The results of this study demonstrate that MRS can differentiate high-grade gliomas from metastases, especially with peritumoral measurements, supporting the hypothesis that MRS can detect infiltration of tumor cells in the peritumoral edema.

Background: Conventional magnetic resonance (MR) imaging has a number of limitations in the diagnosis of the most common intracranial brain tumors, including tumor specification and the detection of tumoral infiltration in regions of peritumoral edema. Purpose: To prospectively assess if diffusion-weighted MR imaging (DWI) could be used to differentiate between different types of brain tumors and to distinguish between peritumoral infiltration in high-grade gliomas, lymphomas, and pure vasogenic edema in metastases and meningiomas. Material and Methods: MR imaging and DWI was performed on 93 patients with newly diagnosed brain tumors: 59 patients had histologically verified high-grade gliomas (37 glioblastomas multiforme, 22 anaplastic astrocytomas), 23 patients had metastatic brain tumors, five patients had primary cerebral lymphomas, and six patients had meningiomas. Apparent diffusion coefficient (ADC) values of tumor (enhancing regions or the solid portion of tumor) and peritumoral edema, and ADC ratios (ADC of tumor or peritumoral edema to ADC of contralateral white matter, ADC of tumor to ADC of peritumoral edema) were compared with the histologic diagnosis. ADC values and ratios of high-grade gliomas, primary cerebral lymphomas, metastases, and meningiomas were compared by using ANOVA and multiple comparisons. Optimal thresholds of ADC values and ADC ratios for distinguishing high-grade gliomas from metastases were determined by receiver operating characteristic (ROC) curve analysis. Results: Statistically significant differences were found for minimum and mean of ADC tumor and ADC tumor ratio values between metastases and high-grade gliomas when including only one factor at a time. Including a combination of in total four parameters (mean ADC tumor, and minimum, maximum and mean ADC tumor ratio) resulted in sensitivity, specificity, positive (PPV), and negative predictive values (NPV) of 72.9, 82.6, 91.5, and 54.3% respectively. In the ROC curve analysis, the area under the curve of the combined four parameters was the largest (0.84), indicating a good test. Conclusion: Our results suggest that ADC values and ADC ratios (minimum and mean of ADC tumor and ADC tumor ratio) may be helpful in the differentiation of metastases from high-grade gliomas. It cannot distinguish high-grade gliomas from lymphomas, and lymphomas from metastases. ADC values and ADC ratios in peritumoral edema cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema when measurements for high-grade gliomas, lymphomas, metastases, and meningiomas were compared.

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Background Neurocognitive disorder (NCD) is common in stroke survivors. We aimed to identify clinically accessible imaging markers of stroke and chronic pathology that are associated with early post-stroke NCD. Methods We included 231 stroke survivors from the “Norwegian Cognitive Impairment after Stroke (Nor-COAST)” study who underwent a standardized cognitive assessment 3 months after the stroke. Any NCD (mild cognitive impairment and dementia) and major NCD (dementia) were diagnosed according to “Diagnostic and Statistical Manual of Mental Disorders (DSM-5)” criteria. Clinically accessible imaging findings were analyzed on study-specific brain MRIs in the early phase after stroke. Stroke lesion volumes were semi automatically quantified and strategic stroke locations were determined by an atlas based coregistration. White matter hyperintensities (WMH) and medial temporal lobe atrophy (MTA) were visually scored. Logistic regression was used to identify neuroimaging findings associated with major NCD and any NCD. Results Mean age was 71.8 years (SD 11.1), 101 (43.7%) were females, mean time from stroke to imaging was 8 (SD 16) days. At 3 months 63 (27.3%) had mild NCD and 65 (28.1%) had major NCD. Any NCD was significantly associated with WMH pathology (odds ratio (OR) = 2.73 [1.56 to 4.77], p = 0.001), MTA pathology (OR = 1.95 [1.12 to 3.41], p = 0.019), and left hemispheric stroke (OR = 1.8 [1.05 to 3.09], p = 0.032). Major NCD was significantly associated with WMH pathology (OR = 2.54 [1.33 to 4.84], p = 0.005) and stroke lesion volume (OR (per ml) =1.04 [1.01 to 1.06], p = 0.001). Conclusion WMH pathology, MTA pathology and left hemispheric stroke were associated with the development of any NCD. Stroke lesion volume and WMH pathology were associated with the development of major NCD 3 months after stroke. These imaging findings may be used in the routine clinical setting to identify patients at risk for early post-stroke NCD. Trial registration ClinicalTrials.gov, NCT02650531, Registered 8 January 2016 – Retrospectively registered.

