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The relationship between magnetic resonance imaging (MRI) and clinical variables in patients suspected to have Creutzfeldt-Jakob Disease (CJD) is uncertain. We aimed to determine which MRI features of CJD (positive or negative), previously described in vivo, accurately identify CJD, are most reliably detected, vary with disease duration, and whether combined clinical and imaging features increase diagnostic accuracy for CJD. Prospective patients suspected of having CJD were referred to the National CJD Research and Surveillance Unit between 1994–2004; post-mortem, brains were sent for MRI and histopathology. Two neuroradiologists independently assessed MRI for atrophy, white matter hyperintensities, and caudate, lentiform and pulvinar signals, blind to histopathological diagnosis and clinical details. We examined differences in variable frequencies using Fisher’s exact tests, and associations between variables and CJD in logistic regression models. Amongst 200 cases, 118 (59%) with a histopathological diagnosis of CJD and 82 (41%) with histopathological diagnoses other than CJD, a logistic regression model including age, disease duration at death, atrophy, white matter hyperintensities, bright or possibly bright caudate, and present pulvinar sign correctly classified 81% of cases as CJD versus not CJD. Pulvinar sign alone was not independently associated with an increased likelihood of histopathologically-confirmed CJD (of any subtype) or sporadic CJD after adjustment for age at death, disease duration, atrophy, white matter hyperintensities or caudate signal; despite the large sample, data sparsity precluded investigation of the association of pulvinar sign with variant CJD. No imaging feature varied significantly with disease duration. Of the positive CJD signs, neuroradiologists most frequently agreed on the presence or absence of atrophy (agreements in 169/200 cases [84.5%]). Combining patient age, and disease duration, with absence of atrophy and white matter hyperintensities and presence of increased caudate signal and pulvinar sign predicts CJD with good accuracy. Autopsy remains essential. [ABSTRACT FROM AUTHOR]

Background: White matter hyperintensities (WMHs) are commonly seen on in brain imaging and are associated with stroke and cognitive decline. Therefore, they may provide a relevant intermediate outcome in clinical trials. WMH can be measured as a volume or visually on the Fazekas scale. We investigated predictors of WMH progression and design of efficient studies using WMH volume and Fazekas score as an intermediate outcome.Methods: We prospectively recruited 264 patients with mild ischaemic stroke and measured WMH volume, Fazekas score, age and cardiovascular risk factors at baseline and 1 year. We modelled predictors of WMH burden at 1 year and used the results in sample size calculations for hypothetical randomised controlled trials with different analysis plans and lengths of follow-up.Results: Follow-up WMH volume was predicted by baseline WMH: a 0.73-ml (95% CI 0.65-0.80, p < 0.0001) increase per 1-ml baseline volume increment, and a 2.93-ml increase (95% CI 1.76-4.10, p < 0.0001) per point on the Fazekas scale. Using a mean difference of 1 ml in WMH volume between treatment groups, 80% power and 5% alpha, adjusting for all predictors and 2-year follow-up produced the smallest sample size (n = 642). Other study designs produced samples sizes from 2054 to 21,270. Sample size calculations using Fazekas score as an outcome with the same power and alpha, as well as an OR corresponding to a 1-ml difference, were sensitive to assumptions and ranged from 2504 to 18,886.Conclusions: Baseline WMH volume and Fazekas score predicted follow-up WMH volume. Study size was smallest using volumes and longer-term follow-up, but this must be balanced against resources required to measure volumes versus Fazekas scores, bias due to dropout and scanner drift. Samples sizes based on Fazekas scores may be best estimated with simulation studies. [ABSTRACT FROM AUTHOR]

