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Purpose: To describe the current properties and capabilities of an open-source hardware and software package that is being developed by many sites internationally with the aim of providing an inexpensive yet flexible platform for low-cost MRI. Methods: This paper describes three different setups from 50 to 360 mT in different settings, all of which used the MaRCoS console for acquiring data, and different types of software interfaces (custom-built GUI or PulSeq overlay) to acquire the data. Results: Images are presented from both phantoms and in vivo from healthy volunteers to demonstrate the image quality that can be obtained from the MaRCoS hardware/software interfaced to different low-field magnets. Conclusions: The results presented here show that a number of different sequences commonly used in the clinic can be programmed into an open-source system relatively quickly and easily, and can produce good quality images even at this early stage of development. Both the hardware and software will continue to develop, and it is an aim of this paper to encourage other groups to join this international consortium., 9 pages, 10 figures, comments welcome

Every magnetic resonance imaging (MRI) device requires an electronic control system that handles pulse sequences and signal detection and processing. Here we provide details on the architecture and performance of MaRCoS, a MAgnetic Resonance COntrol System developed by an open international community of low-field MRI researchers. MaRCoS is inexpensive and can handle cycle-accurate sequences without hard length limitations, rapid bursts of events, and arbitrary waveforms. It can also be easily adapted to meet further specifications required by the various academic and private institutions participating in its development. We describe the MaRCoS hardware, firmware and software that enable all of the above, including a Python-based graphical user interface for pulse sequence implementation, data processing and image reconstruction., Comment: 10 pages, 4 figures

Objective Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. Methods We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. Results There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from −0.18 to 0.18) and would not survive study-wide correction for multiple testing. Conclusion Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait., Journal of Child Psychology and Psychiatry, 62 (10), ISSN:0021-9630, ISSN:1469-7610

ObjectiveAttention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders.MethodsStructural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures).ResultsWe found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed.ConclusionOur findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders.

Background: Previous magnetic resonance spectroscopic (MRS) studies have reported brain metabolic abnormalities in Major Depressive Disorder (MDD). Nevertheless, results have been inconsistent, focusing on fully developed major depression neglecting first episode patients (FED). Longitudinal studies have also been rare and with short follow-up periods. The aim of the current study was to investigate the differences between healthy controls and first episode patients at baseline, together with changes of metabolites after 1 year follow-up in the ventromedial prefrontal cortex. Methods: H-1-MRS images were obtained from 64 healthy controls and 31 FED patients using a 3T Philips Achieva scanner and processed with TARQUIN software at baseline and after 1 year. Examined metabolites included Glx (corresponding to Glu + Gln-peak), Glu, NAAG, myo-Ins, Cr, GSH and GABA. Clinical improvement was assessed by HDRS-17 scale. Differences in the concentrations of metabolites were evaluated by MANOVA/MANCOVA and GLM repeated measures for longitudinal changes. Results: FED patients had significantly decreased glutamate levels at baseline (p < 0.05) along with significantly elevated GABA (p < 0.01) compared to healthy controls. At the follow up, myo- Ins levels were significantly increased compared to baseline (p < 0.05). Limitations: The limited sample size, together with the unexpectedly high response rate after treatment (83%) might suggest decreased representativeness of the sample. Conclusions: Results indicate glutamatergic and GABAergic changes taking place within the ventromedial prefrontal region even at the early stage of depression prior to any medication treatment.

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research. ENIGMA MDD work is supported by NIH grants U54 EB020403 (Thompson), R01 MH116147 (Thompson), and R01 MH117601 (Jahanshad & Schmaal). LS was supported by an NHMRC Career Development Fellowship (1140764). AFFDIS cohort: this study was funded by the University Medical Center Goettingen (UMG Startfoerderung) and the research team is supported by German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung, BMBF: 01 ZX 1507, “PreNeSt - e:Med”). Barcelona cohort: MJP is funded by the Ministerio de Ciencia e Innovación of the Spanish Government and by the Instituto de Salud Carlos III through a ‘Miguel Servet’ research contract (CP16–0020); National Research Plan (Plan Estatal de I + D + I 2016–2019); and co-financed by the European Regional Development Fund (ERDF). BRC DeCC cohort: CHYF is supported by NIHR BRC. Calgary cohort: supported by Canadian Institutes for Health Research, Branch Out Neurological Foundation. Cardiff cohort: supported by the Medical Research Council (grant G 1100629) and the National Center for Mental Health (NCMH), funded by Health Research Wales (HS/14/20). CLING cohort: this study was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5–1 and GR1950/10–1). CODE cohort: Henrik Walter is supported by a grant of the Deutsche Forschungsgemeinschaft (WA 1539/4–1). The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4–1, SCHN 1205/3–1, SCHR443/11–1). DIP-Groningen cohort: this study was supported by the Gratama Foundation, the Netherlands (2012/35 to NG). Edinburgh cohort: The research leading to these results was supported by IMAGEMEND, which received funding from the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 602450. This paper reflects only the author’s views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z. FOR2107-Marburg cohort: funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7–2 to AK; FOR2107 KI 588/14–2 to TK and FOR2107 JA 1890/7–2 to AJ). Houston cohorts: supported in part by NIMH grant R01 085667 and the Dunn Research Foundation. JCS is supported by the Pat Rutherford, Jr. Endowed Chair in Psychiatry. IMH Study cohort: supported by funding from NHG (SIG/15012) and NMRC CISSP (2018). Melbourne cohort: funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD). Minnesota cohort: the study was funded by the National Institute of Mental Health (K23MH090421; Dr. Cullen) and Biotechnology Research Center (P41 RR008079; Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. Münster cohort: funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). NESDA cohort: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10–000–1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. Pharmo cohort: supported by ERA-NET PRIOMEDCHILD FP 6 (EU) grant 11.32050.26. PSYABM-NORMENT: supported by the Research Council of Norway (project number 229135). The South East Norway Health Authority Research Funding (project number 2015052). The Department of Psychology, University of Oslo, Norway. San Francisco cohort: supported by NIH/NCCIH 1R61AT009864–01A1. NIMH R01MH085734. SHIP and SHIP-trend cohorts: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. Stanford cohorts: this work was supported by NIH grant R37 MH101495. The BiDirect Study was supported by grants from the German Federal Ministry of Education and Research (BMBF; grants FKZ-01ER0816 and FKZ-01ER1506). MDS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. TCH is supported by NIMH grant 5K01MH117442. EJWVS, JL, and TFB are supported by European Research Council grant no. ERC-ADG-2014–671084 INSOMNIA. TFB is supported by a VU University Amsterdam University Research Fellowship 2016–2017. JL is supported by a VU University Amsterdam University Research Fellowship 2017–2018.

