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Purpose: Motor neuron disease (MND) causes damage to the upper and lower motor neurons including the motor cranial nerves, the latter resulting in bulbar involvement with atrophy of the tongue muscle. To measure tongue atrophy, an operator independent automatic segmentation of the tongue is crucial. The aim of this study was to apply convolutional neural network (CNN) to MRI data in order to determine the volume of the tongue., Methods: A single triplanar CNN of U-Net architecture trained on axial, coronal, and sagittal planes was used for the segmentation of the tongue in MRI scans of the head. The 3D volumes were processed slice-wise across the three orientations and the predictions were merged using different voting strategies. This approach was developed using MRI datasets from 20 patients with 'classical' spinal amyotrophic lateral sclerosis (ALS) and 20 healthy controls and, in a pilot study, applied to the tongue volume quantification to 19 controls and 19 ALS patients with the variant progressive bulbar palsy (PBP)., Results: Consensus models with softmax averaging and majority voting achieved highest segmentation accuracy and outperformed predictions on single orientations and consensus models with union and unanimous voting. At the group level, reduction in tongue volume was not observed in classical spinal ALS, but was significant in the PBP group, as compared to controls., Conclusion: Utilizing single U-Net trained on three orthogonal orientations with consequent merging of respective orientations in an optimized consensus model reduces the number of erroneous detections and improves the segmentation of the tongue. The CNN-based automatic segmentation allows for accurate quantification of the tongue volumes in all subjects. The application to the ALS variant PBP showed significant reduction of the tongue volume in these patients and opens the way for unbiased future longitudinal studies in diseases affecting tongue volume., (© 2024. The Author(s).)

Background: Validation of the 2020 consensus criteria for primary lateral sclerosis (PLS) is essential for their use in clinical practice and future trials., Methods: In a large cohort of patients diagnosed with PLS by expert opinion prior to the new criteria with detailed clinical baseline evaluation (n=107) and longitudinal follow-up (n=63), we applied the new diagnostic criteria and analysed the clinical phenotype, electromyography (EMG), diagnostic accuracy and prognosis, adding neurofilaments and MRI as potential biomarkers., Results: The criteria for definite PLS were met by 28% and those for probable PLS by 19%, whereas 53% did not meet the full criteria at baseline, mainly due to the time, EMG and region criteria. Patients not meeting the criteria had less generalised upper motor neuron involvement but were otherwise similar in demographic and clinical characteristics. All patients with definite and probable PLS maintained PLS diagnosis during follow-up, while four patients not meeting the criteria developed clinical lower motor neuron involvement. Definite PLS cases showed improved survival compared with probable PLS and patients who did not meet the criteria. Despite a clinical PLS phenotype, fibrillation potentials/positive sharp waves and fasciculations in one or more muscles were a frequent EMG finding, with the extent and prognostic significance depending on disease duration. Serum neurofilament light and a multiparametric MRI fibre integrity Z-score correlated with clinical parameters and were identified as potential biomarkers., Conclusion: Validation of the 2020 PLS consensus criteria revealed high diagnostic certainty and prognostic significance, supporting their value for research and clinical practice., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Monosynaptically cortically innervated α-motoneurons are early and strongly involved in amyotrophic lateral sclerosis (ALS). Consequently, the muscles that receive the strongest direct corticomotoneuronal input are the clinically most affected. To objectify this concept in vivo through morphological image correlates, whole-body magnetic resonance imaging (MRI) with muscle signal analysis was performed in patients with ALS compared to healthy controls., Methods: Modified Dixon-based whole-body MRI was acquired in patients with ALS (n = 33) and matched healthy controls (n = 30). Manual labeling of limb muscle MRI was performed, and a specific subset of nine muscles, selected as pairs of muscle groups with different corticomotoneuronal input, was analyzed per subject based on their volume, fat fraction, and functional remaining muscle area (fRMA)., Results: Statistical analysis of 978 muscles in total revealed significantly decreased volumes, decreased fRMA, and increased fat fraction in the muscles of patients with ALS compared to controls. The clinical degree of pareses of directly innervated muscles was significantly worse than that of less directly innervated muscles in each comparison. The muscles receiving stronger direct corticomotoneuronal input showed more pronounced morphological involvement compared to those with less monosynaptic corticomotoneuronal input (fRMA, significant in three pairwise comparisons)., Interpretation: In conclusion, whole-body MRI-based muscle analysis provided additional evidence for a characteristic pattern of pareses in ALS. This technical approach (parameterization and quantification of muscle alterations from MRI) to patients with ALS could pave the way for the future establishment of a diagnostic algorithm of muscle MRI for ALS and may serve as a biomarker., (© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Objective: To investigate cardiac involvement in patients with sporadic inclusion body myositis (IBM) by cardiac magnetic resonance tomography (CMR)., Methods: A case series of 20 patients with IBM underwent basic cardiac assessment and CMR including functional imaging, native and contrast-enhanced T1-weighted, and late gadolinium enhancement (LGE) imaging., Results: All IBM patients reported no cardiac symptoms. Echocardiography was normal in 16/17 IBM patients. In CMR, IBM patients had normal ejection fractions (mean LVEF 63 ± 7%) and ventricular mass. They had reduced left (mean 55 versus 88 ml) and right ventricular stroke volumes (mean 54 versus 86 ml) and increased early myocardial enhancement (pathological T1 Ratio in 44% versus 5%), as compared to age- and gender-matched controls. Since arterial hypertension was more often observed in IBM patients, hypertensive heart disease can also be causative for these changes. Late gadolinium enhancement did not differ statistically from healthy controls. There was no apparent association between elevated biomarkers, echocardiography and CMR., Conclusion: CMR revealed subtle changes in cardiac geometry and tissue characterization in IBM patients when compared to a gender- and age-matched control group. Findings in CMR indicated a higher extent of diffuse myocardial fibrosis as well as smaller left ventricular stroke volumes. These alterations may be due to a higher prevalence of arterial hypertension in the IBM cohort.

