diffusivity, and metabolite changes after electroconvulsive therapy for severe depression. Acta Psychiatr Scand. 2016;133(2):154\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan der AJ, De Jager JE, van Dellen E, Mandl RCW, Somers M, Boks MPM, et al. Changes in perfusion, and structure of hippocampal subfields related to cognitive impairment after ECT: A pilot study using ultra high field MRI. J Affect Disord. 2023;325:321\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePottk\u0026auml;mper JCM, Verdijk J, Stuiver S, Aalbregt E, Ten Doesschate F, Verwijk E, et al. Exploring postictal recovery with acetaminophen or nimodipine: A randomized-controlled crossover trial. Ann Clin Transl Neurol. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerdijk J, Pottk\u0026auml;mper JCM, Verwijk E, van Wingen GA, van Putten M, Hofmeijer J, et al. Study of effect of nimodipine and acetaminophen on postictal symptoms in depressed patients after electroconvulsive therapy (SYNAPSE). Trials. 2022;23(1):324.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheepens DS, van Waarde JA, Ten Doesschate F, Westra M, Kroes MCW, Schene AH, et al. Negative cognitive schema modification as mediator of symptom improvement after electroconvulsive therapy in major depressive disorder. J Affect Disord. 2022;310:156\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerhage F. Intelligentie en leeftijd bij volwassenen en bejaarden: Koninklijke Van Gorcum; 1964.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22\u0026ndash;33;quiz 4\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePsychiatrie NVv. Richtlijn Electroconvulsietherapie (ECT): Federatie Medisch Specialisten; 2021 [\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage. 2006;31(4):1487\u0026ndash;505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen-Berg H, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004;23 Suppl 1:S208-19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchnellb\u0026auml;cher GJ, Rajkumar R, Veselinović T, Ramkiran S, Hagen J, Shah NJ, et al. Structural alterations of the insula in depression patients - A 7-Tesla-MRI study. Neuroimage Clin. 2022;36:103249.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasreddine ZS, Phillips NA, B\u0026eacute;dirian V, Charbonneau S, Whitehead V, Collin I, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFolstein MF, Folstein SE, McHugh PR. \"Mini-mental state\". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFasnacht JS, Wueest AS, Berres M, Thomann AE, Krumm S, Gutbrod K, et al. Conversion between the Montreal Cognitive Assessment and the Mini-Mental Status Examination. J Am Geriatr Soc. 2023;71(3):869\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRey A. L'examen clinique en psychologie. 1958.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuteijn F, Van der Ploeg FAE. Groninger Intelligentie Test (GIT). Lisse, Netherlands: Swets \u0026amp; Zeitlinger; 1983.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamsay MC, Reynolds CR. Separate digits tests: a brief history, a literature review, and a reexamination of the factor structure of the Test of Memory and Learning (TOMAL). Neuropsychol Rev. 1995;5(3):151\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStrauss E, Sherman EMS, Spreen O. Compendium of Neuropsychological Test: Administration, Norms, and Commentary. New York, NY: Oxford University Press; 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReitan RM. Trail-Making Test. Arizona: Reitan Neuropsychology Laboratory; 1979.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKumar DR, Han HK, Tiller J, Loo CK, Martin DM. A Brief Measure for Assessing Patient Perceptions of Cognitive Side Effects After Electroconvulsive Therapy: The Subjective Assessment of Memory Impairment. J ect. 2016;32(4):256\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerdijk JPAJ, Schouten TAL, Pottk\u0026auml;mper JCM, van de Mortel LA, ten Doesschate F, Stuiver S, et al. Postictal agitation is associated with brain-wide postictal microstructural changes after electroconvulsive therapy-induced seizures. Under review.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdwards LJ, Pine KJ, Ellerbrock I, Weiskopf N, Mohammadi S. NODDI-DTI: Estimating Neurite Orientation and Dispersion Parameters from a Diffusion Tensor in Healthy White Matter. Front Neurosci. 2017;11:720.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJacob Y, Morris LS, Verma G, Rutter SB, Balchandani P, Murrough JW. Altered hippocampus and amygdala subregion connectome hierarchy in major depressive disorder. Translational Psychiatry. 2022;12(1):209.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIto J, Marmarou A, Barz\u0026oacute; P, Fatouros P, Corwin F. Characterization of edema by diffusion-weighted imaging in experimental traumatic brain injury. J Neurosurg. 1996;84(1):97\u0026ndash;103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBriellmann RS, Wellard RM, Jackson GD. Seizure-associated abnormalities in epilepsy: evidence from MR imaging. Epilepsia. 2005;46(5):760\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGorter JA, van Vliet EA, Aronica E, Lopes da Silva FH. Progression of spontaneous seizures after status epilepticus is associated with mossy fibre sprouting and extensive bilateral loss of hilar parvalbumin and somatostatin-immunoreactive neurons. Eur J Neurosci. 2001;13(4):657\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Vliet EA, Aronica E, Gorter JA. Blood-brain barrier dysfunction, seizures and epilepsy. Semin Cell Dev Biol. 2015;38:26\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCano M, Camprodon JA. Understanding the Mechanisms of Action of Electroconvulsive Therapy: Revisiting Neuroinflammatory and Neuroplasticity Hypotheses. JAMA Psychiatry. 2023;80(6):643\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJansson L, Wennstr\u0026ouml;m M, Johanson A, Tingstr\u0026ouml;m A. Glial cell activation in response to electroconvulsive seizures. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2009;33(7):1119\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoef D, Tendolkar I, van Eijndhoven PFP, Hoozemans JJM, Oudega ML, Rozemuller AJM, et al. Electroconvulsive therapy is associated with increased immunoreactivity of neuroplasticity markers in the hippocampus of depressed patients. Transl Psychiatry. 2023;13(1):355.