Purpose Cushing's syndrome (CS) is an endocrine disorder due to prolonged exposure to cortisol. Recently, microstructural white matter (WM) alterations detected by diffusion tensor imaging (DTI) have been reported in CS patients, and related to depression, but other functional significances. remain otherwise unclear. We aimed at investigating in more depth mood symptoms in CS patients, and how these relate to cognition (information processing speed), and to WM alterations on DTI. Methods The sample comprised 35 CS patients and 35 healthy controls. Beck Depression Inventory-II (BDI-II) was used to measure depressive symptoms, State-Trait Anxiety Inventory (STAI) to assess anxiety, and processing speed was measured by the Symbol Digit Modalities Test (SDMT). DTI studies were acquired using a 3-Tesla Philips-Achieva MR-facility. Voxelwise statistical analysis of fractional anisotropy (FA), mean, axial and radial diffusivities (MD, AD, RD) data were performed using FMRIB Software Library. Correlation analysis were obtained between mood and processing speed variables, and FA, MD, AD and RD values, taking both CS patients and healthy controls. Results Active, controlled and cured CS patients showed greater depression (F = 12.4, p < 0.001), anxious state (F = 4.8, p = 0.005) and anxious trait (F = 9.6, p < 0.001) scores, than controls. Using the entire sample, depression scores correlated negatively to FA and positively to RD values. Although there were no differences in processing speed between groups, SDMT scores correlated positively to both FA and AD values. Conclusions There were greater depressive and anxious symptoms in CS patients than in healthy controls, but no difference in processing speed. However, DTI is related to depression and information processing speed in CS.

Altres ajuts: The ENIGMA-Major Depressive Disorder working group gratefully acknowledges support from the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to PMT) and NIH grant R01 MH116147 (PMT). LS is supported by an NHMRC MRFF Career Development Fellowship (APP1140764). We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. We wish to acknowledge the patients and control subjects that have particiaped int the study. We thank Rosa Schirmer, Elke Schreiter, Reinhold Borschke and Ines Eidner for image acquisition and data preparation, and Anna Oliynyk for quality checks. We thank Dorothee P. Auer and F. Holsboer for initiation of the RUD study. NESDA: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. M-JvT was supported by a VENI grant (NWO grant number 016.156.077). UCSF: This work was supported by the Brain and Behavior Research Foundation (formerly NARSAD) to TTY; the National Institute of Mental Health (R01MH085734 to TTY; K01MH117442 to TCH) and by the American Foundation for Suicide Prevention (PDF-1-064-13) to TCH. Stanford: This work was supported by NIMH Grants R01MH59259 and R37101495 to IHG. MS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. Muenster: This work was funded by the German Research Foundation (SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). Marburg: This work was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5-1 and DA1151/5-2 to UD; KI 588/ 14-1, KI 588/14-2 to TK; KR 3822/7-1, KR 3822/7-2 to AK; JA 1890/ 7-1, JA 1890/7-2 to AJ). IMH-MDD: This work was supported by the National Healthcare Group Research Grant (SIG/15012) awarded to KS. Barcelona: This study was funded by two grants of the Fondo de Investigación Sanitaria from the Instituto de Salud Carlos III, by the Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM). The author is funded through 'Miguel Servet' research contract (CP16-0020), co-financed by the European Regional Development Fund (ERDF) (2016-2019). QTIM: We thank the twins and singleton siblings who gave generously of their time to participate in the QTIM study. We also thank the many research assistants, radiographers, and IT support staff for data acquisition and DNA sample preparation. This study was funded by White matter disturbances in major depressive disorder: a coordinated analysis across 20 international. . . 1521 the National Institute of Child Health & Human Development (RO1 HD050735); National Institute of Biomedical Imaging and Bioengineering (Award 1U54EB020403-01, Subaward 56929223); National Health and Medical Research Council, Australia (Project Grants 496682, 1009064). NIH ENIGMA-BD2K U54 EB020403 (Thompson); R01 MH117601 (Jahanshad/Schmaal). Magdeburg: M.L. and M.W. are funded by SFB 779. Bipolar Family Study: This study has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013). This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award (104036/Z/14/Z). Minnesota Adolescent Depression Study: The study was funded by the National Institute of Mental Health (K23MH090421), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, the Minnesota Medical Foundation, and the Biotechnology Research Center (P41 RR008079 to the Center for Magnetic Resonance Research), University of Minnesota, and the Deborah E. Powell Center for Women's Health Seed Grant, University of Minnesota. Dublin: This study was supported by Science Foundation Ireland through a Stokes Professorhip grant to TF. MPIP: The MPIP Sample comprises patients included in the Recurrent Unipolar Depression (RUD) Case-Control study at the clinic of the Max Planck Institute of Psychiatry, Munich, German. The RUD study was supported by GlaxoSmithKline. Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

Objective: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects.Methods: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T-1-weighted MRI data were processedwith a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1.Results: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset.Conclusions: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases.

