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OBJECTIVE: Rett syndrome (RTT) is characterized by neurological regression. This pioneering study investigated the effect of age on brain volume reduction by analyzing magnetic resonance imaging findings in participants with RTT, ranging from toddlers to adults. METHODS: Functional evaluation and neuroimaging were performed. All scans were acquired using a Siemens Tim Trio 3 T scanner with a 32-channel head coil. RESULTS: The total intracranial volume and cerebral white matter volume significantly increased with age in the control group compared with that in the RTT group (p < 0.05). Cortical gray matter volume reduction in the RTT group continued to increase in bilateral parietal lobes and left occipital lobes (p < 0.05). The differences in cortical gray matter volume between typically developing brain and RTT-affected brain may tend to continuously increase until adulthood in both temporal lobes although not significant after correction for multiple comparison. CONCLUSIONS: A significant reduction in brain volume was observed in the RTT group. Cortical gray matter volume in the RTT group continued to reduce in bilateral parietal lobes and left occipital lobes. These results provide a baseline for future studies on the effect of RTT treatment and related neuroscience research.

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Objectives: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental disorders, and early detection is crucial. This study aims to identify the Regions of Interest (ROIs) with significant differences between healthy controls and individuals with autism, as well as evaluate the agreement between FreeSurfer 6 (FS6) and Computational Anatomy Toolbox (CAT12) methods. Materials & Methods: Surface-based and volume-based features were extracted from FS software and CAT12 toolbox for Statistical Parametric Mapping (SPM) software to estimate ROI-wise biomarkers. These biomarkers were compared between 18 males Typically Developing Controls (TDCs) and 40 male subjects with ASD to assess group differences for each method. Finally, agreement and regression analyses were performed between the two methods for TDCs and ASD groups. Results: Both methods revealed ROIs with significant differences for each parameter. The Analysis of Covariance (ANCOVA) showed that both TDCs and ASD groups indicated a significant relationship between the two methods (p<0.001). The R2 values for TDCs and ASD groups were 0.692 and 0.680, respectively, demonstrating a moderate correlation between CAT12 and FS6. Bland-Altman graphs showed a moderate level of agreement between the two methods. Conclusion: The moderate correlation and agreement between CAT12 and FS6 suggest that while some consistency is observed in the results, CAT12 is not a superior substitute for FS6 software. Further research is needed to identify a potential replacement for this method.

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Breastfeeding has been associated with several short- and long-term health benefits, including positive cognitive and behavioral outcomes. However, the impact of breastfeeding on structural brain development over time remains unclear. We aimed to assess the association between breastfeeding duration in childhood and the developmental trajectory of overall cortical thickness, cortical area, and total intracranial volume during the transition from childhood to early adulthood. Participants included 670 children and adolescents with 1326 MRI scans acquired over 8 years from the Brazilian High-Risk Cohort for Mental Conditions (BHRCS). Breastfeeding was assessed using a questionnaire answered by the parents. Brain measures were estimated using MRI T1-weighted images at three time points, with 3-year intervals. Data were evaluated using generalized additive models adjusted for multiple confounders. We found that a longer breastfeeding duration was directly associated with higher global cortical thickness in the left (edf = 1.0, F = 6.07, p = 0.01) and right (edf = 1.0, F = 4.70, p = 0.03) hemispheres. For the total intracranial volume, we found an interaction between duration of breastfeeding and developmental stage (edf = 1.0, F = 6.81, p = 0.009). No association was found between breastfeeding duration and brain area. Our study suggests that the duration of breastfeeding impacts overall cortical thickness and the development of total brain volume, but not area. This study adds to the evidence on the potential impact of breastfeeding on brain development and provides relevant insights into the mechanisms by which breastfeeding might confer cognitive and mental health benefits.

