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Dementia is one of the most common neurological syndromes in the world. Usually, diagnoses are made based on paper-and-pencil tests and scored depending on personal judgments of experts. This technique can introduce errors and has high inter-rater variability. To overcome these issues, we present an automatic assessment of the widely used paper-based clock-drawing test by means of deep neural networks. Our study includes a comparison of three modern architectures: VGG16, ResNet-152, and DenseNet-121. The dataset consisted of 1315 individuals. To deal with the limited amount of data, which also included several dementia types, we used optimization strategies for training the neural network. The outcome of our work is a standardized and digital estimation of the dementia screening result and severity level for an individual. We achieved accuracies of 96.65% for screening and up to 98.54% for scoring, overcoming the reported state-of-the-art as well as human accuracies. Due to the digital format, the paper-based test can be simply scanned by using a mobile device and then be evaluated also in areas where there is a staff shortage or where no clinical experts are available.

Space-occupying, malignant middle cerebral artery (MCA) infarctions are still one of the most devastating forms of ischaemic stroke, with a mortality of up to 80% in untreated patients. An early diagnosis is essential and depends on CT and MRI to aid the prediction of a malignant course. Several pharmacological strategies have been proposed but the efficacy of these approaches has not been supported by adequate evidence from clinical trials and, until recently, treatment of malignant MCA infarctions has been a major unmet need. Over the past 3 years, results from randomised controlled trials and their pooled analyses have provided evidence that an early hemicraniectomy leads to a substantial decrease in mortality at 6 and 12 months and is likely to improve functional outcome. Hemicraniectomy is now in routine use for the clinical management of malignant MCA infarction in patients younger than 60 years of age. However, there are still important questions about the individual indication for decompressive surgery, particularly with regard to the ideal timing of hemicraniectomy, a potential cut-off age for the procedure, the hemisphere affected, and ethical considerations about functional outcome in surviving patients.

Purpose Various software applications offer support in the diagnosis of acute ischemic stroke (AIS), yet it remains unclear whether the performance of these tools is comparable to each other. Our study aimed to evaluate three fully automated software applications for Alberta Stroke Program Early CT (ASPECT) scoring (Syngo.via Frontier ASPECT Score Prototype V2, Brainomix e-ASPECTS® and RAPID ASPECTS) in AIS patients. Methods Retrospectively, 131 patients with large vessel occlusion (LVO) of the middle cerebral artery or the internal carotid artery, who underwent endovascular therapy (EVT), were included. Pre-interventional non-enhanced CT (NECT) datasets were assessed in random order using the automated ASPECT software and by three experienced neuroradiologists in consensus. Interclass correlation coefficient (ICC), Bland-Altman, and receiver operating characteristics (ROC) were applied for statistical analysis. Results Median ASPECTS of the expert consensus reading was 8 (7–10). Highest correlation was between the expert read and Brainomix ( r  = 0.871 (0.818, 0.909), p  < 0.001). Correlation between expert read and Frontier V2 ( r  = 0.801 (0.719, 0.859), p  < 0.001) and between expert read and RAPID ( r  = 0.777 (0.568, 0.871), p  < 0.001) was high, respectively. There was a high correlation among the software tools (Frontier V2 and Brainomix: r  = 0.830 (0.760, 0.880), p  < 0.001; Frontier V2 and RAPID: r  = 0.847 (0.693, 0.913), p  < 0.001; Brainomix and RAPID: r  = 0.835 (0.512, 0.923), p  < 0.001). An ROC curve analysis revealed comparable accuracy between the applications and expert consensus reading (Brainomix: AUC = 0.759 (0.670–0.848), p  < 0.001; Frontier V2: AUC = 0.752 (0.660–0.843), p  < 0.001; RAPID: AUC = 0.734 (0.634–0.831), p  < 0.001). Conclusion Overall, there is a convincing yet developable grade of agreement between current ASPECT software evaluation tools and expert evaluation with regard to ASPECT assessment in AIS.

Acute ischemic stroke (AIS) is a leading global cause of mortality and morbidity. Improving long-term outcome predictions after thrombectomy can enhance treatment quality by supporting clinical decision-making. With the advent of interpretable deep learning methods in recent years, it is now possible to develop trustworthy, high-performing prediction models. This study introduces an uncertainty-aware, graph deep learning model that predicts endovascular thrombectomy outcomes using clinical features and imaging biomarkers. The model targets long-term functional outcomes, defined by the three-month modified Rankin Score (mRS), and mortality rates. A sample of 220 AIS patients in the anterior circulation who underwent endovascular thrombectomy (EVT) was included, with 81 (37%) demonstrating good outcomes (mRS ≤ 2). The performance of the different algorithms evaluated was comparable, with the maximum validation under the curve (AUC) reaching 0.87 using graph convolutional networks (GCN) for mRS prediction and 0.86 using fully connected networks (FCN) for mortality prediction. Moderate performance was obtained at admission (AUC of 0.76 using GCN), which improved to 0.84 post-thrombectomy and to 0.89 a day after stroke. Reliable uncertainty prediction of the model could be demonstrated.

