Ischemic stroke is the most common cerebrovascular disease, and its diagnosis, treatment, and study relies on non-invasive imaging. Algorithms for stroke lesion segmentation from magnetic resonance imaging (MRI) volumes are intensely researched, but the reported results are largely incomparable due to different datasets and evaluation schemes. We approached this urgent problem of comparability with the Ischemic Stroke Lesion Segmentation (ISLES) challenge organized in conjunction with the MICCAI 2015 conference. In this paper we propose a common evaluation framework, describe the publicly available datasets, and present the results of the two sub-challenges: Sub-Acute Stroke Lesion Segmentation (SISS) and Stroke Perfusion Estimation (SPES). A total of 16 research groups participated with a wide range of state-of-the-art automatic segmentation algorithms. A thorough analysis of the obtained data enables a critical evaluation of the current state-of-the-art, recommendations for further developments, and the identification of remaining challenges. The segmentation of acute perfusion lesions addressed in SPES was found to be feasible. However, algorithms applied to sub-acute lesion segmentation in SISS still lack accuracy. Overall, no algorithmic characteristic of any method was found to perform superior to the others. Instead, the characteristics of stroke lesion appearances, their evolution, and the observed challenges should be studied in detail. The annotated ISLES image datasets continue to be publicly available through an online evaluation system to serve as an ongoing benchmarking resource (www.isles-challenge.org).

Brain volumetry combined with support vector machine classification allowed for reliable automated differentiation of parkinsonian syndromes on single-patient level even for MRI acquired on different scanners. © 2016 International Parkinson and Movement Disorder Society.

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Background: Patients with alcohol addiction show a number of transient or persistent neurological and psychiatric deficits. The complexity of these brain alterations suggests that several brain areas are involved, although the definition of the brain alteration patterns is not yet accomplished. Aim: To determine brain atrophy patterns in patients with alcohol dependence. Methods: Voxel-based morphometry (VBM) of grey matter (GM) and white matter (WM) was performed in 22 patients with alcohol dependence and in 22 healthy controls matched for age and sex. Results: In patients with alcohol dependence, VBM of GM revealed a significant decrease in density (p,0.001) in the precentral gyrus, middle frontal gyrus, insular cortex, dorsal hippocampus, anterior thalamus and cerebellum compared with controls. Reduced density of WM was found in the periventricular area, pons and cerebellar pedunculi in patients with alcohol addiction. Conclusions: Our findings provide evidence that alcohol addiction is associated with altered density of GM and WM of specific brain regions. This supports the assumption that alcohol dependence is associated with both local GM dysfunction and altered brain connectivity. Also, VBM is an effective tool for in vivo investigation of cerebral atrophy in patients with alcohol addiction.

BackgroundQuantification of the optic nerve sheath diameter (ONSD) by transbulbar sonography is a promising non-invasive technique for the detection of altered intracranial pressure. In order to establish this method as follow-up tool in diseases with intracranial hyper- or hypotension scan-rescan reproducibility and accuracy need to be systematically investigated.MethodsThe right ONSD of 15 healthy volunteers (mean age 24.5 ± 0.8 years) were measured by both transbulbar sonography (9 – 3 MHz) and 3 Tesla MRI (half-Fourier acquisition single-shot turbo spin-echo sequences, HASTE) 3 and 5 mm behind papilla. All volunteers underwent repeated ultrasound and MRI examinations in order to assess scan-rescan reproducibility and accuracy. Moreover, inter- and intra-observer variabilities were calculated for both techniques.ResultsScan-rescan reproducibility was robust for ONSD quantification by sonography and MRI at both depths (r > 0.75, p ≤ 0.001, mean differences < 2%). Comparing ultrasound- and MRI-derived ONSD values, we found acceptable agreement between both methods for measurements at a depth of 3 mm (r = 0.72, p = 0.002, mean difference < 5%). Further analyses revealed good inter- and intra-observer reliability for sonographic measurements 3 mm behind the papilla and for MRI at 3 and 5 mm (r > 0.82, p < 0.001, mean differences < 5%).ConclusionsSonographic ONSD quantification 3 mm behind the papilla can be performed with good reproducibility, measurement accuracy and observer agreement. Thus, our findings emphasize the feasibility of this technique as a non-invasive bedside tool for longitudinal ONSD measurements.