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PURPOSE: Total intracranial volume (TIV) is often a nuisance covariate in MRI-based brain volumetry. This study compared two TIV adjustment methods with respect to their impact on z-scores in single subject analyses of regional brain volume estimates. METHODS: Brain parenchyma, hippocampus, thalamus, and TIV were segmented in a normal database comprising 5059 T1w images. Regional volume estimates were adjusted for TIV using the residual method or the proportion method. Age was taken into account by regression with both methods. TIV- and age-adjusted regional volumes were transformed to z-scores and then compared between the two adjustment methods. Their impact on the detection of thalamus atrophy was tested in 127 patients with multiple sclerosis. RESULTS: The residual method removed the association with TIV in all regions. The proportion method resulted in a switch of the direction without relevant change of the strength of the association. The reduction of physiological between-subject variability was larger with the residual method than with the proportion method. The difference between z-scores obtained with the residual method versus the proportion method was strongly correlated with TIV. It was larger than one z-score point in 5% of the subjects. The area under the ROC curve of the TIV- and age-adjusted thalamus volume for identification of multiple sclerosis patients was larger with the residual method than with the proportion method (0.84 versus 0.79). CONCLUSION: The residual method should be preferred for TIV and age adjustments of T1w-MRI-based brain volume estimates in single subject analyses.

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PURPOSE: Numerous brain MR imaging studies have been performed to understand radiation-induced cognitive decline. However, many of them focus on a single region of interest, e.g. cerebral cortex or hippocampus. In this study, we use deformation-based morphometry (DBM) and voxel-based morphometry (VBM) to measure the morphological changes in patients receiving fractionated photon RT, and relate these to the dose. Additionally, we study tissue specific volume changes in white matter (WM), grey matter (GM), cerebrospinal fluid and total intracranial volume (TIV). METHODS AND MATERIALS: From our database, we selected 28 patients with MRI of high quality available at baseline and 1 year after RT. Scans were rigidly registered to each other, and to the planning CT and dose file. We used DBM to study non-tissue-specific volumetric changes, and VBM to study volume loss in grey matter. Observed changes were then related to the applied radiation dose (in EQD2). Additionally, brain tissue was segmented into WM, GM and cerebrospinal fluid, and changes in these volumes and TIV were tested. RESULTS: Performing DBM resulted in clusters of dose-dependent volume loss 1 year after RT seen throughout the brain. Both WM and GM were affected; within the latter both cerebral cortex and subcortical nuclei show volume loss. Volume loss rates ranging from 5.3 to 15.3%/30 Gy were seen in the cerebral cortical regions in which more than 40% of voxels were affected. In VBM, similar loss rates were seen in the cortex and nuclei. The total volume of WM and GM significantly decreased with rates of 5.8% and 2.1%, while TIV remained unchanged as expected. CONCLUSIONS: Radiotherapy is associated with dose-dependent intracranial morphological changes throughout the entire brain. Therefore, we will consider to revise sparing of organs at risk based on future cognitive and neurofunctional data.

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Stress is inevitably linked to life. It has many and complex facets. Notably, perception of stressful stimuli is an important factor when mounting stress responses and measuring its impact. Indeed, moved by the increasing number of stress-triggered pathologies, several groups drew on advanced neuroimaging techniques to explore stress effects on the brain. From that, several regions and circuits have been linked to stress, and a comprehensive integration of the distinct findings applied to common individuals is being pursued, but with conflicting results. Herein, we performed a volumetric regression analysis using participants' perceived stress as a variable of interest. Data shows that increased levels of perceived stress positively associate with the right amygdala and anterior hippocampal volumes.

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Successful segmentation of the total intracranial vault (ICV) and ventricles is of critical importance when studying neurodegeneration through neuroimaging. We present iCVMapper and VentMapper, robust algorithms that use a convolutional neural network (CNN) to segment the ICV and ventricles from both single and multi-contrast MRI data. Our models were trained on a large dataset from two multi-site studies (N = 528 subjects for ICV, N = 501 for ventricular segmentation) consisting of older adults with varying degrees of cerebrovascular lesions and atrophy, which pose significant challenges for most segmentation approaches. The models were tested on 238 participants, including subjects with vascular cognitive impairment and high white matter hyperintensity burden. Two of the three test sets came from studies not used in the training dataset. We assessed our algorithms relative to four state-of-the-art ICV extraction methods (MONSTR, BET, Deep Extraction, FreeSurfer, DeepMedic), as well as two ventricular segmentation tools (FreeSurfer, DeepMedic). Our multi-contrast models outperformed other methods across many of the evaluation metrics, with average Dice coefficients of 0.98 and 0.96 for ICV and ventricular segmentation respectively. Both models were also the most time efficient, segmenting the structures in orders of magnitude faster than some of the other available methods. Our networks showed an increased accuracy with the use of a conditional random field (CRF) as a post-processing step. We further validated both segmentation models, highlighting their robustness to images with lower resolution and signal-to-noise ratio, compared to tested techniques. The pipeline and models are available at: https://icvmapp3r.readthedocs.io and https://ventmapp3r.readthedocs.io to enable further investigation of the roles of ICV and ventricles in relation to normal aging and neurodegeneration in large multi-site studies.