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshayeri Ahmadabad R, Khaleghi Ghadiri M, Gorji A. The role of Toll-like receptor signaling pathways in cerebrovascular disorders: the impact of spreading depolarization. Journal of Neuroinflammation. 2020;17(1):108.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Jager JE, Boesjes R, Roelandt GHJ, Koliaki I, Sommer IEC, Schoevers RA, et al. Shared effects of electroconvulsive shocks and ketamine on neuroplasticity: A systematic review of animal models of depression. Neurosci Biobehav Rev. 2024;164:105796.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNuninga JO, Mandl RCW, Boks MP, Bakker S, Somers M, Heringa SM, et al. Volume increase in the dentate gyrus after electroconvulsive therapy in depressed patients as measured with 7T. Mol Psychiatry. 2020;25(7):1559\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbe Y, Yokoyama K, Kato T, Yagishita S, Tanaka KF, Takamiya A. Neurogenesis-independent mechanisms of MRI-detectable hippocampal volume increase following electroconvulsive stimulation. Neuropsychopharmacology. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadsen TM, Treschow A, Bengzon J, Bolwig TG, Lindvall O, Tingstr\u0026ouml;m A. Increased neurogenesis in a model of electroconvulsive therapy. Biol Psychiatry. 2000;47(12):1043\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWarner-Schmidt JL, Madsen TM, Duman RS. Electroconvulsive seizure restores neurogenesis and hippocampus-dependent fear memory after disruption by irradiation. Eur J Neurosci. 2008;27(6):1485\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFridgeirsson EA, Deng ZD, Denys D, van Waarde JA, van Wingen GA. Electric field strength induced by electroconvulsive therapy is associated with clinical outcome. Neuroimage Clin. 2021;30:102581.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoef D, van Eijndhoven P, van den Munckhof E, Hoogendoorn A, Manten R, Spaans H-P, et al. Pre-treatment predictors of cognitive side-effects after treatment with electroconvulsive therapy in patients with depression: A multicenter study. Journal of Affective Disorders. 2024;349:321\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOltedal L, Bartsch H, S\u0026oslash;rhaug OJ, Kessler U, Abbott C, Dols A, et al. The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy. Neuroimage Clin. 2017;14:422\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamiya K, Hori M, Aoki S. NODDI in clinical research. Journal of Neuroscience Methods. 2020;346:108908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalombo M, Ianus A, Guerreri M, Nunes D, Alexander DC, Shemesh N, et al. SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI. NeuroImage. 2020;215:116835.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchiavi S, Palombo M, Zac\u0026agrave; D, Tazza F, Lapucci C, Castellan L, et al. Mapping tissue microstructure across the human brain on a clinical scanner with soma and neurite density image metrics. Hum Brain Mapp. 2023;44(13):4792\u0026ndash;811.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 1","content":"\n\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electroconvulsive therapy, diffusion tensor imaging, cognitive side-effects, major depression, neuroplasticity","lastPublishedDoi":"10.21203/rs.3.rs-6295387/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6295387/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eElectroconvulsive therapy (ECT) is an effective treatment for major depressive episodes, though its mechanisms remain unclear. Its use is limited due to stigma and possible cognitive side-effects. Repeated magnetic resonance imaging (MRI) could provide further insights into the brain changes associated with ECT’s efficacy and cognitive outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed prospective longitudinal repeated MRI, cognitive, and efficacy data of depressed ECT-patients. Structural and diffusion tensor imaging (DTI) MRI scans were conducted at baseline, directly after initial ECT-sessions, within two weeks after the course and at three months follow-up. Test-retest effects were controlled by including 26 matched healthy controls (\u003cem\u003en\u003c/em\u003e=26). Linear and nonlinear changes in grey matter (GM) volume, white matter (WM) volume, mean diffusivity (MD) and fractional anisotropy (FA) were assessed. Early brain changes were associated with cognitive and efficacy outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the 3\u003csup\u003erd\u003c/sup\u003e ECT-session (\u003cem\u003en\u003c/em\u003e=19), subcortical GM volumes increased, accompanied by right lateralized decrease of MD in those areas. Two weeks post-ECT (\u003cem\u003en\u003c/em\u003e=30), cortical GM volume increased which returned to baseline after three months. In WM, MD linearly increased post-ECT, without widespread FA changes, and MD did not return to baseline after three months (\u003cem\u003en\u003c/em\u003e=30). ECT decreased verbal learning transiently, letter fluency, and animal category fluency tests (\u003cem\u003en\u003c/em\u003e=23, p\u003csub\u003ebonferroni\u003c/sub\u003e = 0.04; \u003cem\u003en=\u003c/em\u003e22, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.04; \u003cem\u003en=\u003c/em\u003e62, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonferroni\u003c/em\u003e\u003c/sub\u003e = 0.02). Early brain changes were not associated with cognitive performance or efficacy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese results suggest that ECT induces rapid changes in brain microstructure and macrostructure. But while macroscopic increases are temporary, microscopic changes in brain structure are longer-lasting.\u003c/p\u003e","manuscriptTitle":"Electroconvulsive therapy induces rapid microstructural and macrostructural changes, but microstructural changes are longer-lasting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-08 20:48:16","doi":"10.21203/rs.3.rs-6295387/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24d3c315-5cee-4304-bc3b-084092427784","owner":[],"postedDate":"May 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":46836476,"name":"Biological sciences/Neuroscience"},{"id":46836477,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-05-08T20:48:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-08 20:48:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6295387","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6295387","identity":"rs-6295387","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}