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Purpose Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. Methods Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. Results There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. Conclusion PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Purpose To systematically review and evaluate the methodological quality of studies using radiomics for diagnostic and predictive purposes in patients with intracranial meningioma. To perform a meta-analysis of machine learning studies for the prediction of intracranial meningioma grading from pre-operative brain MRI. Methods Articles published from the year 2000 on radiomics and machine learning applications in brain imaging of meningioma patients were included. Their methodological quality was assessed by three readers with the radiomics quality score, using the intra-class correlation coefficient (ICC) to evaluate inter-reader reproducibility. A meta-analysis of machine learning studies for the preoperative evaluation of meningioma grading was performed and their risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool. Results In all, 23 studies were included in the systematic review, 8 of which were suitable for the meta-analysis. Total (possible range, −8 to 36) and percentage radiomics quality scores were respectively 6.96 ± 4.86 and 19 ± 13% with a moderate to good inter-reader reproducibility (ICC = 0.75, 95% confidence intervals, 95%CI = 0.54–0.88). The meta-analysis showed an overall AUC of 0.88 (95%CI = 0.84–0.93) with a standard error of 0.02. Conclusions Machine learning and radiomics have been proposed for multiple applications in the imaging of meningiomas, with promising results for preoperative lesion grading. However, future studies with adequate standardization and higher methodological quality are required prior to their introduction in clinical practice.

Objective The aim of this study was to compare the function of the glymphatic system in patients with status epilepticus (SE) with that in healthy controls by diffusion tensor image analysis along the perivascular space (DTI-ALPS) method. We also investigated the association between glymphatic system function and the clinical characteristics of SE. Methods We retrospectively enrolled 28 patients with SE and 31 healthy controls matched for age and sex. All study participants underwent diffusion tensor imaging using the same 3-T MRI scanner, and the DTI-ALPS index was calculated. We compared the DTI-ALPS index between the SE group and the control group. We also evaluated the associations of the DTI-ALPS index with etiology and type of SE, age, putative duration of seizure, time interval until MRI, seizure-related changes on diffusion-weighted imaging, and any previous structural lesions. Results The DTI-ALPS index was significantly lower in the SE group than in the control group (1.462 ± 0.297 vs. 1.632 ± 0.270, p  = 0.026) and was negatively correlated with age ( r  =  − 0.280, p  = 0.032) in the SE group. However, there were no significant between-group differences in the DTI-ALPS index according to other clinical factors. Significance The finding of a significantly lower DTI-ALPS index in the SE group suggests that the glymphatic system is impaired in patients with SE. DTI-ALPS is a useful tool for evaluation of the function of the glymphatic system in these patients.

Purpose Glymphatic system dysfunction has been reported in animal models of traumatic brain injury (TBI). This study aimed to evaluate the activity of the human glymphatic system using the non-invasive Diffusion Tensor Image-Analysis aLong the Perivascular Space (DTI-ALPS) method in patients with TBI. Methods A total of 89 patients with TBI (June 2018 to May 2020) were retrospectively enrolled, and 34 healthy volunteers were included who had no previous medical or neurological disease. Magnetic resonance imaging (MRI) with DTI was performed, and the ALPS index was calculated to evaluate the glymphatic system’s activity. Wilcoxon rank-sum test was used to compare the ALPS index between patients with TBI and healthy controls. ANOVA was done to compare the ALPS index among controls and patients with mild/moderate-to-severe TBI. Multivariate logistic regression analyses were used to identify independent clinical and radiological factors associated with the ALPS index. The correlation between Glasgow Coma Scale (GCS) score and the ALPS index was also assessed. Results The ALPS index was significantly lower in patients with TBI than in healthy controls (median, 1.317 vs. 1.456, P  < 0.0001). There were significant differences in the ALPS index between healthy controls and patients with mild/moderate-to-severe TBI (ANOVA, P  < 0.001). The presence of subarachnoid hemorrhage ( P  = 0.004) and diffuse axonal injury ( P  = 0.001) was correlated with a lower ALPS index in the multivariate analysis. There was a weak positive correlation between the ALPS index and GCS scores ( r  = 0.242, P  = 0.023). Conclusions The DTI-ALPS method is useful for evaluating glymphatic system impairment and quantifying its activity in patients with TBI.

Purpose To explore the functional connectivity (FC) between the bilateral thalamus and the other brain regions in patients with vestibular migraine (VM). Methods Resting-state fMRI and 3D-T1 data were collected from 37 patients with VM during the interictal period and 44 age-, gender-, and years of education-matched healthy controls (HC). The FC of the bilateral thalamus was analyzed using a standard seed-based whole-brain correlation method. Furthermore, the correlations between thalamus FC and clinical characteristics of patients were investigated using Pearson’s partial correlation. Results Compared with HC, VM patients showed decreased FC between the left thalamus and the left anterior cingulate cortex (ACC), bilateral insular and right supplementary motor cortex. We also observed decreased FC between the right thalamus and the left insular and ACC in VM patients. Furthermore, patients with VM also exhibited increased FC between the left thalamus and the right precuneus and middle frontal gyrus, between the right thalamus and superior parietal lobule. FC between the right thalamus and the left insular was negatively correlated with disease duration ( p  = 0.019, r =  − 0.399), FC between the left thalamus and the left ACC was negatively correlated with HIT-6 score ( p  = 0.004, r =  − 0.484). Conclusion VM patients showed altered FC between thalamus and brain regions involved in pain, vestibular and visual processing, which are associated with specific clinical features. Specifically, VM patients showed reduced thalamo-pain and thallamo-vestibular pathways, while exhibited enhanced thalamo-visual pathway, which provided first insight into the underlying functional brain connectivity in VM patients.

