An in vivo high-resolution human brain atlas of synaptic density.

Synapses are fundamental to the function of the central nervous system and are implicated in a number of brain disorders. Despite their pivotal role, a comprehensive imaging resource detailing the distribution of synapses in the human brain has been lacking until now. Here, we employ high-resolution PET neuroimaging in healthy humans (17F/16M) to create a 3D atlas of the synaptic marker Synaptic Vesicle glycoprotein 2A (SV2A). Calibration to absolute density values (pmol/mL) was achieved by leveraging postmortem human brain autoradiography data. The atlas unveils distinctive cortical and subcortical gradients of synapse density that reflect functional topography and hierarchical order from core sensory to higher-order integrative areas - a distribution that diverges from SV2A mRNA patterns. Furthermore, we find a positive association between IQ and SV2A density in several higher-order cortical areas. This new resource will help advance our understanding of brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future neuroscience research.Significance statement Here, we present a high-resolution 3D in vivo brain atlas of synaptic density in the human brain. In the healthy human brain, distinctive cortical and subcortical gradients of synapse density reflect functional topography and hierarchical order from core sensory to higher-order integrative areas - a distribution that diverges from SV2A mRNA patterns. This brain atlas will help advance our understanding of human brain physiology and the pathogenesis of brain disorders, serving as a pivotal tool for future research in clinical, translational and comparative neuroscience .

Long-Term Medication Profiles in Parkinson's Disease under Subthalamic Deep Brain Stimulation: A Controlled Study.

BACKGROUND: Subthalamic deep brain stimulation (STN-DBS) reduces antiparkinsonian medications in Parkinson's disease (PD) compared with the preoperative state. Longitudinal and comparative studies on this effect are lacking. OBJECTIVE: To compare longitudinal trajectories of antiparkinsonian medication in STN-DBS treated patients to non-surgically treated control patients. METHODS: We collected retrospective information on antiparkinsonian medication from PD patients that underwent subthalamic DBS between 1999 and 2010 and control PD patients similar in age at onset and baseline, sex-distribution, and comorbidities. RESULTS: In 74 DBS patients levodopa-equivalent daily dose (LEDD) were reduced by 33.9-56.0% in relation to the preoperative baseline over the 14-year observational period. In 61 control patients LEDDs increased over approximately 10 years, causing a significant divergence between groups. The largest difference amongst single drug-classes was observed for dopamine agonists. CONCLUSION: In PD patients, chronic STN-DBS was associated with a lower LEDD compared with control patients over 14 years.

Progressive Brain Atrophy in Multiple System Atrophy: A Longitudinal, Multicenter, Magnetic Resonance Imaging Study.

OBJECTIVE: To determine the rates of brain atrophy progression in vivo in patients with multiple system atrophy (MSA). BACKGROUND: Surrogate biomarkers of disease progression are a major unmet need in MSA. Small-scale longitudinal studies in patients with MSA using magnetic resonance imaging (MRI) to assess progression of brain atrophy have produced inconsistent results. In recent years, novel MRI post-processing methods have been developed enabling reliable quantification of brain atrophy in an automated fashion. METHODS: Serial 3D-T1-weighted MRI assessments (baseline and after 1 year of follow-up) of 43 patients with MSA were analyzed and compared to a cohort of early-stage Parkinson's disease (PD) patients and healthy controls (HC). FreeSurfer's longitudinal analysis stream was used to determine the brain atrophy rates in an observer-independent fashion. RESULTS: Mean ages at baseline were 64.4 ± 8.3, 60.0 ± 7.5, and 59.8 ± 9.2 years in MSA, PD patients and HC, respectively. A mean disease duration at baseline of 4.1 ± 2.5 years in MSA patients and 2.3 ± 1.4 years in PD patients was observed. Brain regions chiefly affected by MSA pathology showed progressive atrophy with annual rates of atrophy for the cerebellar cortex, cerebellar white matter, pons, and putamen of -4.24 ± 6.8%, -8.22 ± 8.8%, -4.67 ± 4.9%, and - 4.25 ± 4.9%, respectively. Similar to HC, atrophy rates in PD patients were minimal with values of -0.41% ± 1.8%, -1.47% ± 4.1%, -0.04% ± 1.8%, and -1.54% ± 2.2% for cerebellar cortex, cerebellar white matter, pons, and putamen, respectively. CONCLUSIONS: Patients with MSA show significant brain volume loss over 12 months, and cerebellar, pontine, and putaminal volumes were the most sensitive to change in mid-stage disease. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial.