White matter hyperintensities accumulate with age and occur in patients with stroke, but their pathogenesis is poorly understood. We measured multiple magnetic resonance imaging biomarkers of tissue integrity in normal-appearing white matter and white matter hyperintensities in patients with mild stroke, to improve understanding of white matter hyperintensities origins. We classified white matter into white matter hyperintensities and normal-appearing white matter and measured fractional anisotropy, mean diffusivity, water content (T1-relaxation time) and blood–brain barrier leakage (signal enhancement slope from dynamic contrast-enhanced magnetic resonance imaging).We studied the effects of age, white matter hyperintensities burden (Fazekas score) and vascular risk factors on each biomarker, in normalappearing white matter and white matter hyperintensities, and performed receiver-operator characteristic curve analysis. Amongst 204 patients (34.3–90.9 years), all biomarkers differed between normal-appearing white matter and white matter hyperintensities (P<0.001). In normal-appearing white matter and white matter hyperintensities, mean diffusivity and T1 increased with age (P<0.001), all biomarkers varied with white matter hyperintensities burden (P<0.001; P=0.02 signal enhancement slope), but only signal enhancement slope increased with hypertension (P=0.028). Fractional anisotropy showed complex age-white matter hyperintensities-tissue interactions; enhancement slope showed white matter hyperintensities-tissue interactions. Mean diffusivity distinguished white matter hyperintensities from normal-appearing white matter best at all ages. Blood–brain barrier leakage increases with hypertension and white matter hyperintensities burden at all ages in normal-appearing white matter and white matter hyperintensities, whereas water mobility and content increase as tissue damage accrues, suggesting that blood–brain barrier leakage mediates small vessel disease-related brain damage. [ABSTRACT FROM AUTHOR]

Background: Perivascular spaces (PVS) are an important component of cerebral small vessel disease (SVD), several inflammatory disorders, hypertension and blood-brain barrier breakdown, but are difficult to quantify. A recent international collaboration of SVD experts has highlighted the need for a robust, easy-to-use PVS rating scale for the effective investigation of the diagnostic and prognostic significance of PVS. The purpose of the current study was to develop and extend existing PVS scales to provide a more comprehensive scale for the measurement of PVS in the basal ganglia, centrum semiovale and midbrain, and to test its intra- and inter-rater agreement, assessing reasons for discrepancy. Methods: We reviewed previously published PVS scales, including site of PVS assessed, rating method, and size and morphological criteria. Retaining key features, we devised a more comprehensive scale in order to improve the reliability of PVS rating. Two neuroradiologists tested the new scale in MRI brain scans of 60 patients from two studies (stroke, ageing population), chosen to represent a full range of PVS, and demonstrating concomitant features of SVD such as lacunes and white matter hyperintensities. We rated basal ganglia, centrum semiovale, and midbrain PVS. Basal ganglia and centrum semiovale PVS were rated 0 (none), 1 (1-10), 2 (11-20), 3 (21-40) and 4 (>40), and midbrain PVS were rated 0 (none visible) or 1 (visible). We calculated kappa statistics for rating, assessed consistency in use of PVS categories (Bhapkar test) and reviewed sources of discrepancy. Results: Intra- and inter-rater kappa statistics were highest for basal ganglia PVS (range 0.76-0.87 and 0.8-0.9, respectively) than for centrum semiovale PVS (range 0.68-0.75 and 0.61-0.8, respectively) or midbrain PVS (inter-rater range 0.51-0.52). Inter-rater consistency was better for basal ganglia compared to centrum semiovale PVS (Bhapkar statistic 2.49-3.72, compared to 6.79-21.08, respectively). Most inter-rater disagreements were due to very faint PVS, coexisting extensive white matter hyperintensities (WMH) or the presence of lacunes. Conclusions: We developed a more inclusive and robust visual PVS rating scale allowing rating of all grades of PVS severity on structural brain imaging. The revised PVS rating scale has good observer reliability for basal ganglia and centrum semiovale PVS, best for basal ganglia PVS, and moderate reliability for midbrain PVS. Agreement is influenced by PVS severity and the presence of background features of SVD. The current scale can be used in further studies to assess the clinical implications of PVS. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Objective Magnetic resonance (MR) diffusion-weighted imaging (DWI) is sensitive to small acute ischemic lesions and might help diagnose transient ischemic attack (TIA). Reclassification of patients with TIA and a DWI lesion as 'stroke' is under consideration. We assessed DWI positivity in TIA and implications for reclassification as stroke. Methods We searched multiple sources, without language restriction, from January 1995 to July 2012. We used PRISMA guidelines, and included studies that provided data on patients presenting with suspected TIA who underwent MR DWI and reported the proportion with an acute DWI lesion. We performed univariate random effects meta-analysis to determine DWI positive rates and influencing factors. Results We included 47 papers and 9,078 patients (range = 18-1,693). Diagnosis was by a stroke specialist in 26 of 47 studies (55%); all studies excluded TIA mimics. The pooled proportion of TIA patients with an acute DWI lesion was 34.3% (95% confidence interval [CI] = 30.5-38.4, range = 9-67%; I2 = 89.3%). Larger studies (n > 200) had lower DWI-positive rates (29%; 95% CI = 23.2-34.6) than smaller (n < 50) studies (40.1%; 95% CI = 33.5-46.6%; p = 0.035), but no other testable factors, including clinician speciality and time to scanning, reduced or explained the 7-fold DWI-positive variation. Interpretation The commonest DWI finding in patients with definite TIA is a negative scan. Available data do not explain why ⅔ of patients with definite specialist-confirmed TIA have negative DWI findings. Until these factors are better understood, reclassifying DWI-positive TIAs as strokes is likely to increase variance in estimates of global stroke and TIA burden of disease. ANN NEUROL 2014;75:67-76 [ABSTRACT FROM AUTHOR]