[EN] Background: Diagnostic Task Force Criteria (TFC) for arrhythmogenic cardiomyopathy (AC) exhibit poor performance for left dominant forms. TFC only include right ventricular (RV) dysfunction (akinesia, dyssynchrony, volumes and ejection fraction). Moreover, cardiac magnetic resonance imaging (CMRI) assessment of left ventricular (LV) dyssynchrony has hitherto not been described. Thus, we aimed to comprehensively characterize LVCMRI behavior in AC patients. Methods: Thirty-five AC patients with LV involvement and twenty-three non-affected family members (controls) were enrolled. Feature-tracking analysis was applied to cine CMRI to assess LV ejection fraction (LVEF), LV end-systolic and end-diastolic volume indexes, strain values and dyssynchrony. Regions with more frequent strain and dyssynchrony impairment were also studied. Results: Radial dyssynchrony and LVEF were selected (sensitivities 54.3% and 48.6%, respectively at 100% specificity), with a threshold of 70 ms for radial dyssynchrony and 48.5% for LVEF. 71.4% of patients exceeded these thresholds (31.4% both, 22.9% only dyssynchrony and 17.1% only LVEF). Considering these cut-off values as a novel combined criterion, 30% of patients with 'borderline' or 'possible' AC following 2010 TFC would move to a 'definite' AC diagnosis. Strain was globally impaired whereas dyssynchronous regions were more often apical and located at the inferolateral wall. Conclusions: Mirroring the RV evaluation, we suggest including LVEF and LV dyssynchrony to improve the diagnosis of AC. Two independent mechanisms can be claimed in AC patients with LV involvement: 1) decreased myocardial deformation with global LV affectation and 2) delayed myocardial contraction at localized regions., This work was supported by grants from the "Ministerio de Economia y Competitividad" [DPI2015-70821-R], "Instituto de Salud Carlos III" and FEDER "Union Europea, Una forma de hacer Europa" [RD12/0042/0029, PI14/01477, PI18/01582 and La Fe Biobank PT17/0015/0043].

Contains fulltext : 204879pub.pdf (Publisher’s version ) (Open Access) Contains fulltext : 204879pos.pdf (Author’s version postprint ) (Open Access) OBJECTIVE: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. METHODS: Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). RESULTS: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. CONCLUSIONS: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Background: Major depressive disorder (MDD) is accompanied by atypical brain structure affecting grey and white matter from the early stages. Neuroimaging studies of first-episode depression (FED) have provided evidence on this regard, but most of the studies are cross-sectional. The aim of this longitudinal study was to test potential changes in grey matter (GM) and white matter (WM) volumes in FED. Methods: Thirty-three untreated FED patients (DSM-IV criteria) and 33 healthy controls (HC) underwent a 3T structural magnetic resonance imaging (sMRI) at baseline and after 2 years. Depressive symptoms were assessed at baseline and throughout the study with the 17-item Hamilton Depressive Rating Scale (HDRS-17). Recurrences of FED patients were also collected along the follow-up. To analyze GM and WM differences, whole-brain voxel-based morphometry (VBM, SPM12) was employed (FWE corrected). Results: FED patients showed significant reductions compared to HC in WM volumes of prefrontal cortex (left anterior corona radiata). No differences were found in GM volumes. Full factorial longitudinal analysis of the whole sample revealed no significant effect in GM nor in WM, while the full factorial longitudinal analysis comparing recurrent and non-recurrent patients showed increments in WM volumes of left posterior corona radiata and right posterior thalamic radiation in the recurrent group. Limitations: Limited sample size, especially in the follow-up. Conclusions: The present findings provided some new evidence of the role of white matter alterations in the early stages of MDD and in the progression of the illness.

BACKGROUND: Despite its high recurrence rate, major depression disorder (MDD) still lacks neurobiological markers to optimize treatment selection. The aim of this study was to examine the prognostic potential of clinical and structural magnetic resonance imaging (sMRI) in the long-term MDD clinical outcomes (COs). METHODS: Forty-nine MDD patients were grouped into one of four different CO categories according to their trajectory: recovery, partial remission, remission recurrence, and chronic depression. Regression models including baseline demographic, clinical, and sMRI data were used for predicting patients' COs and symptom severity 5 years later. RESULTS: The model including only clinical data explained 32.4% of the variance in COs and 55% in HDRS, whereas the model combining clinical and sMRI data increased up to 52/68%, respectively. A bigger volume of right anterior cingulate gyrus was the variable that best predicted COs. CONCLUSIONS: The findings suggest that the addition of sMRI brain data to clinical information in depressive patients can significantly improve the prediction of their COs. The dorsal part of the right anterior cingulate gyrus may act as a potential biomarker of long-term clinical trajectories.© 2016 Wiley Periodicals, Inc. Language: en