Selective serotonin reuptake inhibitors (SSRIs) are widely used for treating neuropsychiatric disorders. However, the exact mechanism of action and why effects can take several weeks to manifest is not clear. The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited. Here, we investigate the effects of the SSRI escitalopram on presynaptic density as a proxy for synaptic plasticity. In a double-blind placebo-controlled study (NCT04239339), 32 healthy participants with no history of psychiatric or cognitive disorders were randomized to receive daily oral dosing of either 20 mg escitalopram (n = 17) or a placebo (n = 15). After an intervention period of 3-5 weeks, participants underwent a [11C]UCB-J PET scan (29 with full arterial input function) to quantify synaptic vesicle glycoprotein 2A (SV2A) density in the hippocampus and the neocortex. Whereas we find no statistically significant group difference in SV2A binding after an average of 29 (range: 24-38) days of intervention, our secondary analyses show a time-dependent effect of escitalopram on cerebral SV2A binding with positive associations between [11C]UCB-J binding and duration of escitalopram intervention. Our findings suggest that brain synaptic plasticity evolves over 3-5 weeks in healthy humans following daily intake of escitalopram. This is the first in vivo evidence to support the hypothesis of neuroplasticity as a mechanism of action for SSRIs in humans and it offers a plausible biological explanation for the delayed treatment response commonly observed in patients treated with SSRIs. While replication is warranted, these results have important implications for the design of future clinical studies investigating the neurobiological effects of SSRIs.

Somatostatin receptor subtype expression and radiomics from DWI-MRI represent SUV of [68Ga]Ga-DOTATOC PET in patients with meningioma.

OBJECTIVE: This retrospective study aimed to analyse the correlation between somatostatin receptor subtypes (SSTR 1-5) and maximum standardized uptake value (SUVmax) in meningioma patients using Gallium-68 DOTA-D-Phe1-Tyr3-octreotide Positron Emission Tomography ([68Ga]Ga-DOTATOC PET). Secondly, we developed a radiomic model based on apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance images (DWI MRI) to reproduce SUVmax. METHOD: The study included 51 patients who underwent MRI and [68Ga]Ga-DOTATOC PET before meningioma surgery. SUVmax values were quantified from PET images and tumour areas were segmented on post-contrast T1-weighted MRI and mapped to ADC maps. A total of 1940 radiomic features were extracted from the tumour area on each ADC map. A random forest regression model was trained to predict SUVmax and the model's performance was evaluated using repeated nested cross-validation. The expression of SSTR subtypes was quantified in 18 surgical specimens and compared to SUVmax values. RESULTS: The random forest regression model successfully predicted SUVmax values with a significant correlation observed in all 100 repeats (p < 0.05). The mean Pearson's r was 0.42 ± 0.07 SD, and the root mean square error (RMSE) was 28.46 ± 0.16. SSTR subtypes 2A, 2B, and 5 showed significant correlations with SUVmax values (p < 0.001, R2 = 0.669; p = 0.001, R2 = 0.393; and p = 0.012, R2 = 0.235, respectively). CONCLUSION: SSTR subtypes 2A, 2B, and 5 correlated significantly with SUVmax in meningioma patients. The developed radiomic model based on ADC maps effectively reproduces SUVmax using [68Ga]Ga-DOTATOC PET.

Association between the loudness dependence of auditory evoked potential, serotonergic neurotransmission and treatment outcome in patients with depression.