Patients undergo interventions to achieve a 'normal' brain temperature; a parameter that remains undefined for humans. The profound sensitivity of neuronal function to temperature implies the brain should be isothermal, but observations from patients and non-human primates suggest significant spatiotemporal variation. We aimed to determine the clinical relevance of brain temperature in patients by establishing how much it varies in healthy adults. We retrospectively screened data for all patients recruited to the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High Resolution Intensive Care Unit Sub-Study. Only patients with direct brain temperature measurements and without targeted temperature management were included. To interpret patient analyses, we prospectively recruited 40 healthy adults (20 males, 20 females, 20-40 years) for brain thermometry using magnetic resonance spectroscopy. Participants were scanned in the morning, afternoon, and late evening of a single day. In patients (n = 114), brain temperature ranged from 32.6 to 42.3°C and mean brain temperature (38.5 ± 0.8°C) exceeded body temperature (37.5 ± 0.5°C, P < 0.0001). Of 100 patients eligible for brain temperature rhythm analysis, 25 displayed a daily rhythm, and the brain temperature range decreased in older patients (P = 0.018). In healthy participants, brain temperature ranged from 36.1 to 40.9°C; mean brain temperature (38.5 ± 0.4°C) exceeded oral temperature (36.0 ± 0.5°C) and was 0.36°C higher in luteal females relative to follicular females and males (P = 0.0006 and P < 0.0001, respectively). Temperature increased with age, most notably in deep brain regions (0.6°C over 20 years, P = 0.0002), and varied spatially by 2.41 ± 0.46°C with highest temperatures in the thalamus. Brain temperature varied by time of day, especially in deep regions (0.86°C, P = 0.0001), and was lowest at night. From the healthy data we built HEATWAVE-a 4D map of human brain temperature. Testing the clinical relevance of HEATWAVE in patients, we found that lack of a daily brain temperature rhythm increased the odds of death in intensive care 21-fold (P = 0.016), whilst absolute temperature maxima or minima did not predict outcome. A warmer mean brain temperature was associated with survival (P = 0.035), however, and ageing by 10 years increased the odds of death 11-fold (P = 0.0002). Human brain temperature is higher and varies more than previously assumed-by age, sex, menstrual cycle, brain region, and time of day. This has major implications for temperature monitoring and management, with daily brain temperature rhythmicity emerging as one of the strongest single predictors of survival after brain injury. We conclude that daily rhythmic brain temperature variation-not absolute brain temperature-is one way in which human brain physiology may be distinguished from pathophysiology. [ABSTRACT FROM AUTHOR]

• Raised signal in CSF on FLAIR may indicate raised CSF protein or debris. • Inferior frontal sulcal hyperintensities (IFSH) were associated with ageing. • IFSH were associated with PVS score in centrum semiovale in stroke patients. Raised signal in cerebrospinal fluid (CSF) on fluid-attenuated inversion recovery (FLAIR) may indicate raised CSF protein or debris and is seen in inferior frontal sulci on routine MRI. To explore its clinical relevance, we assessed the association of inferior frontal sulcal hyperintensities (IFSH) on FLAIR with demographics, risk factors, and small vessel disease markers in three cohorts (healthy volunteers, n=44; mild stroke patients, n=105; older community-dwelling participants from Lothian birth cohort 1936, n=101). We collected detailed clinical data, scanned all subjects on the same 3T MRI scanner and 3-dimensional FLAIR sequence and developed a scale to rate IFSH. In adjusted analyses, the IFSH score increased with age (per 10-year increase; OR 1.69; 95% CI, 1.42-2.02), and perivascular spaces score in centrum semiovale in stroke patients (OR 1.73; 95% CI, 1.13-2.69). Since glymphatic CSF clearance declines with age and drains partially via the cribriform plate to the nasal lymphatics, IFSH on 3T MRI may be a non-invasive biomarker of altered CSF clearance and justifies further research in larger, more diverse samples. [ABSTRACT FROM AUTHOR]