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Background: White matter hyperintensities (WMH) contribute to cognitive decline and increase risk for dementia. Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by the emergence and persistence of neuropsychiatric symptoms (NPS) in later life as an at-risk state for incident cognitive decline and dementia. Both WMH and MBI are common in patients with mild cognitive impairment (MCI), but few studies have established the link between these two risk markers in this population. Methods: Participants were memory clinic patients with MCI from the French MEMENTO study. WMH volume was quantified using brain magnetic resonance imaging. Participants were categorized into MBI+ and MBI- status based on NPS persistence, and the association between MBI status and domains with WMH volume was assessed with linear regression. Results: A total of 768 participants [mean age 72.8 (SD=8.00); 57% female] were included. MBI (i.e., persistent NPS) was present in 229 participants (29.8%). MBI+ status was significantly associated with lower MMSE score and male sex. Compared to MBI-, MBI+ status was associated with 9.4% higher WMH volume [p = 0.01 (95% CI 2.0% to 16.7%)]. In this model, MMSE score was not associated with WMH volume. None of the MBI domains individually predicted greater WMH volume, although emotional dysregulation, impulse dyscontrol, and apathy trended towards significance. Conclusions: In a memory clinic sample of older adults with MCI, MBI was associated with higher WMH volume. Global MBI status outperformed MMSE and individual MBI domains, supporting the utility of MBI, a multi-NPS-domain composite assessment, for predicting WMH volume.

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Background: Depression has been linked to vitamin D deficiency. However, little attention was paid to the neural substrate underlying this association. Methods: Fifty patients with major depressive disorder (MDD) were enrolled in this study. High-resolution structural magnetic resonance imaging was performed to calculate total intracranial volume (TIV). Peripheral venous blood samples were collected to measure serum vitamin D concentration. Hamilton Rating Scale for Depression (HAMD) was used to assess severity of depression symptoms. The relationship among TIV, serum vitamin D concentration, and HAMD score was examined using correlation, linear regression, and mediation analyses. Results: In patients with MDD, HAMD score was negatively correlated with TIV and serum vitamin D concentration, and TIV was positively correlated with serum vitamin D concentration. Linear regression analyses showed that TIV and serum vitamin D concentration were significant predictors of HAMD score. Importantly, mediation analysis revealed that TIV significantly mediated the relationship between serum vitamin D concentration and HAMD score. Conclusion: Our findings suggest that TIV may serve as a potential neural biomarker for monitoring responses to adjuvant therapy of vitamin D in patients with MDD.

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When analyzing large multicenter databases, the effects of multiple confounding covariates increase the variability in the data and may reduce the ability to detect changes due to the actual effect of interest, for example, changes due to disease. Efficient ways to evaluate the effect of covariates toward the data harmonization are therefore important. In this article, we showcase techniques to assess the "goodness of harmonization" of covariates. We analyze 7,656 MR images in the multisite, multiscanner Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We present a comparison of three methods for estimating total intracranial volume to assess their robustness and correct the brain structure volumes using the residual method and the proportional (normalization by division) method. We then evaluated the distribution of brain structure volumes over the entire ADNI database before and after accounting for multiple covariates such as total intracranial volume, scanner field strength, sex, and age using two techniques: (a) Zscapes, a panoramic visualization technique to analyze the entire database and (b) empirical cumulative distributions functions. The results from this study highlight the importance of assessing the goodness of data harmonization as a necessary preprocessing step when pooling large data set with multiple covariates, prior to further statistical data analysis.