Previous studies have suggested that the loudness dependence of auditory evoked potential (LDAEP) is associated with the effectiveness of antidepressant treatment in patients with major depressive disorders (MDD). Furthermore, both LDAEP and the cerebral serotonin 4 receptor (5-HT4R) density is inversely related to brain serotonin levels. We included 84 patients with MDD and 22 healthy controls to examined the association between LDAEP and treatment response and its association with cerebral 5-HT4R density. Participants underwent both EEG and 5-HT4R neuroimaging with [11C]SB207145 PET. Thirty-nine patients with MDD were re-examined after 8 weeks of treatment with selective serotonin reuptake inhibitors/serotonin noradrenaline reuptake inhibitor (SSRI/SNRI). We found that the cortical source of LDAEP was higher in untreated patients with MDD compared to healthy controls (p=0.03). Prior to SSRI/SNRI treatment, subsequent treatment responders had a negative association between LDAEP and depressive symptoms and a positive association between scalp LDAEP and symptom improvement at week 8. This was not found in source LDAEP. In healthy controls, we found a positive correlation between both scalp and source LDAEP and cerebral 5-HT4R binding but that was not observed in patients with MDD. We did not see any changes in scalp and source LDAEP in response to SSRI/SNRI treatment. These results support a theoretical framework where both LDAEP and cerebral 5-HT4R are indices of cerebral 5-HT levels in healthy individuals while this association seems to be disrupted in MDD. The combination of the two biomarkers may be useful for stratifying patients with MDD. Clinical Trials Registration:https://clinicaltrials.gov/ct2/show/NCT02869035?draw=1Registration number: NCT0286903.

Serotonin 4 Receptor Brain Binding in Major Depressive Disorder and Association With Memory Dysfunction.

Importance: The cerebral serotonin 4 (5-HT4) receptor is a promising novel target for treatment of major depressive disorder (MDD), and pharmacological stimulation of the 5-HT4 receptor has been associated with improved learning and memory in healthy individuals. Objective: To map the neurobiological signatures of patients with untreated MDD compared with healthy controls and to examine the association between cerebral 5-HT4 receptor binding and cognitive functions in the depressed state. Design, Setting, and Participants: This case-control study used baseline data from the NeuroPharm clinical depression trial in Denmark. Adult participants included antidepressant-free outpatients with a current moderate to severe depressive episode and healthy controls. All participants completed positron emission tomography (PET) scanning with [11C]SB207145 for quantification of brain 5-HT4 receptor binding, but only the patients underwent cognitive testing. Data analyses were performed from January 21, 2020, to April 22, 2022. Main Outcomes and Measures: The main study outcome was the group difference in cerebral 5-HT4 receptor binding between patients with MDD and healthy controls. In addition, the association between 5-HT4 receptor binding and verbal memory performance in the patient group was tested. Other cognitive domains (working memory, reaction time, emotion recognition bias, and negative social emotions) were assessed as secondary outcomes. Results: A total of 90 patients with untreated MDD (mean [SD] age, 27.1 [8.2] years; 64 women [71.1%]) and 91 healthy controls (mean [SD] age, 27.1 [8.0] years; 55 women [60.4%]) were included in the analysis. Patients with current MDD had significantly lower cerebral 5-HT4 receptor binding than healthy controls (-7.0%; 95% CI, -11.2 to -2.7; P = .002). In patients with MDD, there was a correlation between cerebral 5-HT4 receptor binding and verbal memory (r = 0.29; P = .02). Conclusions and Relevance: Results of this study show that cerebral 5-HT4 receptor binding was lower in patients with MDD than in healthy controls and that the memory dysfunction in patients with MDD was associated with lower cerebral 5-HT4 receptor binding. The cerebral 5-HT4 receptor is a promising treatment target for memory dysfunction in patients with MDD.

Generalizability of treatment outcome prediction in major depressive disorder using structural MRI: A NeuroPharm study.

Brain morphology has been suggested to be predictive of drug treatment outcome in major depressive disorders (MDD). The current study aims at evaluating the performance of pretreatment structural brain magnetic resonance imaging (MRI) measures in predicting the outcome of a drug treatment of MDD in a large single-site cohort, and, importantly, to assess the generalizability of these findings in an independent cohort. The random forest, boosted trees, support vector machines and elastic net classifiers were evaluated in predicting treatment response and remission following an eight week drug treatment of MDD using structural brain measures derived with FastSurfer (FreeSurfer). Models were trained and tested within a nested cross-validation framework using the NeuroPharm dataset (n = 79, treatment: escitalopram); their generalizability was assessed using an independent clinical dataset, EMBARC (n = 64, treatment: sertraline). Prediction of antidepressant treatment response in the Neuropharm cohort was statistically significant for the random forest (p = 0.048), whereas none of the models could significantly predict remission. Furthermore, none of the models trained using the entire NeuroPharm dataset could significantly predict treatment outcome in the EMBARC dataset. Although our primary findings in the NeuroPharm cohort support some, but limited value in using pretreatment structural brain MRI to predict drug treatment outcome in MDD, the models did not generalize to an independent cohort suggesting limited clinical applicability. This study emphasizes the importance of assessing model generalizability for establishing clinical utility.