Considering premorbid or "peak" adult intelligence (IQ) is important when examining post-stroke cognition. The stability of estimated premorbid IQ and its relationship to current cognitive ability in stroke is unknown. We investigated changes in estimated premorbid IQ and current cognitive ability up to three years post-stroke. Minor stroke patients (NIHSS < 8) were assessed at one to three months, one and three years' post-stroke. The National Adult Reading Test (NART) and Addenbrooke's Cognitive Examination-Revised (ACE-R) were used to estimate premorbid IQ (NART IQ) and current cognitive ability respectively at each time-point. Baseline demographics, vascular and stroke characteristics were included. Of the 264 patients recruited (mean age 66), 158 (60%), 151 (57%), and 153 (58%) completed cognitive testing at each time-point respectively. NART IQ initially increased (mean difference (MD) = 1.32, 95% CI = 0.54 to 2.13, p < 0.001) before decreasing (MD = −4.269, 95% CI = −5.12 to −3.41, p < 0.001). ACE-R scores initially remained stable (MD = 0.29, 95% CI = −0.49 to 1.07, p > 0.05) before decreasing (MD = −1.05, 95% CI = −2.08 to −0.01, p < 0.05). Adjusting for baseline variables did not change the relationship between NART IQ and ACE-R with time. Increases in NART IQ were associated with more education. For ACE-R, older age was associated with declines, and higher NART IQ and more education was associated with increases. Across 3 years, we observed fluctuations in estimated premorbid IQ and minor changes in current cognitive ability. Future research should aim to identify variables associated with these changes. However, studies of post-stroke cognition should account for premorbid IQ. [ABSTRACT FROM AUTHOR]

Aim: To systematically review and meta-analyse studies of neurodevelopmental outcome of children born to mothers prescribed methadone in pregnancy.Method: MEDLINE, Embase, and PsycINFO were searched for studies published from 1975 to 2017 reporting neurodevelopmental outcomes in children with prenatal methadone exposure.Results: Forty-one studies were identified (2283 participants). Eight studies were amenable to meta-analysis: at 2 years the Mental Development Index weighted mean difference of children with prenatal methadone exposure compared with unexposed infants was -4.3 (95% confidence interval [CI] -7.24 to -1.63), and the Psychomotor Development Index weighted mean difference was -5.42 (95% CI -10.55 to -0.28). Seven studies reported behavioural scores and six found scores to be lower among methadone-exposed children. Twelve studies reported visual outcomes: nystagmus and strabismus were common; five studies reported visual evoked potentials of which four described abnormalities. Factors that limited the quality of some studies, and introduced risk of bias, included absence of blinding, small sample size, high attrition, uncertainty about polydrug exposure, and lack of comparison group validity.Interpretation: Children born to mothers prescribed methadone in pregnancy are at risk of neurodevelopmental problems but risk of bias limits inference about harm. Research into management of opioid use disorder in pregnancy should include evaluation of childhood neurodevelopmental outcome.What This Paper Adds: Children born to opioid-dependent mothers prescribed methadone are at risk of neurodevelopmental impairment. Exposed infants have lower Mental Development Index and Psychomotor Development Index scores than unexposed children. Atypical visual evoked potentials, strabismus, and nystagmus have increased prevalence. Estimates of impairment may be biased by intermediate to poor quality evidence. [ABSTRACT FROM AUTHOR]