[EN] Background and objective: A heterogenous expression characterizes arrhythmogenic cardiomyopathy (AC). The evaluation of regional wall movement included in the current Task Force Criteria is only qualitative and restricted to the right ventricle. However, a strain-based approach could precisely quantify myocardial deformation in both ventricles. We aim to define and modelize the strain behavior of the left ventricle in AC patients with left ventricular (LV) involvement by applying algorithms such as Principal Component Analysis (PCA), clustering and naive Bayes (NB) classifiers. Methods: Thirty-six AC patients with LV involvement and twenty-three non-affected family members (controls) were enrolled. Feature-tracking analysis was applied to cine cardiac magnetic resonance imaging to assess strain time series from a 3D approach, to which PCA was applied. A Two-Step clustering algorithm separated the patients' group into clusters according to their level of LV strain impairment. A statistical characterization between controls and the new AC subgroups was done. Finally, a NB classifier was built and new data from a small evolutive dataset was predicted. Results: 60% of AC-LV patients showed mildly affected strain and 40% severely affected strain. Both groups and controls exhibited statistically significant differences, especially when comparing controls and severely affected AC-LV patients. The classification accuracy of the strain NB classifier reached 82.76%. The model performance was as good as to classify the individuals with a 100% sensitivity and specificity for severely impaired strain patients, 85.7% and 81.1% for mildly impaired strain patients, and 69.9% and 91.4% for normal strain, respectively. Even when the severely affected LV-AC group was excluded, LV strain showed a good accuracy to differentiate patients and controls. The prediction of the evolutive dataset revealed a progressive alteration of strain in time. Conclusions: Our LV strain classification model may help to identify AC patients with LV involvement, at least in a setting of a high pretest probability, such as family screening., This work was supported by grants from the "Ministerio de Economia y Competitividad"[DPI2015-70821-R], "Instituto de Salud Carlos III " and FEDER "Union Europea, Una forma de hacer Europa"[PI14/01477, PI15/00748, PI18/01582, CIBERCV] and La Fe Biobank [PT17/0 015/0043].

Arrhythmogenic cardiomyopathy (AC) is an inherited rare disease that can cause sudden cardiac death. Due to its heterogeneous phenotipe, a compendium of criteria collected in a Task Force Criteria (TFC) have to be met for its diagnosis, being dysshynchrony one of those criteria. The classical form of the disease involves the right ventricle, while the left ventricle AC (AC-LV) has been less studied. We aim to study dyssynchrony in AC-LV patients. The sample consisted of 36 subjects diagnosed with AC-LV and 23 non-affected relatives who were non-carriers of the pathogenic mutation of the proband. From each individual, radial, circumferential and longitudinal strain were obtained in the 16 AHA segments of the myocardium and dyssynchrony was calculated as the standard deviation of the time-to-peak strain. LV ejection fraction (LVEF) was also obtained. Finally, a clustering algorithm was applied to the 3-axis dyssynchronies and the LVEF. The clustering algorithm performed well (silhouette = 0.6) and detected 2 clusters (cluster1 = 23 controls + 19 AC-LV patients and cluster2 = 17 AC-LV patients). Radial dyssynchrony was the feature with the higher predictor importance. In conclusion, 47% of AC-LV patients present impaired dyssynchrony. Radial dyssynchrony was the most affected parameter among all dyssynchronies and LVEF.

BACKGROUND AND PURPOSE: The role of juxtacortical lesions in brain volume loss in multiple sclerosis has not been fully clarified. The aim of this study was to explore the role of juxtacortical lesions on cortical atrophy and to investigate whether the presence of juxtacortical lesions is related to local cortical thinning in the early stages of MS. MATERIALS AND METHODS: A total of 131 patients with clinically isolated syndrome or with relapsing-remitting MS were scanned on a 3T system. Patients with clinically isolated syndrome were classified into 3 groups based on the presence and topography of brain lesions: no lesions (n = 24), only non–juxtacortical lesions (n = 33), and juxtacortical lesions and non–juxtacortical lesions (n = 34). Patients with relapsing-remitting MS were classified into 2 groups: only non–juxtacortical lesions (n = 10) and with non–juxtacortical lesions and juxtacortical lesions (n = 30). A juxtacortical lesion probability map was generated, and cortical thickness was measured by using FreeSurfer. RESULTS: Juxtacortical lesion volume in relapsing-remitting MS was double that of patients with clinically isolated syndrome. The insula showed the highest density of juxtacortical lesions, followed by the temporal, parietal, frontal, and occipital lobes. Patients with relapsing-remitting MS with juxtacortical lesions showed significantly thinner cortices overall and in the parietal and temporal lobes compared with those with clinically isolated syndrome with normal brain MR imaging. The volume of subcortical structures (thalamus, pallidum, putamen, and accumbens) was significantly decreased in relapsing-remitting MS with juxtacortical lesions compared with clinically isolated syndrome with normal brain MR imaging. The spatial distribution of juxtacortical lesions was not found to overlap with areas of cortical thinning. CONCLUSIONS: Cortical thinning and subcortical gray matter volume loss in patients with a clinically isolated syndrome or relapsing-remitting MS was related to the presence of juxtacortical lesions, though the cortical areas with the most marked thinning did not correspond to those with the largest number of juxtacortical lesions.