Mapping neurotransmitter systems to the structural and functional organization of the human neocortex.

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

Characterization and diagnostic potential of R2* in early-stage progressive supranuclear palsy variants.

INTRODUCTION: Iron accumulation in subcortical brain nuclei has been shown to be differentially increased in atypical parkinsonian disorders. It is unclear whether the patterns of iron accumulation are consistent between variants of progressive supranuclear palsy (PSP) and their diagnostic utility in early to moderately advanced stages of the diseases. METHODS: Brain iron content (R2*) was quantified using magnetic resonance imaging in patients clinically diagnosed as PSP - parkinsonism (PSP-P, n = 15), PSP - Richardson's syndrome (PSP-RS, n = 14), Parkinson's disease (PD, n = 15), or the parkinsonian variant of multiple system atrophy (MSA-P, n = 14) using established criteria, and healthy controls (HC). Disease duration was less than 5 years in all patients. The quantification of regional R2* was performed using a semi-automatized approach. RESULTS: Significant group differences in R2*, primarily within the red nucleus and the substantia nigra, were identified between PSP, PD, MSA-P, and HC, but not between PSP-P and PSP-RS. However, distinct R2* correlation patterns across brain regions were observed for the different groups. Good classification performances (sensitivity and specificity >80%) were only obtained for PSP vs. HC. For all other comparisons, sensitivity and/or specificity was below <70%. CONCLUSION: Iron accumulation in subcortical brain nuclei has distinct correlated patterns in PSP-P and PSP-RS, which could be reflecting different pathophysiological mechanisms. Increased iron content in these nuclei appears to be a predictor for atypical parkinsonian disorders such as PSP and MSA. Further studies are required to reproduce this finding and elucidate the evolution of these patterns over the course of the disease.

Preclinical Pediatric Care by Emergency Physicians: A Comparison of Trauma and Nontrauma Patients in a Population-Based Study in Austria.

OBJECTIVES: Fewer than 10% of emergency medical system (EMS) calls concern children and adolescents younger than 18 years. Studies have shown that the preclinical care of children differs from that of adults regarding assessment, interventions, and monitoring. The aims of this study were to describe the preclinical care and emergency transport of pediatric patients in Vorarlberg, Austria and to compare trauma and nontrauma cases. METHODS: This is a population-based study, analyzing medical records of EMS calls to children and adolescents. We received all patient records of EMS calls to children and adolescents younger than 18 years (n = 4390 in total) from the 2 local EMS providers, the Red Cross Vorarlberg and the Austrian Mountain Rescue Service (Christophorus 8 and Gallus 1) covering a study period of 7 years, from 2013 to 2019. The record data were extracted by automation with an in-house program and subsequently anonymized. Statistical analyses were performed with SPSS Statistics. RESULTS: During the study period, 7.9% of all EMS calls concerned children and adolescents younger than 18 years. For our study, 3761 records were analyzed and 1270 trauma cases (33.8%) were identified. The most common injuries were injuries of the extremities and traumatic brain injury. The frequency of National Advisory Committee of Aeronautics Scores of 4 or higher was 17.7%, similar for all age groups and for trauma as well as nontrauma patients. Mean Glasgow Coma Scale scores were higher in the trauma group than in the nontrauma group (14.2 vs 11.2). In 62.9% of all patients, 1 or more vital parameters were documented. A majority of these values was in the pathologic range for the respective age group. The rate of pulsoxymetry monitoring during transport was low (42.1% in trauma and 30.3% in nontrauma patients) and decreased significantly with patient age. Moreover, while the placing of intravenous lines and monitoring during transport were significantly more frequent in trauma patients, the administration of medication or oxygen was significantly more frequent in nontrauma patients. CONCLUSIONS: The pediatric population lacks assessments and monitoring in preclinical care, especially the youngest children and nontrauma patients, although emergency severity scores are similar.