The expression of selected microRNAs (miRNAs) known to be involved in the regulation of immune responses was analyzed in 74 patients with relapsing remitting multiple sclerosis (RRMS) and 32 healthy controls. Four miRNAs (miR-326, miR-155, miR-146a, miR-142-3p) were aberrantly expressed in peripheral blood mononuclear cells from RRMS patients compared to controls. Although expression of these selected miRNAs did not differ between treatment-naïve (n = 36) and interferon-beta treated RRMS patients (n = 18), expression of miR-146a and miR-142-3p was significantly lower in glatiramer acetate (GA) treated RRMS patients (n = 20) suggesting that GA, at least in part, restores the expression of deregulated miRNAs in MS.

The avoidance of hematoma expansion is the most important therapeutic goal during acute care of patients with intracerebral hemorrhage. Hematoma expansion occurs in up to 20-40% of patients and leads to poorer patient outcome in one of the most severe sub-types of stroke. At current, randomized controlled trials have failed to provide evidence for interventions that effectively improve functional outcome in patients with intracerebral hemorrhage. Hence, hematoma expansion may serve as important surrogate target that appears causally linked with a poorer prognosis. Therefore, reduction of hematoma expansion rates will eventually translate to improved patient outcome overall. Recent years have shed light on the importance of early and aggressive treatment in order to reduce the risk for hematoma expansion in these patients. Time measures and imaging markers have been identified that may allow patient selection at very high risk for hematoma expansion. Refinements in patient selection may increase chance for randomized trials to show true benefit. Therefore, this current review article will critically evaluate and discuss available evidence associated with hematoma expansion in patients with intracerebral hemorrhage.

Malignant infarction of the middle cerebral artery (MCA) is associated with an 80% mortality rate. Non-randomised studies have suggested that decompressive surgery reduces this mortality without increasing the number of severely disabled survivors. To obtain sufficient data as soon as possible to reliably estimate the effects of decompressive surgery, results from three European randomised controlled trials (DECIMAL, DESTINY, HAMLET) were pooled. The trials were ongoing when the pooled analysis was planned. Individual data for patients aged between 18 years and 60 years, with space-occupying MCA infarction, included in one of the three trials, and treated within 48 h after stroke onset were pooled for analysis. The protocol was designed prospectively when the trials were still recruiting patients and outcomes were defined without knowledge of the results of the individual trials. The primary outcome measure was the score on the modified Rankin scale (mRS) at 1 year dichotomised between favourable (0–4) and unfavourable (5 and death) outcome. Secondary outcome measures included case fatality rate at 1 year and a dichotomisation of the mRS between 0–3 and 4 to death. Data analysis was done by an independent data monitoring committee. 93 patients were included in the pooled analysis. More patients in the decompressive-surgery group than in the control group had an mRS≤4 (75% vs 24%; pooled absolute risk reduction 51% [95% CI 34–69]), an mRS≤3 (43% vs 21%; 23% [5–41]), and survived (78% vs 29%; 50% [33–67]), indicating numbers needed to treat of two for survival with mRS≤4, four for survival with mRS≤3, and two for survival irrespective of functional outcome. The effect of surgery was highly consistent across the three trials. In patients with malignant MCA infarction, decompressive surgery undertaken within 48 h of stroke onset reduces mortality and increases the number of patients with a favourable functional outcome. The decision to perform decompressive surgery should, however, be made on an individual basis in every patient.