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Alzheimer's disease (AD) is characterized by an accumulation of ß-amyloid (Aß42) accompanied by brain atrophy and cognitive decline. Several recent studies have shown that Aß42 accumulation is associated with gray matter (GM) changes prior to the development of cognitive impairment, in the so-called preclinical stage of the AD (pre-AD). It also has been proved that the GM atrophy profile is not linear, both in normal ageing but, especially, on AD. However, several other factors may influence this association and may have an impact on the generalization of results from different samples. In this work, we estimate differences in rates of GM volume change in cognitively healthy elders in association with baseline core cerebrospinal fluid (CSF) AD biomarkers, and assess to what these differences are sample dependent. We report the dependence of atrophy rates, measured in a two-year interval, on Aß42, computed both over continuous and categorical values of Aß42, at voxel-level (p < 0.001; k < 100) and corrected for sex, age and education. Analyses were performed jointly and separately, on two samples. The first sample was formed of 31 individuals (22 Ctrl and 9 pre-AD), aged 60-80 and recruited at the Hospital Clinic of Barcelona. The second sample was a replica of the first one with subjects selected from the ADNI dataset. We also investigated the dependence of the GM atrophy rate on the basal levels of continuous p-tau and on the p-tau/Aß42 ratio. Correlation analyses on the whole sample showed a dependence of GM atrophy rates on Aß42 in medial and orbital frontal, precuneus, cingulate, medial temporal regions and cerebellum. Correlations with p-tau were located in the left hippocampus, parahippocampus and striatal nuclei whereas correlation with p-tau/Aß42 was mainly found in ventral and medial temporal areas. Regarding analyses performed separately, we found a substantial discrepancy of results between samples, illustrating the complexities of comparing two independent datasets even when using the same inclusion criteria. Such discrepancies may lead to significant differences in the sample size needed to detect a particular reduction on cerebral atrophy rates in prevention trials. Higher cognitive reserve and more advanced pathological progression in the ADNI sample could partially account for the observed discrepancies. Taken together, our findings in these two samples highlight the importance of comparing and merging independent datasets to draw more robust and generalizable conclusions on the structural changes in the preclinical stages of AD.

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One of the most common mitochondrial DNA (mtDNA) mutations, the A to G transition at base pair 3243, has been linked to changes in the brain, in addition to commonly observed hearing problems, diabetes and myopathy. However, a detailed quantitative description of m.3243A>G patients' brains has not been provided so far. In this study, ultra-high field MRI at 7T and volume- and surface-based data analyses approaches were used to highlight morphology (i.e. atrophy)-, microstructure (i.e. myelin and iron concentration)- and metabolism (i.e. cerebral blood flow)-related differences between patients (N = 22) and healthy controls (N = 15). The use of quantitative MRI at 7T allowed us to detect subtle changes of biophysical processes in the brain with high accuracy and sensitivity, in addition to typically assessed lesions and atrophy. Furthermore, the effect of m.3243A>G mutation load in blood and urine epithelial cells on these MRI measures was assessed within the patient population and revealed that blood levels were most indicative of the brain's state and disease severity, based on MRI as well as on neuropsychological data. Morphometry MRI data showed a wide-spread reduction of cortical, subcortical and cerebellar gray matter volume, in addition to significantly enlarged ventricles. Moreover, surface-based analyses revealed brain area-specific changes in cortical thickness (e.g. of the auditory cortex), and in T1, T2* and cerebral blood flow as a function of mutation load, which can be linked to typically m.3243A>G-related clinical symptoms (e.g. hearing impairment). In addition, several regions linked to attentional control (e.g. middle frontal gyrus), the sensorimotor network (e.g. banks of central sulcus) and the default mode network (e.g. precuneus) were characterized by alterations in cortical thickness, T1, T2* and/or cerebral blood flow, which has not been described in previous MRI studies. Finally, several hypotheses, based either on vascular, metabolic or astroglial implications of the m.3243A>G mutation, are discussed that potentially explain the underlying pathobiology. To conclude, this is the first 7T and also the largest MRI study on this patient population that provides macroscopic brain correlates of the m.3243A>G mutation indicating potential MRI biomarkers of mitochondrial diseases and might guide future (longitudinal) studies to extensively track neuropathological and clinical changes.