Background and objective Cervical spondylosis (CS) is often accompanied by persistent cervical pain, and psychological complications including depression and anxiety, which aggravate pain. Past studies have revealed brain alterations in chronic pain patients. However, the cortical mechanism for NSAID (non-steroidal anti-inflammatory drug) responders relative to non-responders is still lacking. Therefore, we aimed to investigate the brain functional differences between responders to NSAID relative to non-responders using amplitude of low-frequency fluctuation (ALFF) and dynamic functional connectivity variance (DFCV). To our knowledge, our study is the first to investigate the DFCV in CS patients. Materials and methods We first explored the differences in psychological inventories in CS patients who respond to NSAID vs non-responders. The voxel-wise ALFF was calculated and compared between CS patients and healthy controls. The ALFF within the resultant clusters were extracted and compared between responders and non-responders. DFCV among the resulting clusters was compared in responders vs non-responders. Results We found that (1) compared to responders, non-responders exhibited higher levels of anxiety and depression; (2) relative to healthy controls, CS patients exhibited altered ALFF within the middle cingulate cortice (MCC), cerebellum, and middle frontal gyrus (MFG); (3) moreover, compared with responders, non-responders exhibited lower ALFF within MCC; furthermore, non-responders also exhibited increased DFCV between MCC and cerebellum, and between MCC and MFG. Conclusion Our data indicate that psychological comorbidities (e.g., anxiety) influence response to NSAID in CS patients. Relative to NSAID responders, non-responders had altered MCC function, which may be associated with anxiety in CS patients.

  Purpose To characterize the altered brain function in patients with vestibular migraine (VM) using resting-state functional magnetic resonance imaging (fMRI). Methods In this prospective study, fMRI images as well as clinical characteristics and behavioral scales were collected from 40 VM patients and 40 healthy controls (HC). All patients received neurological, neuro-otological, and conventional MRI examinations to exclude peripheral vestibular lesions, focal lesions, and other neurological diseases. Seed-based (bilateral parietal operculum cortex 2, OP2) functional connectivity (FC) and independent component analysis (ICA)-based functional network connectivity (FNC) were performed to investigate the brain functional changes in patients with VM. Additionally, the correlations between the altered FC/FNC and behavioral results were analyzed. Results Compared with HC, patients with VM showed increased FC between the left OP2 and right precuneus and exhibited decreased FC between the left OP2 and left anterior cingulate cortex. We also observed increased FC between the right OP2 and regions of the right middle frontal gyrus and bilateral precuneus, as well as decreased FC between the bilateral OP2. Furthermore, patients with VM showed decreased FNC between visual network (VN) and networks of auditory and default mode, and exhibited increased FNC between VN and executive control network. A correlation analysis found that FC between the left OP2 and right precuneus was positively correlated with scores of dizziness handicap inventory (DHI) in patients with VM. Conclusion The present study demonstrated altered brain function in patients with VM.

Purpose Spatial smoothing is an essential pre-processing step in the process of analysing functional magnetic resonance imaging (fMRI) data, both during an experimental task or during resting-state fMRI (rsfMRI). The main benefit of this spatial smoothing step is to artificially increase the signal-to-noise ratio of the fMRI signal. Previous fMRI studies have investigated the impact of spatial smoothing on task fMRI data, while rsfMRI studies usually apply the same analytical process used for the task data. However, this study investigates changes in different rsfMRI analyses, such as ROI-to-ROI, seed-to-voxels and ICA analyses. Methods Nineteen healthy volunteers were scanned using rsfMRI with three applied smoothing kernels: 0 mm, 4 mm and 8 mm. Appropriate statistical comparisons were made. Results The findings showed that spatial smoothing has a greater effect on rsfMRI data when analysed using seed-to-voxel-based analysis. The effect was less pronounced when analysing data using ROI-ROI or ICA analyses. The results demonstrated that even when analysing the data without the application of spatial smoothing, the results were significant compared with data analysed using a typical smoothing kernel. However, data analysed with lower-smoothing kernels produced greater negative correlations, particularly with the ICA analysis. Conclusion The results suggest that a medium smoothing kernel (around 4 mm) may be preferable, as it is comparable with the 8 mm kernel in all of the analyses performed. It is also recommended that the researchers consider analysing the data using two different smoothing kernels, as this will help to confirm the significance of the results and avoid overestimating the findings.

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.

Purpose Previous functional magnetic resonance imaging studies have substantiated changes in multiple brain regions of functional activity in patients with vestibular migraine. However, few studies have assessed functional connectivity within and between specific brain networks in vestibular migraine. Methods Our study subjects included 37 patients with vestibular migraine and 35 healthy controls, and the quality of magnetic resonance images of all subjects met the requirements. Independent component analysis was performed to identify resting-state networks, and we investigated changes in functional connectivity patterns within and between brain networks. We also used Pearson correlation analysis to assess the relationship between changes in functional connectivity and the clinical features of patients with vestibular migraine. Results A total of 14 independent components were identified. Compared to healthy controls, patients with vestibular migraine exhibited decreased intra-network functional connectivity in the executive control network and weakened functional connectivity between the anterior default mode network and the ventral attention network, between the anterior default mode network and the salience network, and between the right frontoparietal network and the auditory network. Moreover, the functional connectivity between the salience network and the dorsal attention network was increased. However, the functional connectivity of networks and clinical characteristics of vestibular migraine patients did not demonstrate any significant correlation. Conclusion In conclusion, our study suggested that patients with vestibular migraine also have abnormal multisensory integration during the interictal period and that the attention network is involved. Changing within- and between-network functional connectivity may indicate that vestibular cortex areas are in a sensitive state.