Sacral insufficiency fractures are not uncommon and should be considered in the elderly population with low back pain. Sacroplasty using the optimized "long-axis technique" gave almost immediate pain relief for all five patients in our study material. No complications were observed.

Background: Neurocognitive disorder (NCD) is common after stroke, with major NCD appearing in about 10% of survivors of a first-ever stroke. We aimed to classify clinical- and imaging factors related to rapid development of major NCD 3 months after a stroke, so as to examine the optimal composition of factors for predicting rapid development of the disorder. We hypothesized that the prediction would mainly be driven by neurodegenerative as opposed to vascular brain changes.Methods: Stroke survivors from five Norwegian hospitals were included from the “Norwegian COgnitive Impairment After STroke” (Nor-COAST) study. A support vector machine (SVM) classifier was trained to distinguish between patients who developed major NCD 3 months after the stroke and those who did not. Potential predictor factors were based on previous literature and included both vascular and neurodegenerative factors from clinical and structural magnetic resonance imaging findings. Cortical thickness was obtained via FreeSurfer segmentations, and volumes of white matter hyperintensities (WMH) and stroke lesions were semi-automatically gathered using FSL BIANCA and ITK-SNAP, respectively. The predictive value of the classifier was measured, compared between classifier models and cross-validated.Results: Findings from 227 stroke survivors [age = 71.7 (11.3), males = (56.4%), stroke severity NIHSS = 3.8 (4.8)] were included. The best predictive accuracy (AUC = 0.876) was achieved by an SVM classifier with 19 features. The model with the fewest number of features that achieved statistically comparable accuracy (AUC = 0.850) was the 8-feature model. These features ranked by their weighting were; stroke lesion volume, WMH volume, left occipital and temporal cortical thickness, right cingulate cortical thickness, stroke severity (NIHSS), antiplatelet medication intake, and education.Conclusion: The rapid (<3 months) development of major NCD after stroke is possible to predict with an 87.6% accuracy and seems dependent on both neurodegenerative and vascular factors, as well as aspects of the stroke itself. In contrast to previous literature, we also found that vascular changes are more important than neurodegenerative ones. Although possible to predict with relatively high accuracy, our findings indicate that the development of rapid onset post-stroke NCD may be more complex than earlier suggested.

Both rCBVt and MVL(max) showed good discriminative power in distinguishing all tumor grades. rCBVt correlated strongly with tumor grade; the correlation between MVL(max) and tumor grade was moderate.

Background Chronic brain pathology and pre-stroke cognitive impairment (PCI) is predictive of post-stroke dementia. The aim of the current study was to measure pre-stroke neurodegenerative and vascular disease burden found on brain MRI and to assess the association between pre-stroke imaging pathology and PCI, whilst also looking for potential sex differences. Methods This prospective brain MRI cohort is part of the multicentre Norwegian cognitive impairment after stroke (Nor-COAST) study. Patients hospitalized with acute ischemic or hemorrhagic stroke were included from five participating stroke units. Visual rating scales were used to categorize baseline MRIs (N = 410) as vascular, neurodegenerative, mixed, or normal, based on the presence of pathological imaging findings. Pre-stroke cognition was assessed by interviews of patients or caregivers using the Global Deterioration Scale (GDS). Stroke severity was assessed with the National Institute of Health Stroke Scale (NIHSS). Univariate and multiple logistic regression analyses were performed to investigate the association between imaging markers, PCI, and sex. Results Patients’ (N = 410) mean (SD) age was 73.6 (±11) years; 182 (44%) participants were female, the mean (SD) NIHSS at admittance was 4.1 (±5). In 68% of the participants, at least one pathological imaging marker was found. Medial temporal lobe atrophy (MTA) was present in 30% of patients, white matter hyperintensities (WMH) in 38% of patients and lacunes in 35% of patients. PCI was found in 30% of the patients. PCI was associated with cerebrovascular pathology (OR 2.5; CI = 1.4 to 4.5, p = 0.001) and mixed pathology (OR 3.4; CI = 1.9 to 6.1, p = 0.001) but was not associated with neurodegeneration (OR 1.0; CI = 0.5 to 2.2; p = 0.973). Pathological MRI markers, including MTA and lacunes, were more prevalent among men, as was a history of clinical stroke prior to the index stroke. The OR of PCI for women was not significantly increased (OR 1.2; CI = 0.8 to 1.9; p = 0.3). Conclusions Pre-stroke chronic brain pathology is common in stroke patients, with a higher prevalence in men. Vascular pathology and mixed pathology are associated with PCI. There were no significant sex differences for the risk of PCI. Trial registration NCT02650531, date of registration: 08.01.2016.