Background: The regional distribution of cerebral morphological alterations in primary lateral sclerosis (PLS) is considered to include the area III of the corpus callosum (CC)., Objective: The study was designed to investigate regional white matter (WM) alterations in the callosal area III by T1 weighted magnetic resonance imaging (T1w-MRI) data in PLS patients compared with healthy controls, in order to identify atrophy and texture changes in vivo., Methods: T1w-MRI-based white matter mapping was used to perform an operator-independent CC-segmentation for the different areas of the CC in 67 PLS patients vs 82 matched healthy controls and vs 85 ALS patients. The segmentation was followed by texture analysis of the separated CC areas for the PLS patients vs controls and vs ALS patients., Results: PLS was associated with significant atrophy in the area III of the CC (but not in the other callosal segments), while the alterations in the ALS patients were much more variable and were not significant at the group level. Furthermore, significant regional alterations of the texture parameters entropy and homogeneity in this area were shown in PLS patients and in ALS patients., Conclusions: This T1w-MRI study demonstrated focused regional CC atrophy and texture alterations limited to the callosal area III (which comprises fibers projecting into the primary motor cortices) in PLS, in comparison to a higher variability in CC size in ALS., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The criteria for assessing upper motor neuron pathology in pure lower motor neuron disease (LMND) still remain a major issue of debate with respect to the clinical classification as an amyotrophic lateral sclerosis (ALS) variant., Objective: The study was designed to investigate white matter damage by a hypothesis-guided tract-of-interest-based approach in patients with LMND compared with healthy controls and ´classical´ ALS patients in order to identify in vivo brain structural changes according to the neuropathologically defined ALS affectation pattern. Data were pooled from two previous studies at two different study sites (Ulm, Germany and Milano, Italy)., Methods: DTI-based white matter integrity mapping was performed by voxelwise statistical comparison and by a tractwise analysis of fractional anisotropy (FA) maps according to the ALS-staging pattern for 65 LMND patients (clinically differentiated in fast and slow progressors) vs. 92 matched controls and 101 ALS patients with a 'classical' phenotype to identify white matter structural alterations., Results: The analysis of white matter structural connectivity by regional FA reductions demonstrated the characteristic alteration patterns along the CST and also in frontal and prefrontal brain areas in LMND patients compared to controls and ALS. Fast progressing LMND showed substantial involvement, like in ALS, while slow progressors showed less severe alterations. In the tract-specific analysis according to the ALS-staging pattern, fast progressing LMND showed significant alterations of ALS-related tract systems as compared to slow progressors and controls., Conclusions: This study showed an affectation pattern for corticoefferent fibers in LMND with fast disease progression as defined for ALS, that way confirming the hypothesis that fast progressing LMND is a phenotypical variant of ALS.

Purpose: Frontotemporal lobar degeneration (FTLD) is a common cause of early onset dementia. Behavioral variant frontotemporal dementia (bvFTD), its most common subtype, is characterized by deep alterations in behavior and personality. In 2011, new diagnostic criteria were suggested that incorporate imaging criteria into diagnostic algorithms. The study aimed at validating the potential of imaging criteria to individually predict diagnosis with machine learning algorithms., Materials & Methods: Brain atrophy was measured with structural magnetic resonance imaging (MRI) at 3 Tesla in a multi-centric cohort of 52 bvFTD patients and 52 healthy control subjects from the German FTLD Consortium's Study. Beside group comparisons, diagnosis bvFTD vs. controls was individually predicted in each subject with support vector machine classification in MRI data across the whole brain or in frontotemporal, insular regions, and basal ganglia known to be mainly affected based on recent meta-analyses. Multi-center effects were controlled for with a new method, "leave one center out" conjunction analyses, i.e. repeatedly excluding subjects from each center from the analysis., Results: Group comparisons revealed atrophy in, most consistently, the frontal lobe in bvFTD beside alterations in the insula, basal ganglia and temporal lobe. Most remarkably, support vector machine classification enabled predicting diagnosis in single patients with a high accuracy of up to 84.6%, where accuracy was highest in a region-of-interest approach focusing on frontotemporal, insular regions, and basal ganglia in comparison with the whole brain approach., Conclusion: Our study demonstrates that MRI, a widespread imaging technology, can individually identify bvFTD with high accuracy in multi-center imaging data, paving the road to personalized diagnostic approaches in the future.

Introduction: There is some evidence that Parkinson's Disease (PD) patients have lower body weight and lower fat mass when compared to healthy subjects and that lower body weight and fat mass influence disease risk and progression. It remains unclear, however, if weight loss of fat mass loss occurs only in a subgroup of patients and whether fat distribution is altered during PD. The aim of this study was to prospectively investigate adipose tissue content and distribution in PD patients., Methods: The body fat composition of PD patients (N = 54) was compared with age matched healthy controls (N = 55) using a magnetic resonance imaging (MRI)-based method. A longitudinal MRI scan was acquired in 25 PD patients after a mean follow up period of 12 months., Results: The volume of total body fat as well as of visceral fat showed no difference between PD patients and healthy controls at baseline or at follow up. However, PD patients displayed decreased subcutaneous fat tissue (p = 0.01) and a higher visceral to subcutaneous fat ratio as compared to controls (p = 0.004). After follow up, 16 PD patients did not lose weight, while 9 PD patients lost between 0.5 and 10 kg., Conclusion: Fat distribution is altered in PD patients, with an increased ratio of visceral to subcutaneous fat., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Diffusion tensor imaging (DTI) for assessing ALS-associated white matter alterations has still not reached the level of a neuroimaging biomarker. Since large-scale multicentre DTI studies in ALS may be hampered by differences in scanning protocols, an approach for pooling of DTI data acquired with different protocols was investigated. Three hundred and nine datasets from 170 ALS patients and 139 controls were collected ex post facto from a monocentric database reflecting different scanning protocols. A 3D correction algorithm was introduced for a combined analysis of DTI metrics despite different acquisition protocols, with the focus on the CST as the tract correlate of ALS neuropathological stage 1. A homogenous set of data was obtained by application of 3D correction matrices. Results showed that a fractional anisotropy (FA) threshold of 0.41 could be defined to discriminate ALS patients from controls (sensitivity/specificity, 74%/72%). For the remaining test sample, sensitivity/specificity values of 68%/74% were obtained. In conclusion, the objective was to merge data recorded with different DTI protocols with 3D correction matrices for analyses at group level. These post processing tools might facilitate analysis of large study samples in a multicentre setting for DTI analysis at group level to aid in establishing DTI as a non-invasive biomarker for ALS.