In the brain, enlarged perivascular spaces (PVS) relate to cerebral small vessel disease (SVD), poor cognition, inflammation and hypertension. We propose a fully automatic scheme that uses a support vector machine (SVM) to classify the burden of PVS in the basal ganglia (BG) region as low or high. We assess the performance of three different types of descriptors extracted from the BG region in T2-weighted MRI images: (i) statistics obtained from Wavelet transform’s coefficients, (ii) local binary patterns and (iii) bag of visual words (BoW) based descriptors characterizing local keypoints obtained from a dense grid with the scale-invariant feature transform (SIFT) characteristics. When the latter were used, the SVM classifier achieved the best accuracy (81.16%). The output from the classifier using the BoW descriptors was compared with visual ratings done by an experienced neuroradiologist (Observer 1) and by a trained image analyst (Observer 2). The agreement and cross-correlation between the classifier and Observer 2 (κ = 0.67 (0.58–0.76)) were slightly higher than between the classifier and Observer 1 (κ = 0.62 (0.53–0.72)) and comparable between both the observers (κ = 0.68 (0.61–0.75)). Finally, three logistic regression models using clinical variables as independent variable and each of the PVS ratings as dependent variable were built to assess how clinically meaningful were the predictions of the classifier. The goodness-of-fit of the model for the classifier was good (area under the curve (AUC) values: 0.93 (model 1), 0.90 (model 2) and 0.92 (model 3)) and slightly better (i.e. AUC values: 0.02 units higher) than that of the model for Observer 2. These results suggest that, although it can be improved, an automatic classifier to assess PVS burden from brain MRI can provide clinically meaningful results close to those from a trained observer. [ABSTRACT FROM AUTHOR]

Background: Neuropsychiatric symptoms could form part of an early cerebral small vessel disease prodrome that is detectable before stroke or dementia onset. We aimed to identify whether apathy, depression, anxiety, and subjective memory complaints associate with longitudinal white matter hyperintensity (WMH) progression. Methods: Community-dwelling older adults from the observational Lothian Birth Cohort 1936 attended three visits at mean ages 73, 76, and 79 years, repeating MRI, Mini-Mental State Examination, neuropsychiatric (Dimensional Apathy Scale, Hospital Anxiety and Depression Scale), and subjective memory symptoms. We ran regression and mixed-effects models for symptoms and normalised WMH volumes (cube root of WMH:ICV x 10). Results: At age 73, 76, and 79, m = 672, n = 476, and n = 382 participants attended MRI respectively. Worse apathy at age 79 was associated with WMH volume increase (β = 0.27, p = 0.04) in the preceding 6 years. A 1SD increase in apathy score at age 79 associated with a 0.17 increase in WMH (β = 0.17 normalised WMH percent ICV, p = 0.009). In apathy subscales, executive (β = 0.13, p = 0.05) and emotional (β = 0.13, p = 0.04) scores associated with increasing WMH more than initiation scores (β = 0.11, p = 0.08). Increasing WMH also associated with age (β = 0.40, p = 0.002) but not higher depression (β = -0.01, p = 0.78), anxiety (β = 0.05, p = 0.13) scores, or subjective memory complaints (β = 1.12, p = 0.75). Conclusions: Apathy independently associates with preceding longitudinal WMH progression, while depression, anxiety, and subjective memory complaints do not. Patients with apathy should be considered for enrolment to small vessel disease trials. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to test e‐ASPECTS software in patients with stroke. Marketed as a decision‐support tool, e‐ASPECTS may detect features of ischemia or hemorrhage on computed tomography (CT) imaging and quantify ischemic extent using Alberta Stroke Program Early CT Score (ASPECTS). Methods: Using CT from 9 stroke studies, we compared software with masked experts. As per indications for software use, we assessed e‐ASPECTS results for patients with/without middle cerebral artery (MCA) ischemia but no other cause of stroke. In an analysis outside the intended use of the software, we enriched our dataset with non‐MCA ischemia, hemorrhage, and mimics to simulate a representative "front door" hospital population. With final diagnosis as the reference standard, we tested the diagnostic accuracy of e‐ASPECTS for identifying stroke features (ischemia, hyperattenuated arteries, and hemorrhage) in the representative population. Results: We included 4,100 patients (51% women, median age = 78 years, National Institutes of Health Stroke Scale [NIHSS] = 10, onset to scan = 2.5 hours). Final diagnosis was ischemia (78%), hemorrhage (14%), or mimic (8%). From 3,035 CTs with expert‐rated ASPECTS, most (2084/3035, 69%) e‐ASPECTS results were within one point of experts. In the representative population, the diagnostic accuracy of e‐ASPECTS was 71% (95% confidence interval [CI] = 70–72%) for detecting ischemic features, 85% (83–86%) for hemorrhage. Software identified more false positive ischemia (12% vs 2%) and hemorrhage (14% vs <1%) than experts. Interpretation: On independent testing, e‐ASPECTS provided moderate agreement with experts and overcalled stroke features. Therefore, future prospective trials testing impacts of artificial intelligence (AI) software on patient care and outcome are required before widespread implementation of stroke decision‐support software. ANN NEUROL 2022;92:943–957 [ABSTRACT FROM AUTHOR]