Contains fulltext : 169834.pdf (Publisher’s version ) (Open Access) Contains fulltext : 169834pos.pdf (Author’s version postprint ) (Open Access) BACKGROUND: Neuroimaging studies have shown structural alterations in several brain regions in children and adults with attention deficit hyperactivity disorder (ADHD). Through the formation of the international ENIGMA ADHD Working Group, we aimed to address weaknesses of previous imaging studies and meta-analyses, namely inadequate sample size and methodological heterogeneity. We aimed to investigate whether there are structural differences in children and adults with ADHD compared with those without this diagnosis. METHODS: In this cross-sectional mega-analysis, we used the data from the international ENIGMA Working Group collaboration, which in the present analysis was frozen at Feb 8, 2015. Individual sites analysed structural T1-weighted MRI brain scans with harmonised protocols of individuals with ADHD compared with those who do not have this diagnosis. Our primary outcome was to assess case-control differences in subcortical structures and intracranial volume through pooling of all individual data from all cohorts in this collaboration. For this analysis, p values were significant at the false discovery rate corrected threshold of p=0.0156. FINDINGS: Our sample comprised 1713 participants with ADHD and 1529 controls from 23 sites with a median age of 14 years (range 4-63 years). The volumes of the accumbens (Cohen's d=-0.15), amygdala (d=-0.19), caudate (d=-0.11), hippocampus (d=-0.11), putamen (d=-0.14), and intracranial volume (d=-0.10) were smaller in individuals with ADHD compared with controls in the mega-analysis. There was no difference in volume size in the pallidum (p=0.95) and thalamus (p=0.39) between people with ADHD and controls. Exploratory lifespan modelling suggested a delay of maturation and a delay of degeneration, as effect sizes were highest in most subgroups of children (21 years): in the accumbens (Cohen's d=-0.19 vs -0.10), amygdala (d=-0.18 vs -0.14), caudate (d=-0.13 vs -0.07), hippocampus (d=-0.12 vs -0.06), putamen (d=-0.18 vs -0.08), and intracranial volume (d=-0.14 vs 0.01). There was no difference between children and adults for the pallidum (p=0.79) or thalamus (p=0.89). Case-control differences in adults were non-significant (all p>0.03). Psychostimulant medication use (all p>0.15) or symptom scores (all p>0.02) did not influence results, nor did the presence of comorbid psychiatric disorders (all p>0.5). INTERPRETATION: With the largest dataset to date, we add new knowledge about bilateral amygdala, accumbens, and hippocampus reductions in ADHD. We extend the brain maturation delay theory for ADHD to include subcortical structures and refute medication effects on brain volume suggested by earlier meta-analyses. Lifespan analyses suggest that, in the absence of well powered longitudinal studies, the ENIGMA cross-sectional sample across six decades of ages provides a means to generate hypotheses about lifespan trajectories in brain phenotypes. FUNDING: National Institutes of Health. 10 p.

The aim of this study is to analyze the differences in low frequency fluctuation (LFF) values between schizophrenia patients with and without auditory verbal hallucinations (AVH). Nineteen schizophrenia patients with persistent AVH (HP), fourteen non-hallucinating schizophrenia patients (nHP) and twenty healthy controls (HC) underwent R-fMRI. LFF values were calculated in the slow frequency band (0.01-0.08 Hz). By means of group level contrasts, we performed direct voxel-wise group comparisons. Both groups of patients showed decreased amplitude LFF (ALFF) values in the occipital pole and lingual gyrus compared to HC, whereas increased ALFF values were found in the temporal pole and fusifom gyrus. Schizophrenia patients exhibited decreased fractional ALFF (fALFF) values in the precuneus, occipital pole and bilateral occipital cortex, and increased fALFF in the insula compared to HC. There were also differences between patients with and without AVH. (Ok to start with lower case?) fALFF values were higher in the putamen and insular cortex and lower in the frontal pole in HP compared to nHP and HC. ALFF increased in HP patients in the bilateral thalamus and bilateral parahippocampal gyrus, compared to nHP patients and HC. Our results suggest that altered dynamics in low-frequency fluctuations may play a key role in the neurophysiology of auditory hallucinations. (C) 2017 Elsevier B.V. All rights reserved.

ObjectiveCushing's syndrome (CS) is associated with neuropsychological deficits. As the cerebellum plays a key role in neuropsychological functions it may be affected in CS. The aim of this study was to investigate whether patients with CS have a smaller cerebellar volume than healthy controls, and to analyse whether cerebellar volume is associated with neuropsychological performance and clinical parameters.DesignA cross-sectional study was performed.MethodsThirty-six CS patients (15 with active CS and 21 with CS in remission) and 36 controls matched for age, sex, and education underwent neuropsychological testing, quality of life assessment, clinical evaluation, and magnetic resonance imaging brain scan. Cerebellar volumes (white matter and cortex, bilateral) were calculated using FreeSurfer Software.ResultsPatients with active CS showed smaller bilateral cerebellar cortex volumes than controls (left,P=0.035 and right,P=0.034), as well as a trend toward smaller right cerebellar cortex volumes than patients in remission CS (P=0.051). No differences were observed in the volume of cerebellar white matter between the three groups. Both right and left cerebellar cortex volumes correlated negatively with triglyceride levels (right:r=−0.358,P=0.002 and left:r=−0.317,P=0.005) and age at diagnosis (right:r=−0.433,P=0.008 and left:r=−0.457,P=0.005). Left cerebellar cortex volume also correlated positively with visual memory performance (r=0.245,P=0.038). Right cerebellar cortex volume positively correlated with quality-of-life scores (r=0.468,P=0.004).ConclusionsThe cerebellar cortex volume is smaller in active CS patients than in controls. This finding is associated with poor visual memory and quality of life and is mostly pronounced in patients with higher triglyceride levels and older age at diagnosis.

A scheme to significantly speed up the processing of MRI with FreeSurfer (FS) is presented. The scheme is aimed at maximizing the productivity (number of subjects processed per unit time) for the use case of research projects with datasets involving many acquisitions. The scheme combines the already existing GPU-accelerated version of the FS workflow with a task-level parallel scheme supervised by a resource scheduler. This allows for an optimum utilization of the computational power of a given hardware platform while avoiding problems with shortages of platform resources. The scheme can be executed on a wide variety of platforms, as its implementation only involves the script that orchestrates the execution of the workflow components and the FS code itself requires no modifications. The scheme has been implemented and tested on a commodity platform within the reach of most research groups (a personal computer with four cores and an NVIDIA GeForce 480 GTX graphics card). Using the scheduled task-level parallel scheme, a productivity above 0.6 subjects per hour is achieved on the test platform, corresponding to a speedup of over six times compared to the default CPU-only serial FS workflow.