The recent discovery of active brown fat in human adults has led to renewed interest in the role of this key metabolic tissue. This is particularly true for neurodegenerative conditions like Huntington disease (HD), an adult-onset heritable disorder with a prominent energy deficit phenotype. Current methods for imaging brown adipose tissue (BAT) are in limited use because they are equipment-wise demanding and often prohibitively expensive. This prompted us to explore how a standard MRI set-up can be modified to visualize BAT in situ by taking advantage of its characteristic fat/water content ratio to differentiate it from surrounding white fat. We present a modified MRI protocol for use on an 11.7 T small animal MRI scanner to visualize and quantify BAT in wild-type and disease model laboratory mice. In this application study using the R6/2 transgenic mouse model of HD we demonstrate a significantly reduced BAT volume in HD mice vs. matched controls (n = 5 per group). This finding provides a plausible structural explanation for the previously described temperature phenotype of HD mice and underscores the significance of peripheral tissue pathology for the HD phenotype. On a more general level, the results demonstrate the feasibility of MR-based BAT imaging in rodents and open the path towards transferring this imaging approach to human patients. Future studies are needed to determine if this method can be used to track disease progression in HD and other disease entities associated with BAT abnormalities, including metabolic conditions such as obesity, cachexia, and diabetes.

Purpose: Body fat distribution changes are associated with multiple alterations in metabolism. Therefore, the assessment of body fat compartments by MRI in animal models is a promising approach to obesity research. Standard T1-weighted (T1w) whole body MRI was used here to quantify different effects in the subcutaneous and visceral fat compartments in rats under treatment with an anorexiant., Materials and Methods: Twenty rats on a high caloric diet were investigated by the identical MRI protocol at baseline and after seven weeks. Ten rats received a treatment with sibutramine, 10 rats served as vehicle control group. To longitudinally assess body fat components, MRI analysis was used with two approaches: 2D slicewise graphic analysis (SGA) was compared with an automated 3D analysis algorithm (3DA)., Results: At the group level, fat volume differences showed a longitudinal increase of subcutaneous and visceral fat volumes for the control group, whereas the sibutramine group showed stable subcutaneous fat volumes and decrease in visceral fat volumes. SGA and 3DA volume determination showed significant correlations for subcutaneous fat volume (C=0.85, p<0.001), visceral fat volume (C=0.87, p<0.001), and total fat volume (C=0.90, p<0.001)., Conclusion: It could be demonstrated that computer-based analysis of T1w MRI could be used to longitudinally assess changes in body fat compartments in rats at the group level. In detail, it was possible to investigate the effect of sibutramine separate on the fat compartments in rats., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Background: While adiposity is a well-established risk factor for cardiovascular disease, the association between adiposity and cerebrovascular disease is not entirely understood. For example, common methods to quantify body fat volume such as body mass index, waist circumference and waist-to-hip ratio are not suitable to identify the complex distribution patterns of body fat and its relation to cerebrovascular pathology. In view of a better understanding of the association between fat distribution and cerebrovascular disorders, the aim of the study was to perform measurements of body fat distribution patterns and body fat volumes in correlation to arteriosclerosis of the brain-feeding arteries and white matter lesion load (WMLL)., Methods: In this study we performed a magnetic resonance imaging (MRI)-based volumetric differential analysis of subcutaneous and visceral body fat distribution in 25 patients with MRI-proven hyperacute ischemic stroke. For the measurement of adipose tissue volume and tissue distribution automatic labeling analysis software was used. A correlation analysis of MRI volumetric measurements of subcutaneous and visceral body fat, atherosclerotic plaque load of the brain-feeding arteries measured by computed tomography angiography, and WMLL measured by MRI volumetry of the whole brain was performed., Results: The normalized total abdominal adipose tissue and the normalized subcutaneous abdominal adipose tissue showed no significant correlation with either WMLL or total plaque volume. In contrast, the normalized visceral adipose tissue showed a significant correlation with WMLL volume. Visceral adipose tissue as a percentage of total adipose tissue showed a significant correlation with WMLL. In particular, the percentage of visceral adipose tissue rather than total body fat volume strongly correlated with atherosclerosis and ischemic cerebral lesions. Furthermore, the volume of both soft and calcified plaques correlated significantly with WMLL., Conclusions: Our results contribute to existing studies about the association of different patterns of fat distribution with atherosclerosis of the brain-feeding arteries, in particular highlighting the importance of visceral adiposity as a risk factor for cerebrovascular disease. The percentage of visceral adipose tissue in total adipose tissue has the potential of a sensitive parameter and might become a relevant new epidemiological marker, showing highly significant correlations with well-established markers of cerebrovascular disease. In conclusion, the percentage of visceral adipose tissue by itself has to be regarded as a risk factor for both small vessel cerebrovascular disease and cerebral atherosclerosis of the large-to-medium-sized arteries., (Copyright © 2013 S. Karger AG, Basel.)