Post-stroke cognitive impairment is common and can have major impact on life after stroke. Peak-width of Skeletonized Mean Diffusivity (PSMD) is a diffusion imaging marker of white matter microstructure and is also associated with cognition. Here, we examined associations between PSMD and post-stroke global cognition in an ongoing study of mild ischemic stroke patients. We studied cross-sectional associations between PSMD and cognition at both 3-months (N = 229) and 1-year (N = 173) post-stroke, adjusted for premorbid IQ, sex, age, stroke severity and disability, as well as the association between baseline PSMD and 1-year cognition. At baseline, (mean age = 65.9 years (SD = 11.1); 34% female), lower Montreal Cognitive Assessment (MoCA) scores were associated with older age, lower premorbid IQ and higher stroke severity, but not with PSMD (βstandardized = −0.116, 95% CI −0.241, 0.009; p = 0.069). At 1-year, premorbid IQ, older age, higher stroke severity and higher PSMD (βstandardized = −0.301, 95% CI −0.434, −0.168; p < 0.001) were associated with lower MoCA. Higher baseline PSMD was associated with lower 1-year MoCA (βstandardized = −0.182, 95% CI −0.308, −0.056; p = 0.005). PSMD becomes more associated with global cognition at 1-year post-stroke, possibly once acute effects have settled. Additionally, PSMD in the subacute phase after a mild stroke could help predict long-term cognitive impairment. [ABSTRACT FROM AUTHOR]

Background: The cause of lacunar ischemic stroke, a clinical feature of cerebral small vessel disease (SVD), is largely unknown. Inflammation and endothelial dysfunction have been implicated. Plasma biomarkers could provide mechanistic insights but current data are conflicting. White matter hyperintensities (WMHs) are an important imaging biomarker of SVD. It is unknown if plasma biomarkers add predictive capacity beyond age and vascular risk factors in explaining WMH. Methods: We prospectively recruited patients presenting with non-disabling ischemic stroke, classifying them clinically and with the help of MRI as lacunar or cortical. We measured biomarkers of inflammation, endothelial dysfunction and hemostasis for >1 month after stroke and compared biomarker levels between stroke subtypes. We quantitatively calculated WMH. We used multiple linear regression analysis to model WMH as a function of age, sex, hypertension and smoking (the baseline model). We fitted exploratory models using plasma biomarkers as predictor variables to assess model improvement over baseline. Results: We recruited 125 patients. The lacunar group (n = 65) had lower tissue plasminogen activator (t-PA) levels in unadjusted (7.39 vs. 8.59 ng/ml, p = 0.029) and adjusted (p = 0.035) analyses compared with the cortical group (n = 60). There were no significant differences in the other plasma biomarkers. The results for t-PA were consistent with an updated meta-analysis, although the effect remains non-significant (standardized mean difference -0.08 (95% CI -0.25 to 0.09)). The baseline regression model explained 29% of the variance in quantitative WMH (R ² 0.289). Inflammatory biomarkers showed minor improvement over baseline (R² 0.291), but the other plasma biomarkers did not improve the baseline model. Conclusion: Plasma t-PA levels appear to differ between lacunar and cortical stroke subtypes, late after stroke, independent of age, sex and vascular risk factors and may reflect endothelial dysfunction. Except for a minor additional predictive effect of inflammatory markers, plasma biomarkers do not relate to WMH severity in this small stroke population. [ABSTRACT FROM AUTHOR]