Investigating the Migraine Cycle over 21 Consecutive Days Using Proton Magnetic Resonance Spectroscopy and Resting-State fMRI: A Pilot Study.

Recent neuroimaging studies have revealed important aspects of the underlying pathophysiological mechanisms of migraine suggesting abnormal brain energy metabolism and altered functional connectivity. Proton magnetic resonance spectroscopy (1H-MRS) studies investigated migraine patients in the interictal or ictal state. This first-of-its-kind study aimed to investigate the whole migraine cycle using 1H-MRS and resting-state functional magnetic resonance imaging (fMRI). A migraine patient underwent 1H-MRS and resting-state fMRI for 21 consecutive days, regardless of whether he was in an interictal or ictal state. Metabolite ratios were assessed and compared to the intrinsic connectivity of subcortical brain areas. Probable migraine phase-dependent changes in N-acetyl aspartate (NAA)/total creatine (tCr) and choline (Cho)/tCr levels are found in the left occipital lobe and left basal ganglia. NAA reflects neuronal integrity and Cho cellular membrane turnover. Such abnormalities may increase the susceptibility to excitatory migraine triggers. Functional connectivity between the right hippocampus and right or left pallidum was strongly correlated to the NAA/Cho ratio in the right thalamus, suggesting neurochemical modulation of these brain areas through thalamic connections. To draw statistically significant conclusions a larger cohort is needed.

Revisiting brain iron deficiency in restless legs syndrome using magnetic resonance imaging.

STUDY OBJECTIVES: Studies on brain iron content in restless legs syndrome (RLS) using magnetic resonance imaging (MRI) are heterogeneous. In this study, we sought to leverage the availability of a large dataset including a range of iron-sensitive MRI techniques to reassess the association between brain iron content and RLS with added statistical power and to compare these results to previous studies. METHODS: The relaxation rates R2, R2', and R2* and quantitative susceptibility are MRI parameters strongly correlated to iron content. In general, these parameters are sensitive to magnetic field variations caused by iron particles. These parameters were quantified within iron-rich brain regions using a fully automatized approach in a cohort of 72 RLS patients and individually age and gender-matched healthy controls identified from an existing dataset acquired at the Sleep Laboratory of the Department of Neurology, Medical University of Innsbruck. 3 T-MRI measures were corrected for age and volume of the segmented brain nuclei and results were compared with previous findings in a meta-analysis. RESULTS: In our cohort, RLS patients had increased R2* signal in the caudate and increased quantitative susceptibility signal in the putamen and the red nucleus compared to controls, suggesting increased iron content in these areas. The meta-analysis revealed no significant pooled effect across all brain regions. Furthermore, potential publication bias was identified for the substantia nigra. CONCLUSIONS: Normal and increased iron content of subcortical brain areas detected in this study is not in line with the hypothesis of reduced brain iron storage, but favors CSF investigations and post mortem studies indicating alteration of brain iron mobilization and homeostasis in RLS.

HFP-QSMGAN: QSM from homodyne-filtered phase images.

PURPOSE: Homodyne filtering is a standard preprocessing step in the estimation of SWI. Unfortunately, SWI is not quantitative, and QSM cannot be accurately estimated from filtered phase images. Compared with gradient-echo sequences suitable for computing QSM, SWI is more readily available and is often the only susceptibility-sensitive sequence acquired in the clinical setting. In this project, we aimed to quantify susceptibility from the homodyne-filtered phase (HFP), acquired for computing susceptibility-weighted images, using convolutional neural networks to solve the compounded problem of (1) computing the solution to the inverse dipole problem, and (2) compensating for the effects of the homodyne filtering. METHODS: Two convolutional neural networks, the U-Net and a modified QSMGAN architecture (HFP-QSMGAN), were trained to predict QSM maps at different TEs from HFP images. The QSM maps were quantified from a gradient-echo sequence acquired in the same individuals using total generalized variation (TGV)-QSM. The QSM maps estimated directly from the HFP were also included for comparison. Voxel-wise predictions and, importantly, regional predictions of susceptibility with adjustment to a reference region, were compared. RESULTS: Our results indicate that the U-Net model provides more accurate voxel-wise predictions of susceptibility compared with HFP-QSMGAN and HFP-QSM. However, regional estimates of susceptibility predicted by HFP-QSMGAN are more strongly correlated with the values from TGV-QSM compared with those of U-Net and HFP-QSM. CONCLUSION: Accurate prediction of susceptibility can be achieved from filtered SWI phase using convolutional neural networks.