Background: Computer tomography (CT) is still the fastest and most robust technique to rule out ICH in acute stroke. However CT-sensitivity for detection of ischemic stroke in the hyperacute phase is still relatively low. Moreover the validity of pure clinical judgment is diminished by several stroke imitating diseases (mimics). The "Triage® Stroke Panel", a biochemical multimarker assay, detects Brain Natriuretic Peptide (BNP), D-Dimers (DD), Matrix-Metalloproteinase-9 (MMP-9), and S100B protein and promptly generates a Multimarkerindex of these values (MMX). This index has been licensed for diagnostic purposes as it might increase the validity of the clinical diagnosis to differentiate between stroke imitating diseases and true ischemic strokes. Our aim was to prove whether the panel is a reliable indicating device for the diagnosis of ischemic stroke in a time window of 6 h to fasten the pre- and intrahospital pathway to fibrinolysis., Methods: We investigated all consecutive patients admitted to our stroke unit during a time period of 5 months. Only patients with clinical investigation, blood sample collection and MRI within six hours from symptom onset were included. Values of biochemical markers were analyzed according to the results of diffusion weighted MR-imaging. In addition MMX-values in ischemic strokes were correlated with the TOAST-criteria. For statistical analysis the SAS Analyst software was used. Correlation coefficients were analyzed and comparison tests for two or more groups were performed. Statistical significance was assumed in case of p < 0.05. Finally a ROC-analysis was performed for the MMX-Index., Results: In total 174 patients were included into this study (n = 100 strokes, n = 49 mimics, n = 25 transitoric ischemic attacks). In patients with ischemic strokes the mean NIHSS was 7.6 ± 6.2, while the mean DWI-lesion volume was 20.6 ml (range 186.9 to 4.2 ml). According to the MMX or the individual markers there was no statistically significant difference between the group of ischemic strokes and the group of mimics. Moreover the correlation of the index and the DWI-lesion-volume was poor (p = 0.2)., Conclusions: In our setting of acute MRI-proven ischemic stroke the used multimarker-assay (Triage® Stroke Panel) was not of diagnostic validity. We do not recommend to perform this assay as this might lead to a unjustified time delay.

Aim: To evaluate a standardised MRI acquisition protocol and a new image rating scale for disease severity in patients with progressive supranuclear palsy (PSP) and multiple systems atrophy (MSA) in a large multicentre study., Methods: The MRI protocol consisted of two-dimensional sagittal and axial T1, axial PD, and axial and coronal T2 weighted acquisitions. The 32 item ordinal scale evaluated abnormalities within the basal ganglia and posterior fossa, blind to diagnosis. Among 760 patients in the study population (PSP = 362, MSA = 398), 627 had per protocol images (PSP = 297, MSA = 330). Intra-rater (n = 60) and inter-rater (n = 555) reliability were assessed through Cohen's statistic, and scale structure through principal component analysis (PCA) (n = 441). Internal consistency and reliability were checked. Discriminant and predictive validity of extracted factors and total scores were tested for disease severity as per clinical diagnosis., Results: Intra-rater and inter-rater reliability were acceptable for 25 (78%) of the items scored (≥ 0.41). PCA revealed four meaningful clusters of covarying parameters (factor (F) F1: brainstem and cerebellum; F2: midbrain; F3: putamen; F4: other basal ganglia) with good to excellent internal consistency (Cronbach α 0.75-0.93) and moderate to excellent reliability (intraclass coefficient: F1: 0.92; F2: 0.79; F3: 0.71; F4: 0.49). The total score significantly discriminated for disease severity or diagnosis; factorial scores differentially discriminated for disease severity according to diagnosis (PSP: F1-F2; MSA: F2-F3). The total score was significantly related to survival in PSP (p<0.0007) or MSA (p<0.0005), indicating good predictive validity., Conclusions: The scale is suitable for use in the context of multicentre studies and can reliably and consistently measure MRI abnormalities in PSP and MSA. Clinical Trial Registration Number The study protocol was filed in the open clinical trial registry (http://www.clinicaltrials.gov) with ID No NCT00211224.

The MRI-based evaluation of the quantity and regional distribution of adipose tissue is one objective measure in the investigation of obesity. The aim of this article was to report a comprehensive and automatic analytical method for the determination of the volumes of subcutaneous fat tissue (SFT) and visceral fat tissue (VFT) in either the whole human body or selected slices or regions of interest. Using an MRI protocol in an examination position that was convenient for volunteers and patients with severe diseases, 22 healthy subjects were examined. The software platform was able to merge MRI scans of several body regions acquired in separate acquisitions. Through a cascade of image processing steps, SFT and VFT volumes were calculated. Whole-body SFT and VFT distributions, as well as fat distributions of defined body slices, were analysed in detail. Complete three-dimensional datasets were analysed in a reproducible manner with as few operator-dependent interventions as possible. In order to determine the SFT volume, the ARTIS (Adapted Rendering for Tissue Intensity Segmentation) algorithm was introduced. The advantage of the ARTIS algorithm was the delineation of SFT volumes in regions in which standard region grow techniques fail. Using the ARTIS algorithm, an automatic SFT volume detection was feasible. MRI data analysis was able to determine SFT and VFT volume percentages using new analytical strategies. With the techniques described, it was possible to detect changes in SFT and VFT percentages of the whole body and selected regions. The techniques presented in this study are likely to be of use in obesity-related investigations, as well as in the examination of longitudinal changes in weight during various medical conditions., (Copyright © 2010 John Wiley & Sons, Ltd.)