Magnetic Resonance Imaging (MRI) visible perivascular spaces (PVS) have been associated with age, decline in cognitive abilities, interrupted sleep, and markers of small vessel disease. But the limits of validity of their quantification have not been established. We use a purpose-built digital reference object to construct an in-silico phantom for addressing this need, and validate it using a physical phantom. We use cylinders of different sizes as models for PVS. We also evaluate the influence of 'PVS' orientation, and different sets of parameters of the two vesselness filters that have been used for enhancing tubular structures, namely Frangi and RORPO filters, in the measurements' accuracy. PVS measurements in MRI are only a proxy of their true dimensions, as the boundaries of their representation are consistently overestimated. The success in the use of the Frangi filter relies on a careful tuning of several parameters. Alpha= 0.5, beta= 0.5 and c= 500 yielded the best results. RORPO does not have these requirements and allows detecting smaller cylinders in their entirety more consistently in the absence of noise and confounding artefacts. The Frangi filter seems to be best suited for voxel sizes equal or larger than 0.4 mm-isotropic and cylinders larger than 1 mm diameter and 2 mm length. 'PVS' orientation did not affect measurements in data with isotropic voxels. Does not apply. The in-silico and physical phantoms presented are useful for establishing the validity of quantification methods of tubular small structures. [Display omitted] • Physical and in-silico PVS phantoms to test assessment accuracy publicly available. • PVS orientation is not an influential factor in differences between measurements. • Frangi filter best for voxels> =0.4 mm-isotropic and cylinders> 1 mm Ø & 2 mm length. • BBest parameters for Frangi: α=0.5, β=0.5 & c= 500, c depending on signal intensity. • RORPO allows detecting smaller cylinders in their entirety more accurately. [ABSTRACT FROM AUTHOR]

Growing interest surrounds perivascular spaces (PVS) as a clinical biomarker of brain dysfunction given their association with cerebrovascular risk factors and disease. Neuroimaging techniques allowing quick and reliable quantification are being developed, but, in practice, they require optimisation as their limits of validity are usually unspecified. We evaluate modifications and alternatives to a state-of-the-art (SOTA) PVS segmentation method that uses a vesselness filter to enhance PVS discrimination, followed by thresholding of its response, applied to brain magnetic resonance images (MRI) from patients with sporadic small vessel disease acquired at 3 T. The method is robust against inter-observer differences in threshold selection, but separate thresholds for each region of interest (i.e., basal ganglia, centrum semiovale, and midbrain) are required. Noise needs to be assessed prior to selecting these thresholds, as effect of noise and imaging artefacts can be mitigated with a careful optimisation of these thresholds. PVS segmentation from T1-weighted images alone, misses small PVS, therefore, underestimates PVS count, may overestimate individual PVS volume especially in the basal ganglia, and is susceptible to the inclusion of calcified vessels and mineral deposits. Visual analyses indicated the incomplete and fragmented detection of long and thin PVS as the primary cause of errors, with the Frangi filter coping better than the Jerman filter. Limits of validity to a SOTA PVS segmentation method applied to 3 T MRI with confounding pathology are given. Evidence presented reinforces the STRIVE-2 recommendation of using T2-weighted images for PVS assessment wherever possible. The Frangi filter is recommended for PVS segmentation from MRI, offering robust output against variations in threshold selection and pathology presentation. • Practical evaluations on filter and threshold selection to a SOTA MRI-visible PVS segmentation method. • Practical recommendations on compensating noise impact in SOTA PVS segmentation method. • Comparison PVS segmentation performance on T1-weighted vs. T2-weighted MRI. [ABSTRACT FROM AUTHOR]

Background: Diabetes-related lower limb amputations are associated with considerable morbidity and mortality and are usually preceded by foot ulceration. The available systematic reviews of aggregate data are compromised because the primary studies report both adjusted and unadjusted estimates. As adjusted meta-analyses of aggregate data can be challenging, the best way to standardise the analytical approach is to conduct a metaanalysis based on individual patient data (IPD). There are however many challenges and fundamental methodological omissions are common; protocols are rare and the assessment of the risk of bias arising from the conduct of individual studies is frequently not performed, largely because of the absence of widely agreed criteria for assessing the risk of bias in this type of review. In this protocol we propose key methodological approaches to underpin our IPD systematic review of prognostic factors of foot ulceration in diabetes. Review questions; 1.What are the most highly prognostic factors for foot ulceration (i.e. symptoms, signs, diagnostic tests) in people with diabetes? 2.Can the data from each study be adjusted for a consistent set of adjustment factors? 3.Does the model accuracy change when patient populations are stratified according to demographic and/or clinical characteristics? Methods: MEDLINE and EMBASE databases from their inception until early 2012 were searched and the corresponding authors of all eligible primary studies invited to contribute their raw data. We developed relevant quality assurance items likely to identify occasions when study validity may have been compromised from several sources. A confidentiality agreement, arrangements for communication and reporting as well as ethical and governance considerations are explained. We have agreement from the corresponding authors of all studies which meet the eligibility criteria and they collectively possess data from more than 17000 patients. We propose, as a provisional analysis plan, to use a multilevel mixed model, using "study" as one of the levels. Such a model can also allow for the within-patient clustering that occurs if a patient contributes data from both feet, although to aid interpretation, we prefer to use patients rather than feet as the unit of analysis. We intend to only attempt this analysis if the results of the investigation of heterogeneity do not rule it out and the model diagnostics are acceptable. Discussion: This review is central to the development of a global evidence-based strategy for the risk assessment of the foot in patients with diabetes, ensuring future recommendations are valid and can reliably inform international clinical guidelines. [ABSTRACT FROM AUTHOR]