Automated segmentation of deep brain nuclei using convolutional neural networks and susceptibility weighted imaging.

The advent of susceptibility-sensitive MRI techniques, such as susceptibility weighted imaging (SWI), has enabled accurate in vivo visualization and quantification of iron deposition within the human brain. Although previous approaches have been introduced to segment iron-rich brain regions, such as the substantia nigra, subthalamic nucleus, red nucleus, and dentate nucleus, these methods are largely unavailable and manual annotation remains the most used approach to label these regions. Furthermore, given their recent success in outperforming other segmentation approaches, convolutional neural networks (CNN) promise better performances. The aim of this study was thus to evaluate state-of-the-art CNN architectures for the labeling of deep brain nuclei from SW images. We implemented five CNN architectures and considered ensembles of these models. Furthermore, a multi-atlas segmentation model was included to provide a comparison not based on CNN. We evaluated two prediction strategies: individual prediction, where a model is trained independently for each region, and combined prediction, which simultaneously predicts multiple closely located regions. In the training dataset, all models performed with high accuracy with Dice coefficients ranging from 0.80 to 0.95. The regional SWI intensities and volumes from the models' labels were strongly correlated with those obtained from manual labels. Performances were reduced on the external dataset, but were higher or comparable to the intrarater reliability and most models achieved significantly better results compared to multi-atlas segmentation. CNNs can accurately capture the individual variability of deep brain nuclei and represent a highly useful tool for their segmentation from SW images.

Characterization and diagnostic potential of diffusion tractography in multiple system atrophy.

INTRODUCTION: Microstructural integrity of the middle cerebellar peduncle (MCP) and the putamen captured by diffusion-tensor imaging (DTI) is differentially affected in the parkinsonian and cerebellar variants of multiple system atrophy (MSA-P, MSA-C) compared to Parkinson's disease (PD). The current study applied DTI and tractography in order to 1) characterize the distribution of DTI metrics along the tracts of the MCP and from the putamen in MSA variants, and 2) evaluate the usefulness of combining these measures for the differential diagnosis of MSA-P against PD in the clinical setting. METHODS: Twenty-nine MSA patients (MSA-C, n = 10; MSA-P, n = 19), with a mean disease duration of 2.8 ± 1.7 years, 19 PD patients, and 27 healthy controls (HC) were included in the study. Automatized tractography with a masking procedure was employed to isolate the MCP tracts. DTI measures along the tracts of the MCP and within the putamen were acquired and jointly used to classify MSA vs. PD, and MSA-P vs. PD. Putamen volume was additionally tested as classification feature in post hoc analyses. RESULTS: DTI measures within the MCP and putamen showed significant alterations in MSA variants compared to HC and PD. Classification accuracy for MSA vs. PD and MSA-P vs PD using diffusion measures was 91.7% and 89.5%, respectively. When replacing the putaminal DTI measure by a normalized measure of putamen volume classification accuracy improved to 95.8% and 94.7%, respectively. CONCLUSION: Multimodal information from MCP tractography and putamen volume yields excellent diagnostic accuracy to discriminate between early-to-moderately advanced patients with MSA and PD.

A high-resolution in vivo atlas of the human brain's benzodiazepine binding site of GABAA receptors.

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the human brain and plays a key role in several brain functions and neuropsychiatric disorders such as anxiety, epilepsy, and depression. For decades, several in vivo and ex vivo techniques have been used to highlight the mechanisms of the GABA system, however, no studies have currently combined the techniques to create a high-resolution multimodal view of the GABA system. Here, we present a quantitative high-resolution in vivo atlas of the human brain benzodiazepine receptor sites (BZR) located on postsynaptic ionotropic GABAA receptors (GABAARs), generated on the basis of in vivo [11C]flumazenil Positron Emission Tomography (PET) data. Next, based on ex vivo autoradiography data, we transform the PET-generated atlas from binding values into BZR protein density. Finally, we examine the brain regional association between BZR protein density and ex vivo mRNA expression for the 19 subunits in the GABAAR, including an estimation of the minimally required expression of mRNA levels for each subunit to translate into BZR protein. This represents the first publicly available quantitative high-resolution in vivo atlas of the spatial distribution of BZR densities in the healthy human brain. The atlas provides a unique neuroscientific tool as well as novel insights into the association between mRNA expression for individual subunits in the GABAAR and the BZR density at each location in the brain.