Neuroimaging findings in hereditary spastic paraparesis (HSP), especially in complicated HSP (cHSP), are heterogenous. This study aimed to investigate possible in vivo morphological alterations of the whole brain and the amygdala in cHSP as a correlate of cognitive impairment in contrast to pure variants (pHSP). Amygdalar and whole brain volumes of 33 HSP patients (21 pHSP and 12 cHSP) were measured using three-dimensional magnetic resonance imaging (MRI) data sets by region of interest-based volumetry. A neuropsychological test battery was also performed. A significant reduction in whole brain volume compared with the controls, as well as significant correlations with reduced amygdalar volume and a worse neuropsychological test performance was observed only in cHSP patients. Our findings of disproportional amygdalar atrophy only in cHSP substantiate the association of morphologically assessable cerebral degeneration with cognitive impairment in cHSP., (Copyright 2010 S. Karger AG, Basel.)

With non-invasive functional imaging techniques, neuroscience has reached a new era of connecting anatomy and function. Although other techniques bear the advantage of either higher temporal or spatial resolution, functional magnetic resonance imaging (fMRI) is the most widely used non-invasive brain imaging technique. fMRI provides an acceptable balance between low patient load and high information capacity with good spatial resolution, making it ideal for clinical research in patients with physical restrictions like those with ALS. Most fMRI studies have provided evidence of a spatial shift of function in motor and extramotor areas in ALS patients. Furthermore, MRI-based functional imaging has supported the clinical findings of frontal cortical involvement not only in patients with ALS/dementia complex but also in patients with ALS and sub-clinical cognitive impairment. Functional MRI will identify the preserved but non-executable functions in ALS patients in the end stage and will set the direction for a new way of thinking on the functional capacities of these patients which will have a major impact on our way of thinking about end-of-life decisions.

Objective: To assess the effect of a single levodopa dose (200 mg levodopa, 50 mg carbidopa=sdLD) on cortical and subcortical motor-circuit activation during bimanual grip force in patients with Parkinson's disease (PD)., Patients and Methods: We studied 12 right-handed patients with PD (Hoehn-Yahr stages I-II) after a period of at least 12 h without medication (OFF state) and a second time 1 h after oral administration of sdLD (ON state) using functional magnetic resonance imaging (fMRI). Blood-oxygenation-level-dependency (BOLD) fMRI was measured while participants underwent two unilateral and two bimanual grip force movements with a defined movement amplitude and force (10N) in a block design. 12 age matched healthy subjects were studied as controls (without administration of sdLD)., Results: Bimanual grip force tasks activated a specific pattern of cortical and subcortical structures in all patients during the OFF state and after levodopa administration with statistically significant differences in putamen and thalamus comparing the OFF and ON condition. In contrast, no such significant changes were observed in cortical structures. Between-group analysis revealed higher putaminal activity in controls compared to OFF state in bimanual tasks, while these differences disappeared after administration of levodopa., Conclusions: Our results indicate that the putamen and thalamus are the regions within the cortico-subcortical motor-circuit with most prominent response to levodopa. In our study, cortical motor areas did not respond to levodopa as one could have expected from previous studies. These findings contribute to the increasing evidence that an extended model of the underlying pathophysiology of motor dysfunctions in PD is warranted.

Three-dimensional magnetic resonance imaging of the brain was analyzed using optimized voxel-based morphometry in 21 patients with pure hereditary spastic paraparesis (pHSP) and 12 patients with complicated HSP (cHSP). PHSP patients showed only small regional grey matter volume reduction, whereas significantly decreased grey matter volumes were localized pericentrally in cHSP. In the white matter, several small areas of regional volume reduction were observed in the pHSP patients, whereas the cHSP group exhibited large robust volume reduction involving the entire corpus callosum, a result that was reproduced by an additional region-based MRI analysis. It could be demonstrated that the topography of cerebral volume changes differed markedly in pHSP or cHSP at group level. Corpus callosum thinning seems to be a general feature of cHSP.

Background: Cortical networks underlying motor imagery are functionally close to motor performance networks and can be activated by patients with severe motor disabilities., Objective: The aim of the study was to examine the longitudinal effect of progressive motoneuron degeneration on cortical representation of motor imagery and function in amyotrophic lateral sclerosis., Methods: The authors studied 14 amyotrophic lateral sclerosis patients and 15 healthy controls and a subgroup of 11 patients and 14 controls after 6 months with a grip force paradigm comprising imagery and execution tasks using functional magnetic resonance imaging., Results: Motor imagery activated similar neural networks as motor execution in amyotrophic lateral sclerosis patients and healthy subjects in the primary motor (BA 4), premotor, and supplementary motor (BA 6) cortex. Amyotrophic lateral sclerosis patients presented a stronger response within premotor and primary motor areas for imagery and execution compared to controls. After 6 months, these differences persisted with additional activity in the precentral gyrus in patients as well as in a frontoparietal network for motor imagery, in which activity increased with impairment., Conclusion: The findings suggest an ongoing compensatory process within the higher order motor-processing system of amyotrophic lateral sclerosis patients, probably to overcome loss of function in primary motor and motor imagery-specific networks. The increased activity in precentral and frontoparietal networks in motor imagery might be used to control brain-computer interfaces to drive communication and limb prosthetic devices in patients with loss of motor control such as severely disabled amyotrophic lateral sclerosis patients in a locked-in-like state.