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Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a characteristic overeating disorder, mild to moderate intellectual disability, and a variable range of social and behavioral difficulties. Consequently, widespread alterations in neural structure and developmental and maturational trajectory would be expected. To date, there have been few quantitative and systematic studies of brain morphology in PWS, although alterations of volume and of cortical organisation have been reported. This study aimed to investigate, in detail, the structure of grey matter and cortex in the brain in a sample of young adults with PWS in a well-matched case-controlled analysis. 20 young adults with PWS, aged 19-27 years, underwent multiparameter mapping magnetic resonance imaging sequences, from which measures of grey matter volume, cortical thickness and magnetisation transfer saturation, as a proxy measure of myelination, were examined. These variables were investigated in comparison to a control group of 40 typically developing young adults, matched for age and sex. A voxel-based morphometry analysis identified large and widespread bilateral clusters of both increased and decreased grey matter volume in the brain in PWS. In particular, widespread areas of increased volume encompassed parts of the prefrontal cortex, especially medially, the majority of the cingulate cortices, from anterior to posterior aspects, insula cortices, and areas of the parietal and temporal cortices. Increased volume was also reported in the caudate, putamen and thalamus. The most ventromedial prefrontal areas, in contrast, showed reduced volume, as did the parts of the medial temporal lobe, bilateral temporal poles, and a small cluster in the right lateral prefrontal cortex. Analysis of cortical structure revealed that areas of increased volume in the PWS group were largely driven by greater cortical thickness. Conversely, analysis of myelin content using magnetisation transfer saturation indicated that myelination of the cortex was broadly similar in the PWS and control groups, with the exception of highly localised areas, including the insula. The bilateral nature of these abnormalities suggests a systemic biological cause, with possible developmental and maturational mechanisms discussed, and may offer insight into the contribution of imprinted genes to neural development.

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BACKGROUND AND PURPOSE: Children of Women with Epilepsy with antenatal exposure to antiepileptic drugs (CAED) have reduced neuropsychological functions. We aimed to explore the anatomical basis for this impairment by comparing the brain volumes of CAED with that of matched healthy children without antenatal AED exposure (COAED). MATERIALS AND METHODS: CAED aged 8-12 years were recruited from the Kerala Registry of epilepsy and pregnancy that prospectively follows up children of women with epilepsy and COAED from children attending the imaging department for minor illnesses. Maternal clinical details and the neuropsychological data including IQ of CAED and COAED were obtained. Total intracranial volume (TBV), grey matter volume (GMV), white matter volume (WMV) and volumes of deep grey matter were measured by Voxel Based Morphometry. RESULTS: We studied 30 CAED (mean age 10.8+1.11 years) and 35 COAED (mean age 10.64+1.26). The antenatal AED exposure for the CAED was monotherapy for 8 children and polytherapy for 22 children. The CAED had significantly lower (P<0.001) IQ (77.5+13.8), TBV(1259.55±169.85mL) and GMV (672.51±85.42 mL) compared to the IQ (87.0+13.5), TBV(1405.37±161mL) and GMV (745.427±86.69 mL) of COAED. CAED had lower volumes for Lt Inferior Triangular Gyrus, and hippocampi on both sides, when compared to COAED. Group analysis CAED showed less GMV (P<0.05) for left inferior and middle frontal gyri relative to COAED. CONCLUSIONS: These observations point towards an anatomical basis of lower GMV for the lower neuropsychological functions in children with antenatal AED exposure.

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Total intracranial volume (TIV) is often used as a measure of brain size to correct for individual variability in magnetic resonance imaging (MRI) based morphometric studies. An adjustment of TIV can greatly increase the statistical power of brain morphometry methods. As such, an accurate and precise TIV estimation is of great importance in MRI studies. In this paper, we compared three automated TIV estimation methods (multi-atlas likelihood fusion (MALF), Statistical Parametric Mapping 8 (SPM8) and FreeSurfer (FS)) using longitudinal T1-weighted MR images in a cohort of 70 older participants at elevated sociodemographic risk for Alzheimer's disease. Statistical group comparisons in terms of four different metrics were performed. Furthermore, sex, education level, and intervention status were investigated separately for their impacts on the TIV estimation performance of each method. According to our experimental results, MALF was the least susceptible to atrophy, while SPM8 and FS suffered a loss in precision. In group-wise analysis, MALF was the least sensitive method to group variation, whereas SPM8 was particularly sensitive to sex and FS was unstable with respect to education level. In terms of effectiveness, both MALF and SPM8 delivered a user-friendly performance, while FS was relatively computationally intensive.