The early, preferably pre-clinical, identification of neurodegenerative diseases is important as treatment will be most successful before substantial neuronal loss. Here, we reasoned that functional brain changes as measured using functional magnetic resonance imaging (fMRI) will precede neurodegeneration. Three independent cohorts of patients with the genetic mutation leading to Huntington's Disease (HD) but without any clinical symptoms and matched controls performed three different fMRI tasks: Sequential finger tapping engaged the motor system, which is primarily affected by HD, whereas a working-memory task and a task aiming to induce irritation represented the range of low- and high-level cognitive functions also affected by HD. Each diagnostic group of every cohort included 11-16 subjects. After segmentation into 76 cortical and 14 subcortical regions, we extracted functional connectivity patterns through pairwise correlation between the signals in the regions. The resulting coefficients were directly embedded as input to a pattern classifier aiming to separate controls from gene mutation carriers. Alternatively, graph-theory measures such as degree and clustering coefficient were used as features for the discrimination. Classification accuracy never outperformed the accuracy of a grouping based on parameter estimates from a general-linear model approach or a grouping based on features extracted from anatomical images as reported in a previous analysis. Despite good within-subject stability between two runs of the same task, a high between-subject variability led to chance-level accuracy. These results indicate that standard graph-metrics are insufficient to detect subtle disease related changes when within-group variability is high. Developing methods that reduce variability related to noise should be the focus of future studies.

BackgroundFindings of brain structural changes in major depressive disorder are still inconsistent, partly because some crucial clinical variables have not been taken into account.AimsTo investigate the effect of major depressive disorder on grey matter volumes.MethodVoxel-based morphometry was used to compare 66 patients with depression at different illness stages (22 each with first-episode, remitted-recurrent and treatment resistant/chronic depression) with 32 healthy controls. Brain volumes were correlated with clinical variables.ResultsVoxel-based morphometry showed a significant group effect in right superior frontal gyrus, left medial frontal gyrus and left cingulate gyrus (PConclusionsFrontotemporolimbic areas are smaller in the patients with severe depression and are associated with duration of illness, but not with medication patterns, suggesting negative effects of long-lasting major depressive disorder on grey matter.

FKBP5 encodes a co-chaperone of HSP90 protein that regulates intracellular glucocorticoid receptor sensitivity. When it is bound to the glucocorticoid receptor complex, cortisol binds with lower affinity to glucocorticoid receptor. Cushing’s syndrome is associated with memory deficits, smaller hippocampal volumes, and wide range of cognitive impairments. We aimed at evaluating blood DNA methylation of FKBP5 and its relationship with memory and hippocampal volumes in Cushing’s syndrome patients. Polymorphism rs1360780 in FKBP5 has also been assessed to determine whether genetic variations can also govern CpG methylation. Thirty-two Cushing’s syndrome patients and 32 matched controls underwent memory tests, 3-Tesla MRI of the brain, and DNA extraction from total leukocytes. DNA samples were bisulfite treated, PCR amplified, and pyrosequenced to assess a total of 41CpG-dinucleotides in the introns 1, 2, 5, and 7 of FKBP5. Significantly lower intronic FKBP5 DNA methylation in CS patients compared to controls was observed in ten CpG-dinucleotides. DNA methylation at these CpGs correlated with left and right HV (Intron-2-Region-2-CpG-3: LHV, r = 0.73, p = 0.02; RHV, r = 0.58, p = 0.03). Cured and active CS patients showed both lower methylation of intron 2 (92.37, 91.8, and 93.34 %, respectively, p = 0.03 for both) and of intron 7 (77.08, 73.74, and 79.71 %, respectively, p = 0.02 and p < 0.01) than controls. Twenty-two subjects had the CC genotype, 34 had the TC genotype, and eight had the TT genotype. Lower average DNA methylation in intron 7 was observed in the TT subjects compared to CC (72.5vs. 79.5 %, p = 0.02) and to TC (72.5 vs. 79.0 %, p = 0.03). Our data demonstrate, for the first time, a reduction of intronic DNA methylation of FKBP5 in CS patients.

Chronic exposure to excessive glucocorticoid (GC) concentration in Cushing's syndrome (CS) can affect the brain structurally and functionally; ventromedial prefrontal cortex (vmPFC) is rich in GC receptors and therefore particularly vulnerable to excessive GC concentration. Proton magnetic resonance spectroscopy (H-1-MRS) is a sensitive, non-invasive imaging technique that provides information on brain metabolites in vivo. Our aim was to investigate metabolite concentrations in vmPFC of CS patients and their relationship with clinical outcome. Twenty-two right-handed CS patients (7 active/15 in remission, 19 females, 41.6 +/- 12.3 years) and 22 right-handed healthy controls (14 females, 41.7 +/- 11 years) underwent brain MRI and H-1-MRS exams at 3 Tesla. Concentrations of glutamate (Glu), glutamate + glutamine (Glx), creatine (Cr), N-Acetyl-aspartate (NAA), N-Acetyl-aspartate + N-acetylaspartylglutamate (total NAA), choline-containing compounds (Cho) and myoinositol (MI) were determined. Moreover, anxiety and depressive symptoms were evaluated with the State-Trait Anxiety Inventory (STAI) and the Beck Depression Inventory-II (BDI-II) test, respectively. CS patients had lower concentrations of glutamate and total NAA in the vmPFC than healthy controls (8.6 +/- 1.2 vs. 9.3 +/- 0.7 mmol/L, and 6.4 +/- 0.8 vs. 6.8 +/- 0.4 mmol/L, respectively; p < 0.05). Duration of hypercortisolism was negatively correlated with total NAA (r = -0.488, p < 0.05). Moreover, the concentration of total NAA was negatively correlated with anxiety state (r = -0.359, p < 0.05). Brain metabolites are abnormal in the vmPFC of patients with CS. Decreased total NAA and glutamate concentrations indicate neuronal dysfunction that appear to be related with duration of hypercortisolism and anxiety.

An automated procedure for modeling the radiated emissions of electronic devices is presented in this paper. The principle of the model is to replace the device by a set of electric dipoles defined by their positions, orientations, lengths, and currents. Thus, this modeling procedure aims to determine the number of dipoles and their parameters with a minimum user intervention. The procedure is divided into three parts: the near-field measurements of the tangential components of the magnetic field, an image processing to obtain the number of sources of the model, and the application of an optimization algorithm in order to obtain the different parameters of the model, such as the current and the position of each source.