Background: Evidence for extra-motor involvement in non-demented patients with amyotrophic lateral sclerosis (ALS) has been provided by multiple studies, in particular neuropathological studies have demonstrated neuronal loss in the amygdala. The aim of this study was to investigate possible alterations of amygdala volumes in vivo., Methods: Twenty-two moderately disabled patients with definite ALS without cognitive or behavioural deficits and 22 age-matched healthy controls were included. Amygdala and total brain volumes were measured by region-of-interest-based volumetry in 3-D MRI., Results: A trend was observed with reduced amygdala size in the ALS group, since mean absolute and brain size-corrected amygdala volumes were 6.9% and 7.6% lower in the patient group compared to those in normal controls (P = 0.086 and P = 0.110), respectively., Conclusion: Volumetrically identifiable alterations of the amygdala can be mapped in vivo and may be associated with psychopathological findings in later stages of ALS.

As part of the frontotemporal dementias, primary progressive aphasia (PPA) is typically characterized by nonfluent speech with paraphasias, but there is growing evidence that also a fluent variant of PPA exists. We describe a patient suffering from PPA who adds to the broad clinical spectrum of this disorder. Moreover, we report for the first time that PPA may be associated with severe impairment in meaningful nonverbal sound recognition (environmental sound agnosia). These neuropsychological findings were found to be associated with distinct focal alterations in functional and structural neuroimaging.

In ALS, advanced magnetic resonance imaging (MRI) techniques are increasingly used to investigate the underlying pathology. In this study, the technique of voxel-based morphometry (VBM) was applied to 3-D MRI data in ALS patients to localize regional grey and white matter changes. Twenty-two ALS patients (mean age 58+/-9 years) with clinically definite ALS by revised El Escorial criteria were studied. None of the patients had any signs of associated frontotemporal dementia. High-resolution 3-D MRI data sets of the whole brain, collected on a 1.5 T scanner, were analysed by statistical parametric mapping (SPM) and VBM in comparison to an age-matched normal data base consisting of 22 healthy volunteers (mean age 59+/-11 years), for grey matter and white matter segments separately. Global brain atrophy was assessed by calculation of brain parenchymal fractions (BPF). In ALS patients, BPF were significantly reduced compared to controls (p = 0.0003), indicating global brain atrophy. Regional decreases of grey matter density were found in the ALS patients at corrected p<0.01 in the right-hemispheric primary motor cortex (area of the highest Z-score) and in the left medial frontal gyrus. Furthermore, regional white matter alterations were observed along the corticospinal tracts bilaterally and in multiple smaller areas including corpus callosum, cerebellum, frontal and occipital subcortical regions. Besides considerable global atrophy in ALS, the topography of ALS-associated cerebral morphological changes could be mapped using VBM, in particular white matter signal changes along the bilateral corticospinal tracts, but also in extra-motor areas. VBM might be a potential tool to visualize disease progression in future longitudinal studies.

Mice over-expressing the mutant human G93A-SOD1 are widely used as an animal model of amyotrophic lateral sclerosis (ALS). ALS is characterized by progressive degeneration of motor neurons in the motor cortex, brain stem and spinal cord. The underlying mechanisms for the selective death of motor neurons are still uncertain. To study factors that cause selective neuron degeneration or therapeutic approaches to delay the progression of the disease, a method is required to monitor the state of motor neurons under in-vivo conditions. Here, we demonstrate that in G93A-SOD1 mice the MRI signal intensities of nucleus V, VII, XII, and nucleus ambiguus show a time-dependent increase starting around day 90, parallel to first behavioral signs of a motoneuron disorder.

The extent of brain atrophy was determined in 33 patients with multiple sclerosis (MS) and in 60 healthy subjects (21-76 years) by calculating brain parenchymal fractions (BPF, the ratio of brain parenchymal to intracranial volume) from 3D MRI. Within the normal data base, subjects at higher ages showed significantly lower BPF values. In younger MS patients, BPF was significantly decreased compared with age-matched controls (20-29 years, p= 0.0022; 30-39 years, =p 0.0001; 40-49 years,p = 0.0444) and was significantly correlated with disease duration and disease severity, but not with the number of detectable MS lesions. Determination of age-related BPF demonstrated significant brain atrophy in early MS and can be considered as a useful biological marker for monitoring MS.

Background: Paraneoplastic ischemic stroke has a poor prognosis. We have recently reported an algorithm based on the number of ischemic territories, C-reactive protein (CRP), lactate dehydrogenase (LDH), and granulocytosis to predict the underlying active cancer in a case-control setting. However, co-occurrence of cancer and stroke might also be merely incidental. Objective: To detect cancer-associated ischemic stroke in a large, unselected cohort of consecutive stroke patients by detailed analysis of ischemic stroke associated with specific cancer subtypes and comparison to patients with bacterial endocarditis. Methods: Retrospective single-center cohort study of consecutive 1612 ischemic strokes with magnetic resonance imaging, CRP, LDH, and relative granulocytosis data was performed, including identification of active cancers, history of now inactive cancers, and the diagnosis of endocarditis. The previously developed algorithm to detect paraneoplastic cancer was applied. Tumor types associated with paraneoplastic stroke were used to optimize the diagnostic algorithm. Results: Ischemic strokes associated with active cancer, but also endocarditis, were associated with more ischemic territories as well as higher CRP and LDH levels. Our previous algorithm identified active cancer-associated strokes with a specificity of 83% and sensitivity of 52%. Ischemic strokes associated with lung, pancreatic, and colorectal (LPC) cancers but not with breast and prostate cancers showed more frequent and prominent characteristics of paraneoplastic stroke. A multiple logistic regression model optimized to identify LPC cancers detected active cancer with a sensitivity of 77.8% and specificity of 81.4%. The positive predictive value (PPV) for all active cancers was 13.1%. Conclusion: Standard clinical examinations can be employed to identify suspect paraneoplastic stroke with an adequate sensitivity, specificity, and PPV when it is considered that the association of ischemic stroke with breast and prostate cancers in the stroke-prone elderly population might be largely incidental. [ABSTRACT FROM AUTHOR]