Occupation-related effects on motor cortex thickness among older, cognitive healthy individuals.

Both, decline of sensorimotor functions and cortical thickness are known processes in healthy aging. Physical activity has been suggested to enhance the execution of daily routine activities and to extend the time of functional independence in advanced age. We hypothesized that cortical thickness of motor areas in retired individuals could be related to physical demands of the profession carried out during working life. Depending on their former occupations, 69 cognitively healthy individuals (range 70-85 years) were divided into higher and lower physically complex occupations (HPCO n = 27 and LPCO n = 42) according to the international standard classification of occupations (ISCO-08). Participants underwent a high-resolution 3T T1-weighted MRI scan. Surface-based analysis revealed higher cortical thickness in the left precentral (P = 0.001) and postcentral gyrus (P < 0.001) and right postcentral gyrus (P = 0.001) for the HPCO relative to the LPCO group (corrected for multiple comparisons, sex, age and leisure activities in the past 20 years). Physical leisure activities associated with exertion were positively correlated with cortical thickness in the left pre- and postcentral gyrus (P = 0.037) of the LPCO group. Time since retirement was negatively associated with cortical thickness in the left postcentral gyrus (P = 0.004) of the HPCO group. Executing a higher physically complex occupation before retirement was related to relative higher cortical thickness in the primary motor and somatosensory cortex in later life, supporting the hypothesis that physical activity contributes to neural reserve in these regions. However, these benefits appear to vanish when physical activity is reduced due to retirement.

Neurodegeneration in Hepatic and Neurologic Wilson's Disease.

Clinical presentation of Wilson disease (WD) includes hepatic and neurologic manifestations. This study compares subcortical brain regions by magnetic resonance imaging in patients with WD and without neurological symptoms. Distinct atrophy affecting the basal ganglia, accumbens, and hippocampus was present in neurological WD. Cerebellar atrophy was observed in hepatic WD without neurological symptoms.

Automated Analysis of Diffusion-Weighted Magnetic Resonance Imaging for the Differential Diagnosis of Multiple System Atrophy from Parkinson's Disease.

BACKGROUND: Manual region-of-interest analysis of putaminal and middle cerebellar peduncle diffusivity distinguishes patients with multiple system atrophy (MSA) and Parkinson's disease (PD) with high diagnostic accuracy. However, a recent meta-analysis found substantial between-study heterogeneity of diagnostic accuracy due to the lack of harmonized imaging protocols and standardized analyses pipelines. OBJECTIVE: Evaluation of diagnostic accuracy of observer-independent analysis of microstructural integrity as measured by diffusion-tensor imaging in patients with MSA and PD. METHODS: A total of 29 patients with MSA and 19 patients with PD (matched for age, gender, and disease duration) with 3 years of follow-up were investigated with diffusion-tensor imaging and T1-weighted magnetic resonance imaging. Automated localization of relevant brain regions was obtained, and mean diffusivity and fractional anisotropy values were averaged within the regions of interest. The classification was performed using a C5.0 hierachical decision tree algorithm. RESULTS: Mean diffusivity of the middle cerebellar peduncle and cerebellar gray and white matter compartment as well as the putamen were significantly increased in patients with MSA and showed superior effect sizes compared to the volumetric analysis of these regions. A classifier model identified mean diffusivity of the middle cerebellar peduncle and putamen as the most predictive parameters. Cross-validation of the classification model yields a Cohen's κ and overall diagnostic accuracy of 0.823 and 0.914, respectively. CONCLUSION: Analysis of microstructural integrity within the middle cerebellar peduncle and putamen yielded a superior effect size compared to the volumetric measures, resulting in excellent diagnostic accuracy to discriminate patients with MSA from PD in the early to moderate disease stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.