The insula plays a key role in brain processing of noxious and innocuous thermal stimuli. The anterior and the posterior portions of the insular cortex are involved in different ways in nociceptive and thermoceptive processing. Therefore, their stimulus-specific functional connectivity may also differ. Here we used functional magnetic resonance imaging (fMRI) to investigate the activity and functional connectivity of insular cortex subregions during noxious and innocuous thermal stimulation. In 11 healthy subjects, psychophysically controlled noxious and innocuous warm and cold stimuli were applied to the left forearm. To differentiate between the subregions of the insular cortex involved in pain processing and those involved in temperature processing, a 2×2 factorial fMRI analysis was performed. Pain processing insular areas (main effect of pain) were detected in bilateral aINS and contralateral pINS. Temperature processing insular areas (main effect of temperature) were also found in bilateral aINS and contralateral pINS. The individual signal time courses from the pain- and temperature processing insular activation clusters were used for calculation and comparison of stimulus-specific functional connectivity of aINS and pINS by means of a correlation analysis. As expected, both aINS and pINS were functionally connected to a large brain network — which predominantly includes areas involved in nociception and thermoception: primary (S1) and secondary (S2) somatosensory cortices, cingulate gyrus, prefrontal cortex (PFC) and parietal association cortices (PA). When statistically compared, during both noxious and innocuous stimulation, aINS was more strongly connected to PFC and to ACC than was pINS; pINS meanwhile was more strongly connected to S1 and to the primary motor cortex (M1). Interestingly, S2 was more strongly connected to aINS than to pINS during painful stimulation but not during innocuous thermal stimulation. We conclude that aINS is more strongly functionally connected to areas known for affective and cognitive processing, whereas pINS is more strongly connected with areas known for sensory-discriminative processing of noxious and somatosensory stimuli. ►The anterior insular cortex is functionally strongly connected to areas known for affective and cognitive pain processing. ►The posterior insular cortex is more strongly connected with areas known for sensory-discriminative processing of noxious and somatosensory stimuli. ►These findings support the central role of the insula in pain and thermoception and corroborate the view of the insula as a multidimensional integration side for pain.

Headache is very frequent in multiple sclerosis. However, the question whether headache is just coincidental or may be secondary due to inflammatory cerebral multiple sclerosis lesions is yet to be clarified. This study intended to evaluate the distribution of cerebral lesion sites and the potential presence of specific lesion clusters in patients with multiple sclerosis and comorbid headache using voxel-based lesion symptom mapping (VLSM). Patients with multiple sclerosis and headache were prospectively identified and included in a university neurological center between 2017 and 2023. Only patients with headache onset after first manifestation of multiple sclerosis were included. Demographic and clinical data were assessed, and lesion volumes calculated. Cerebral lesion sites were correlated voxel-wise with presence and absence of headache using non-parametric permutation testing. A cohort of multiple sclerosis patients served as controls for the VLSM-analysis. 48 multiple sclerosis patients with headache were included, as well as 92 controls without headache. Of the 48 patients with headache, 39 (81%) were female and nine (19%) were male. Mean age was significantly higher in headache patients than in controls (51 + / − 11 vs. 42 + / − 11 years, p < 0.05). EDSS, disease duration and lesion volumes did not significantly differ between both groups. Lesion overlap of all patients demonstrated a distribution of white matter lesions consistently in all subcortical brain areas. The VLSM-analysis showed associations between headache and lesion clusters in the left insula, left hippocampus and right thalamus. In our study, multiple sclerosis lesions in the left insula, left hippocampus and right thalamus were associated with headache in multiple sclerosis patients. The data therefore indicates that headache in multiple sclerosis may, in a proportion of patients, result from lesions in the central nervous systems’ pain processing network. Trial registration : No. 93_17 B, Ethics committee of the University Hospital Erlangen-Nürnberg.

Cerebral amyloid angiopathy (CAA) is a common yet underdiagnosed disease of the small brain vessels, resulting in acute vascular events as well as subcortical neurodegeneration. Currently, it is identified only at advanced stages due to the limitations of non-invasive diagnostic tools. Our pilot study evaluates metabolic and immune alterations in stroke patients with imaging-confirmed CAA. This prospective cohort study included stroke patients admitted to the University Hospital Erlangen with CAA diagnosis based on MRI findings. Metabolomic analysis of cerebrospinal fluid and serum samples was performed using liquid chromatography/mass spectrometry, focusing on caffeine metabolism and amino acid pathways. Immunophenotyping of leukocytes was conducted via flow cytometry. The study included 22 stroke patients, of whom 10 had an MRI-based diagnosis of CAA. Metabolomic analysis revealed consistently lower levels of caffeine-related metabolites in CAA patients with significant differences in 5-acetylamino-6-amino-3-methyluracil, paraxanthine, theobromine, 3,7-dimethyluric acid, 3-methylxanthine and 1-methylxanthine. Amino acid levels showed no significant differences. Immunophenotyping revealed a reduction in CD4 T cell subsets, including effector and central memory T cells, alongside an increase in cytotoxic NK cells in CAA patients. These results suggest that specific metabolic and immune signatures could contribute to the development of diagnostic tools for the detection of CAA.