In this paper, a simple method to obtain the equivalent radiation emitting sources of an electronic circuit using the near-field scanning method is presented. The model is based on a set of elemental dipoles that substitutes the electronic circuit and radiates the same magnetic field. Two different approaches are presented: a set of electric dipoles and a set of magnetic dipoles. In order to build the model, both the magnitude and phase of the magnetic field are required. These measurements are carried out using the "near-field scanning method," and two procedures are presented: using the vector network analyzer and the spectrum analyzer. Finally, the model is applied to two different cases: to obtain the radiated near-field of a component (microcontroller) and to obtain the field of a complete electronic board.

Despite its high recurrence rate, major depression disorder (MDD) still lacks neurobiological markers to optimize treatment selection. The aim of this study was to examine the prognostic potential of clinical and structural magnetic resonance imaging (sMRI) in the long-term MDD clinical outcomes (COs).Forty-nine MDD patients were grouped into one of four different CO categories according to their trajectory: recovery, partial remission, remission recurrence, and chronic depression. Regression models including baseline demographic, clinical, and sMRI data were used for predicting patients' COs and symptom severity 5 years later.The model including only clinical data explained 32.4% of the variance in COs and 55% in HDRS, whereas the model combining clinical and sMRI data increased up to 52/68%, respectively. A bigger volume of right anterior cingulate gyrus was the variable that best predicted COs.The findings suggest that the addition of sMRI brain data to clinical information in depressive patients can significantly improve the prediction of their COs. The dorsal part of the right anterior cingulate gyrus may act as a potential biomarker of long-term clinical trajectories.

ObjectiveCushing's syndrome (CS) is associated with high cardiovascular risk. White matter lesions (WML) are common on brain magnetic resonance imaging (MRI) in patients with increased cardiovascular risk.AimTo investigate the relationship between cardiovascular risk, WML, neuropsychological performance and brain volume in CS.Design/methodsThirty-eight patients with CS (23 in remission, 15 active) and 38 controls sex-, age- and education-level matched underwent a neuropsychological and clinical evaluation, blood and urine tests and 3Tesla brain MRI. WML were analysed with the Scheltens scale. Ten-year cardiovascular risk (10CVR) and vascular age (VA) were calculated according to an algorithm based on the Framingham heart study.ResultsPatients in remission had a higher degree of WML than controls and active patients (PP=0.008 respectively), which did not correlate with cognitive performance in any group. WML severity positively correlated with diastolic blood pressure (r=0.659,P=0.001) and duration of hypertension (r=0.478,P=0.021) in patients in remission. Both patient groups (active and in remission) had higher 10CVR (P=0.030,P=0.041) and VA than controls (P=0.013,P=0.039). Neither the 10CVR nor the VA correlated with WML, although both negatively correlated with cognitive function and brain volume in patients in remission (PTotal brain volume and grey matter volume in both CS patient groups were reduced compared to controls (total volume: activeP=0.006, in remissionP=0.012; grey matter: activeP=0.001, in remissionP=0.003), with no differences in white matter volume between groups.ConclusionsPatients in remission of Cushing's syndrome (but not active patients) have more severe white matter lesions than controls, positively correlated with diastolic pressure and duration of hypertension. Ten-year cardiovascular risk and vascular age appear to be negatively correlated with the cognitive function and brain volume in patients in remission of Cushing's syndrome.

The habenula (Hb) can play an important role in major depressive disorder (MDD) as it is a key node between fronto-limbic areas and midbrain monoaminergic structures. In vivo neuroimaging studies have shown reductions in Hb volume in a post-mortem sample of patients with affective disorders but findings in unipolar MDD are not consistent. The current study aimed to investigate whether the Hb volume differed between patients with different stages of unipolar MDD and healthy subjects. We also explored differences in grey (GM) and white matter (WM) volumes and potential age and gender effects. High-resolution images were acquired using a 3T-scanner from 95 participants (21 with first-episode MDD; 20 with remitted-recurrent MDD; 20 with treatment-resistant/chronic MDD; and 34 healthy controls).Two researchers blinded to clinical data manually delineated habenular nuclei, with excellent inter-rater agreement. Multivariate analysis of covariance revealed a significant group-by-gender interaction (F9,258=2.22; p=0.02). Univariate effects emerged for Hb-WM volumes (F3,86=3.12; p=0.03) but not for total Hb volumes (F3,86=0.59; p=0.62) or Hb-GM volumes (F3,86=2.01; p=0.12). Women with a first-episode MDD had greater Hb-WM volumes than healthy controls and patients with treatment-resistant/chronic MDD (p

BACKGROUND AND PURPOSE: Cushing syndrome appears after chronic exposure to elevated glucocorticoid levels. Cortisol excess may alter white matter microstructure. Our purpose was to study WM changes in patients with Cushing syndrome compared with controls by using DTI and the influence of hypercortisolism. MATERIALS AND METHODS: Thirty-five patients with Cushing syndrome and 35 healthy controls, matched for age, education, and sex, were analyzed through DTI (tract-based spatial statistics) for fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity (general linear model, family-wise error, and threshold-free cluster enhancement corrections, P < .05). Furthermore, the influence of hypercortisolism on WM DTI changes was studied by comparing 4 subgroups: 8 patients with Cushing syndrome with active hypercortisolism, 7 with Cushing syndrome with medication-remitted cortisol, 20 surgically cured, and 35 controls. Cardiovascular risk factors were used as covariates. In addition, correlations were analyzed among DTI values, concomitant 24-hour urinary free cortisol levels, and disease duration. RESULTS: There were widespread alterations (reduced fractional anisotropy, and increased mean diffusivity, axial diffusivity, and radial diffusivity values; P < .05) in patients with Cushing syndrome compared with controls, independent of the cardiovascular risk factors present. Both active and cured Cushing syndrome subgroups showed similar changes compared with controls. Patients with medically remitted Cushing syndrome also had reduced fractional anisotropy and increased mean diffusivity and radial diffusivity values, compared with controls. No correlations were found between DTI maps and 24-hour urinary free cortisol levels or with disease duration. CONCLUSIONS: Diffuse WM alterations in patients with Cushing syndrome suggest underlying loss of WM integrity and demyelination. Once present, they seem to be independent of concomitant hypercortisolism, persisting after remission/cure.