Progressive supranuclear palsy (PSP) is a neurodegenerative disease characterized by four-repeat tau deposition in various cell types and anatomical regions, and can manifest as several clinical phenotypes, including the most common phenotype, Richardson's syndrome. The limited availability of biomarkers for PSP relates to the overlap of clinical features with other neurodegenerative disorders, but identification of a growing number of biomarkers from imaging is underway. One way to increase the reliability of imaging biomarkers is to combine different modalities for multimodal imaging. This review aimed to provide an overview of the current state of PSP hybrid imaging by combinations of positron emission tomography (PET) and magnetic resonance imaging (MRI). Specifically, combined PET and MRI studies in PSP highlight the potential of [18F]AV-1451 to detect tau, but also the challenge in differentiating PSP from other neurodegenerative diseases. Studies over the last years showed a reduced synaptic density in [11C]UCB-J PET, linked [11C]PK11195 and [18F]AV-1451 markers to disease progression, and suggested the potential role of [18F]RO948 PET for identifying tau pathology in subcortical regions. The integration of quantitative global and regional gray matter analysis by MRI may further guide the assessment of reduced cortical thickness or volume alterations, and diffusion MRI could provide insight into microstructural changes and structural connectivity in PSP. Challenges in radiopharmaceutical biomarkers and hybrid imaging require further research targeting markers for comprehensive PSP diagnosis. [ABSTRACT FROM AUTHOR]

Background: The characterisation of presymptomatic disease-burden patterns in asymptomatic mutation carriers has a dual academic and clinical relevance. The understanding of disease propagation mechanisms is of considerable conceptual interests, and defining the optimal time of pharmacological intervention is essential for improved clinical trial outcomes. Methods: In a prospective, multimodal neuroimaging study, 22 asymptomatic C9orf72 GGGGCC hexanucleotide repeat carriers, 13 asymptomatic subjects with SOD1, and 54 "gene-negative" ALS kindreds were enrolled. Cortical and subcortical grey matter alterations were systematically appraised using volumetric, morphometric, vertex, and cortical thickness analyses. Using a Bayesian approach, the thalamus and amygdala were further parcellated into specific nuclei and the hippocampus was segmented into anatomically defined subfields. Results: Asymptomatic GGGGCC hexanucleotide repeat carriers in C9orf72 exhibited early subcortical changes with the preferential involvement of the pulvinar and mediodorsal regions of the thalamus, as well as the lateral aspect of the hippocampus. Volumetric approaches, morphometric methods, and vertex analyses were anatomically consistent in capturing focal subcortical changes in asymptomatic C9orf72 hexanucleotide repeat expansion carriers. SOD1 mutation carriers did not exhibit significant subcortical grey matter alterations. In our study, none of the two asymptomatic cohorts exhibited cortical grey matter alterations on either cortical thickness or morphometric analyses. Discussion: The presymptomatic radiological signature of C9orf72 is associated with selective thalamic and focal hippocampal degeneration which may be readily detectable before cortical grey matter changes ensue. Our findings confirm selective subcortical grey matter involvement early in the course of C9orf72-associated neurodegeneration. [ABSTRACT FROM AUTHOR]

Background: For recurrent high-grade glioma, especially glioblastoma, no standard of care treatment exists. Due to the prolongation of progression-free survival and a cortiocosteroid-sparing effect, bevacizumab is often used in this condition. Despite initial clinical responses, there is growing evidence that bevacizumab may potentiate microstructural alterations which may cause cognitive decline, mostly affecting learning and memory. Methods: To investigate bevacizumab-associated microstructural damage of defined regions of interest (ROIs) in the white matter, diffusion tensor imaging (DTI) was performed in 10 patients with a case history or third-party report for neurological dysfunction concerning cognitive performance. Serial DTI data before and under bevacizumab were collected and longitudinal changes of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) were assessed in mesiotemporal (hippocampal), frontal, and occipital regions. Results: The longitudinal DTI data under bevacizumab compared to DTI prior to bevacizumab demonstrated a significant decrease in FA and increase in AD and RD both in mesiotemporal (hippocampal) regions and in frontal regions, whereas occipital regions showed no significant alterations in DTI metrics. Conclusion: The regionally impaired microstructure in mesiotemporal (hippocampal) regions and in frontal regions is in line with the fact that neurocognitive impairment in learning and memory is mostly related to hippocampal integrity and attentional control in frontal regions. Further studies could investigate the potential of DTI to assess bevacizumab-associated microstructural damages in vulnerable brain regions. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) allows the in vivo imaging of pathological white matter alterations, either with unbiased voxel-wise or hypothesis-guided tract-based analysis. Alterations of diffusion metrics are indicative of the cerebral status of patients with amyotrophic lateral sclerosis (ALS) at the individual level. Using machine learning (ML) models to analyze complex and high-dimensional neuroimaging data sets, new opportunities for DTI-based biomarkers in ALS arise. This review aims to summarize how different ML models based on DTI parameters can be used for supervised diagnostic classifications and to provide individualized patient stratification with unsupervised approaches in ALS. To capture the whole spectrum of neuropathological signatures, DTI might be combined with additional modalities, such as structural T1w 3-D MRI in ML models. To further improve the power of ML in ALS and enable the application of deep learning models, standardized DTI protocols and multi-center collaborations are needed to validate multimodal DTI biomarkers. The application of ML models to multiparametric MRI/multimodal DTI-based data sets will enable a detailed assessment of neuropathological signatures in patients with ALS and the development of novel neuroimaging biomarkers that could be used in the clinical workup. [ABSTRACT FROM AUTHOR]