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Voxel-based morphometry (VBM) studies of Parkinson's disease (PD), have yielded mixed results, possibly due to several studies not accounting for common nuisance variables (age, sex, and total intracranial volume [TICV]). TICV is particularly important because there is evidence for larger TICV in PD. We explored the influence of these covariates on VBM by 1) comparing PD patients and controls before adding covariates, after adding age and sex, and after adding age, sex and TICV, and 2) by comparing controls split into large and small TICV before and after controlling for TICV, with age and sex accounted for in both analyses. Experiment 1 consisted of 40 PD participants and 40 controls. Experiment 2 consisted of 88 controls median split by TICV. All participants completed an MRI on a 3 T scanner. TICV was calculated as gray + white + CSF from Freesurfer. VBM was performed on T1 images using an optimized VBM protocol. Volume differences were assessed using a voxel-wise GLM analysis. Clusters were considered significant at >10 voxels and p < .05 corrected for familywise error. Before controlling for covariates, PD showed reduced GM in temporal, occipital, and cerebellar regions. Controlling for age and sex did not affect the pattern of significance. Controlling for TICV reduced the size of the significant region although it still contained portions of bilateral temporal lobes, occipital lobes and cerebellum. The large TICV group showed reduced volume in temporal, parietal, and cerebellar areas. None of these differences survived controlling for TICV. This demonstrates that TICV influences VBM results independently from other factors. Controlling for TICV in VBM studies is recommended.

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BACKGROUND: Writer's cramp is a task-specific dystonia impairing writing and sometimes other fine motor tasks. Neuroimaging studies using manifold designs have shown varying results regarding the nature of changes in the disease. OBJECTIVE: To clarify and extend the knowledge of underlying changes by investigating functional connectivity (FC) in intrinsic connectivity networks with putative sensorimotor function at rest in an increased number of study subjects. METHODS: Resting-state functional magnetic resonance imaging with independent component analysis was performed in 26/27 writer's cramp patients/healthy controls, and FC within and between resting state networks with putative sensorimotor function was compared. Additionally, voxel-based morphometry was carried out on the subjects' structural images. RESULTS: Patients displayed increased left- and reduced right-hemispheric primary sensorimotor FC in the premotor-parietal network. Mostly bilaterally altered dorsal/ventral premotor FC, as well as altered parietal FC were observed within multiple sensorimotor networks and showed differing network-dependent directionality. Beyond within-network FC changes and reduced right cerebellar grey matter volume in the structural analysis, the positive between-network FC of the cerebellar network and the basal ganglia network was reduced. CONCLUSIONS: Abnormal resting-state FC in multiple networks with putative sensorimotor function may act as basis of preexisting observations made during task-related neuroimaging. Further, altered connectivity between the cerebellar and basal ganglia network underlines the important role of these structures in the disease.

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OBJECTIVE: Mutations in SCN1A gene encoding the alpha 1 subunit of the voltage gated sodium channel are associated with several epilepsy syndromes including genetic epilepsy with febrile seizures plus (GEFS +) and severe myoclonic epilepsy of infancy (SMEI). However, in most patients with SCN1A mutation, brain imaging has reported normal or non-specific findings including cerebral or cerebellar atrophy. The aim of this study was to investigate differences in brain morphometry in epileptic children with SCN1A mutation compared to healthy control subjects. METHODS: We obtained cortical morphology (thickness, and surface area) and brain volume (global, subcortical, and regional) measurements using FreeSurfer (version 5.3.0, https://surfer.nmr.mgh.harvard.edu) and compared measurements of children with epilepsy and SCN1A gene mutation (n = 21) with those of age and gender matched healthy controls (n = 42). RESULTS: Compared to the healthy control group, children with epilepsy and SCN1A gene mutation exhibited smaller total brain, total gray matter and white matter, cerebellar white matter, and subcortical volumes, as well as mean surface area and mean cortical thickness. A regional analysis revealed significantly reduced gray matter volume in the patient group in the bilateral inferior parietal, left lateral orbitofrontal, left precentral, right postcentral, right isthmus cingulate, right middle temporal area with smaller surface area and white matter volume in some of these areas. However, the regional cortical thickness was not significantly different in two groups. SIGNIFICANCE: This study showed large-scale developmental brain changes in patients with epilepsy and SCN1A gene mutation, which may be associated with the core symptoms of the patients. Further longitudinal MRI studies with larger cohorts are required to confirm the effect of SCN1A gene mutation on structural brain development.

