[A man in his sixties with gait ataxia, dysarthria and mild cognitive impairment].

Background: Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) syndrome is an immune-mediated, treatable and inflammatory CNS disease first reported by Pittock et al. (2010).

Case Presentation: We describe a 66-year-old man with previous history of diabetes, atrial fibrillation and hypertension, who was admitted to hospital with reduced general condition.

Prediction of survival and progression in glioblastoma patients using temporal perfusion changes during radiochemotherapy.

Background: The aim of this study was to investigate changes in structural magnetic resonance imaging (MRI) according to the RANO criteria and perfusion- and permeability related metrics derived from dynamic contrast-enhanced MRI (DCE) and dynamic susceptibility contrast MRI (DSC) during radiochemotherapy for prediction of progression and survival in glioblastoma.

Methods: Twenty-three glioblastoma patients underwent biweekly structural and perfusion MRI before, during, and two weeks after a six weeks course of radiochemotherapy. Temporal trends of tumor volume and the perfusion-derived parameters cerebral blood volume (CBV) and blood flow (CBF) from DSC and DCE, in addition to contrast agent capillary transfer constant (K) from DCE, were assessed.

Are the current MRI criteria using the DWI-FLAIR mismatch concept for selection of patients with wake-up stroke to thrombolysis excluding too many patients?

Background: Up to 25% of stroke patients wake up with a neurological deficit, so called wake-up stroke (WUS). Different imaging approaches that may aid in the selection of patients likely to benefit from reperfusion therapy are currently under investigation. The magnetic resonance imaging (MRI) diffusion weighted imaging - fluid attenuated inversion recovery (DWI-FLAIR) mismatch concept is one proposed method for identifying patients presenting within 4.

Volumetric glioma quantification: comparison of manual and semi-automatic tumor segmentation for the quantification of tumor growth.

Background: Volumetric magnetic resonance imaging (MRI) is now widely available and routinely used in the evaluation of high-grade gliomas (HGGs). Ideally, volumetric measurements should be included in this evaluation. However, manual tumor segmentation is time-consuming and suffers from inter-observer variability.