Background: The hyperintense acute reperfusion marker (HARM) describes a phenomenon with a hyperintense signal in the subarachnoid space in Fluid-Attenuated Inversion Recovery (FLAIR) magnetic resonance imaging (MRI) sequences, presumably based on blood–brain barrier breakdown in acute stroke with reperfusion. However, this imaging phenomenon was described in other medical conditions. Aim: Determination of the prevalence and associated clinical findings of this phenomenon in a large sample of patients with different neurological conditions. Methods: This is retrospective, single-center, observational study of 23,948 cerebral MRIs acquired in a Neurological University Clinic over 5 years. The prevalence of HARM, the underlying diagnosis, and damage pattern were examined by chart analysis; MRI was analyzed regarding the type of acute lesions, extent of microangiopathic lesions, and whether gadolinium-based contrast agent (GBCA) was given. Results: Among the MRI data, 84 images (0.35%) from 61 patients were HARM-positive without a subarachnoid signal abnormality in any other sequence. Etiologies were heterogeneous; 35 patients had a cerebrovascular disease (CVD; 19 patients received recanalization therapy), 12 patients had an inflammatory central nervous system (CNS) disease and 14 patients had epilepsy. GBCA was applied to 64% of the patients. Conclusion: HARM was a rare radiological finding in a range of different neurological pathologies, not limited to stroke, or to previous reperfusion therapy and was not dependent on previous GBCA administration. Our data suggest that the term is too narrow in terms of the concepts of the underlying pathology. We propose to use the term FLA IR S ubarachnoid H yperintensity ("FLASH") phenomenon which might better reflect the observation that the radiological sign can be associated with a variety of central neurological conditions without a straightforward association with therapy. [ABSTRACT FROM AUTHOR]

Cerebrospinal fluid (CSF) and serum biomarkers are critical for clinical decision making in neurological diseases. In cerebral small vessel disease (CSVD), white matter hyperintensities (WMH) are an important neuroimaging biomarker, but more blood-based biomarkers capturing different aspects of CSVD pathology are needed. In 42 sporadic CSVD patients, we prospectively analysed WMH on magnetic resonance imaging (MRI) and the biomarkers neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), chitinase3-like protein 1 (CHI3L1), Tau and Aβ1-42 in CSF and NfL and GFAP in serum. GFAP and CHI3L1 expression was studied in post-mortem brain tissue in additional cases. CSVD cases with higher serum NfL and GFAP levels had a higher modified Rankin Scale (mRS) and NIHSS score and lower CSF Aβ1-42 levels, whereas the CSF NfL and CHI3L1 levels were positively correlated with the WMH load. Moreover, the serum GFAP levels significantly correlated with the neurocognitive functions. Pathological analyses in CSVD revealed a high density of GFAP-immunoreactive fibrillary astrocytic processes in the periventricular white matter and clusters of CHI3L1-immunoreactive astrocytes in the basal ganglia and thalamus. Thus, besides NfL, serum GFAP is a highly promising fluid biomarker of sporadic CSVD, because it does not only correlate with the clinical severity but also correlates with the cognitive function in patients. [ABSTRACT FROM AUTHOR]

Background: Intracranial hemorrhage (ICH) is associated with high mortality and morbidity, especially in patients under anticoagulative treatment. Andexanet alfa (AA) is a modified recombinant form of human factor Xa (FXa) developed for reversal of FXa-inhibitors, e.g., in the event of ICH, but experience is still limited. Methods: This monocentric retrospective observational cohort study included 46 patients with acute FXa-inhibitor-associated non-traumatic ICH (FXa-I-ICH) of whom 23 were treated with AA within 12 h after symptom onset, compared to 23 patients with usual care (UC). Volumetrically analyzed hematoma expansion (HE) in brain imaging, clinical outcome and incidence of adverse events were analyzed. Results: All patients (mean age 79.8 ± 7.2 years) were effectively anticoagulated. The cohort included severely ill patients with large hematoma volumes (median 20.4, IQR 7.8–39.0 mL). Efficacy, as assessed by HE in imaging, was very good in the AA-group. There was no (0.0%) relevant HE (>33%) in contrast to UC-group (26.1%). Nevertheless, we observed a high incidence of thromboembolic events (30.4% vs. 4.4%) and non-favorable outcomes (death/palliative condition) in 43.5% vs. 26.1%. Conclusions: There was no HE in the volumetric neuroimaging assessment in the AA-group, but clinical outcomes remained often worse. Large randomized trials for the use of AA in patients with acute FXa-inhibitor-associated ICH are needed to investigate the clinical outcome in consideration of the rates of thromboembolism. [ABSTRACT FROM AUTHOR]

The potential of multiparametric quantitative neuroimaging has been extensively discussed as a diagnostic tool in amyotrophic lateral sclerosis (ALS). In the past, the integration of multimodal, quantitative data into a useful diagnostic classifier was a major challenge. With recent advances in the field, machine learning in a data driven approach is a potential solution: neuroimaging biomarkers in ALS are mainly observed in the cerebral microstructure, with diffusion tensor imaging (DTI) and texture analysis as promising approaches. We set out to combine these neuroimaging markers as age-corrected features in a machine learning model with a cohort of 502 subjects, divided into 404 patients with ALS and 98 healthy controls. We calculated a linear support vector classifier (SVC) which is a very robust model and then verified the results with a multilayer perceptron (MLP)/neural network. Both classifiers were able to separate ALS patients from controls with receiver operating characteristic (ROC) curves showing an area under the curve (AUC) of 0.87–0.88 ("good") for the SVC and 0.88–0.91 ("good" to "excellent") for the MLP. Among the coefficients of the SVC, texture data contributed the most to a correct classification. We consider these results as a proof of concept that demonstrated the power of machine learning in the application of multiparametric quantitative neuroimaging data to ALS. [ABSTRACT FROM AUTHOR]