BackgroundAlthough white-matter abnormalities have been reported in middle-aged patients with major depressive disorder (MDD), few data are available on treatment-resistant MDD and the influence of relevant variables related to clinical burden of illness is far from being well established.MethodThe present study examined white-matter microstructure in a sample of 52 patients with MDD in different stages (treatment-resistant/chronic MDD, n = 18; remitted-recurrent MDD, n = 15; first-episode MDD, n = 19) and 17 healthy controls, using diffusion tensor imaging with a tract-based spatial statistics approach. Groups were comparable in age and gender distribution, and results were corrected for familywise error (FWE) rate.ResultsWidespread significant reductions of fractional anisotropy (FA) – including the cingulum, corpus callosum, superior and inferior longitudinal fascicule – were evident in treatment-resistant/chronic MDD compared with first-episode MDD and controls (p p β = –0.49, p = 0.04) and higher depression severity (at a trend level: β = –0.26, p = 0.06) predicted lower FA in linear multiple regression analysis at the whole-brain level. The number of previous episodes and severity of symptoms were significant predictors when focused on the ventromedial prefrontal area (β = −0.28, p = 0.04; and β = −0.29, p = 0.03, respectively). Medication effects were controlled for in the analyses and results remained unaltered.ConclusionsOur findings support the notion that disruptions of white-matter microstructure, particularly in fronto-limbic networks, are associated with resistance to treatment and higher current and past burden of depression.

Methylphenidate (MPH) is the first choice of medical treatment for attention-deficit/hyperactivity disorder (ADHD). Its mechanism of action is to inhibit the reuptake of dopamine and noradrenaline mainly in the region of the striatum. It has been estimated that 10–30 % of patients with ADHD do not respond adequately to MPH. The aim of this study was to evaluate whether striatal differences exist between good and poor responders to MPH. The sample included 27 treatment-naive children with ADHD between the ages of 6 and 14. MPH administration started 1 day after the MRI acquisition. After a month, psychiatrists established the good or poor response to treatment according to clinical criteria. MRI images were analyzed using a technique based on regions of interest applied specifically to the caudate and accumbens nuclei. Sixteen patients showed good response to MPH and 11 a poor one. Regions of interest analysis showed that good responders had a higher concentration of gray matter in the head of both caudate nuclei and the right nucleus accumbens. Furthermore, a significant correlation was found between caudate and accumbens nuclei volume and the Conners’ Parent Rating Scale and Continuous Performance Test improvement. These results support the hypothesis of the involvement of the caudate and accumbens nuclei in MPH response and in ADHD pathophysiology.

SummaryBackground Proton magnetic resonance spectroscopy (1H-MRS) is a sensitive, noninvasive imaging technique capable of measuring brain metabolites in vivo. Chronic exposure to endogenous hypercortisolism in Cushing's syndrome (CS) is associated with negative effects on memory and hippocampal volumes, even after biochemical cure. Objective To investigate metabolites in the hippocampi of CS patients and controls, using 1H-MRS. Patients and methods Eighteen right-handed cured CS patients (age 44·8 ± 12·5 years, 12·6 ± 3·8 years of education) and 18 right-handed healthy controls, matched for age (40·0 ± 11·9) and years of education (14·4 ± 3·8), underwent 3-Tesla magnetic resonance imaging (3T MRI) and 1H-MRS including the head of each hippocampus. Concentrations of Glu (Glutamate), Glx (Glutamate + Glutamine), NAA (N-Acetyl-aspartate), total NAA (N-Acetyl-aspartate + N-Acetyl-aspartyl-Glutamate), Cho (Glycerophosphocholine and Phosphocholine compounds), Cr (Creatine) and MI (mionositol) were measured (mmol/l). Hippocampal volumes (mm3) were additionally calculated using an automated procedure (FreeSurfer). Results CS patients had lower NAA than controls in the left and right hippocampus (5·2 ± 1·0 vs 6·1 ± 0·7, P

Parkinson's disease (PD) has broadly been associated with mild cognitive impairment (PDMCI) and dementia (PDD). Researchers have studied surrogate, neuroanatomic biomarkers provided by magnetic resonance imaging (MRI) that may help in the early diagnosis of this condition. In this article, four classification models (naive Bayes, multivariate filter-based nave Bayes, filter selective naive Bayes and support vector machines, SVM) have been applied to evaluate their capacity to discriminate between cognitively intact patients with Parkinson's disease (PDCI), PDMCI and PDD. For this purpose, the MRI studies of 45 subjects (16 PDCI, 15 PDMCI and 14 PDD) were acquired and post-processed with Freesurfer, obtaining 112 variables (volumes of subcortical structures and thickness of cortical parcels) per subject. A multivariate filter-based naive Bayes model was found to be the best classifier, having the highest cross-validated sensitivity, specificity and accuracy. Additionally, the most relevant variables related to dementia in PD, as predicted by our classifiers, were cerebral white matter, and volumes of the lateral ventricles and hippocampi. (C) 2012 Elsevier Ireland Ltd. All rights reserved.