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Genetic frontotemporal dementia is most commonly caused by mutations in the progranulin (GRN), microtubule-associated protein tau (MAPT) and chromosome 9 open reading frame 72 (C9orf72) genes. Previous small studies have reported the presence of cerebral white matter hyperintensities (WMH) in genetic FTD but this has not been systematically studied across the different mutations. In this study WMH were assessed in 180 participants from the Genetic FTD Initiative (GENFI) with 3D T1- and T2-weighed magnetic resonance images: 43 symptomatic (7 GRN, 13 MAPT and 23 C9orf72), 61 presymptomatic mutation carriers (25 GRN, 8 MAPT and 28 C9orf72) and 76 mutation negative non-carrier family members. An automatic detection and quantification algorithm was developed for determining load, location and appearance of WMH. Significant differences were seen only in the symptomatic GRN group compared with the other groups with no differences in the MAPT or C9orf72 groups: increased global load of WMH was seen, with WMH located in the frontal and occipital lobes more so than the parietal lobes, and nearer to the ventricles rather than juxtacortical. Although no differences were seen in the presymptomatic group as a whole, in the GRN cohort only there was an association of increased WMH volume with expected years from symptom onset. The appearance of the WMH was also different in the GRN group compared with the other groups, with the lesions in the GRN group being more similar to each other. The presence of WMH in those with progranulin deficiency may be related to the known role of progranulin in neuroinflammation, although other roles are also proposed including an effect on blood-brain barrier permeability and the cerebral vasculature. Future studies will be useful to investigate the longitudinal evolution of WMH and their potential use as a biomarker as well as post-mortem studies investigating the histopathological nature of the lesions.

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Hexanucleotide repeat expansions in C9ORF72 are the most common known genetic cause of familial and sporadic frontotemporal dementia and amyotrophic lateral sclerosis. Previous work has shown that patients with behavioral variant frontotemporal dementia due to C9ORF72 show salience and sensorimotor network disruptions comparable to those seen in sporadic behavioral variant frontotemporal dementia, but it remains unknown how early in the lifespan these and other changes in brain structure and function arise. To gain insights into this question, we compared 15 presymptomatic carriers (age 43.7 ± 10.2 years, nine females) to matched healthy controls. We used voxel-based morphometry to assess gray matter, diffusion tensor imaging to interrogate white matter tracts, and task-free functional MRI to probe the salience, sensorimotor, default mode, and medial pulvinar thalamus-seeded networks. We further used a retrospective chart review to ascertain psychiatric histories in carriers and their non-carrier family members. Carriers showed normal cognition and behavior despite gray matter volume and brain connectivity deficits that were apparent as early as the fourth decade of life. Gray matter volume deficits were topographically similar though less severe than those in patients with behavioral variant frontotemporal dementia due to C9ORF72, with major foci in cingulate, insula, thalamus, and striatum. Reduced white matter integrity was found in the corpus callosum, cingulum bundles, corticospinal tracts, uncinate fasciculi and inferior longitudinal fasciculi. Intrinsic connectivity deficits were detected in all four networks but most prominent in salience and medial pulvinar thalamus-seeded networks. Carrier and control groups showed comparable relationships between imaging metrics and age, suggesting that deficits emerge during early adulthood. Carriers and non-carrier family members had comparable lifetime histories of psychiatric symptoms. Taken together, the findings suggest that presymptomatic C9ORF72 expansion carriers exhibit functionally compensated brain volume and connectivity deficits that are similar, though less severe, to those reported during the symptomatic phase. The early adulthood emergence of these deficits suggests that they represent aberrant network patterning during development, an early neurodegeneration prodrome, or both.

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