Objective: Cerebral perfusion imaging with computed tomography (CT) or magnetic resonance (MR) is widely available. The optimum perfusion values to identify tissue at risk of infarction in acute stroke are unclear. We systematically reviewed CT and MR perfusion imaging in acute ischemic stroke. Methods: We searched for papers on MR or CT perfusion performed <24 hours after stroke that assessed perfusion thresholds, mean perfusion lesion values, or lesion volumes. We extracted definitions and perfusion values. We compared definitions and evaluated perfusion thresholds for 'nonviable'/'at risk' and 'at risk'/'not at risk tissue' thresholds. Results: Among 7,152 papers, 69 met inclusion criteria for analysis of definitions (49 MR and 20 CT), 21 MR (n = 551), and 10 CT (n = 266) papers, median sample size 22, provided thresholds. We found multiple definitions for tissue states, eg, tissue at risk, 18; nonviable tissue, 12; 16, no definition. Perfusion parameters varied widely; eg, 9 different MR, 6 different CT parameters for the 'at risk'/'not at risk threshold.' Median threshold values varied up to 4-fold, eg, for the 'at risk'/'not at risk threshold,' median cerebral blood flow ranged from 18 to 37ml/100g/min; mean transit time from 1.8 to 8.3 seconds relative to the contralateral side. The influence of reperfusion and duration of ischemia could not be assessed. Interpretation: CT and MR perfusion imaging viability thresholds in stroke are derived from small numbers of patients, variable perfusion analysis methods and definitions of tissue states. Greater consistency of methods would help determine reliable perfusion viability values for wider clinical use of perfusion imaging. ANN NEUROL 2011 [ABSTRACT FROM AUTHOR]

Background: Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model.Methods: In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa.Findings: In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high.Interpretation: To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI.Funding: The Netherlands Organisation for Health Research and Development. [ABSTRACT FROM AUTHOR]

Proton magnetic resonance spectroscopy yields metabolic information and has proved to be a useful addition to structural imaging in neurological diseases. We applied short-echo time Spectroscopic Imaging in a cohort of 42 patients with secondary progressive multiple sclerosis (SPMS). Linear modelling with respect to brain tissue type yielded metabolite levels that were significantly different in white matter lesions compared with normal-appearing white matter, suggestive of higher myelin turnover (higher choline), higher metabolic rate (higher creatine) and increased glial activity (higher myo-inositol) within the lesions. These findings suggest that the lesions have ongoing cellular activity that is not consistent with the usual assumption of ‘chronic’ lesions in SPMS, and may represent a target for repair therapies. [ABSTRACT FROM AUTHOR]

E-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients. Clinical utility of electronic Alberta stroke program early computed tomography score software in the ENCHANTED trial database. Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. [Extracted from the article]

Purpose Perivascular spaces (PVS) are associated with ageing, cerebral small vessel disease, inflammation and increased blood brain barrier permeability. Most studies to date use visual rating scales to assess PVS, but these are prone to observer variation. Methods We developed a semi-automatic computational method that extracts PVS on bilateral ovoid basal ganglia (BG) regions on intensity-normalised T2-weighted magnetic resonance images. It uses Analyze™10.0 and was applied to 100 mild stroke patients’ datasets. We used linear regression to test association between BGPVS count, volume and visual rating scores; and between BGPVS count & volume, white matter hyperintensity (WMH) rating scores (periventricular: PVH; deep: DWMH) & volume, atrophy rating scores and brain volume. Results In the 100 patients WMH ranged from 0.4 to 119 ml, and total brain tissue volume from 0.65 to 1.45 l. BGPVS volume increased with BGPVS count (67.27, 95%CI [57.93 to 76.60], p < 0.001). BGPVS count was positively associated with WMH visual rating (PVH: 2.20, 95%CI [1.22 to 3.18], p < 0.001; DWMH: 1.92, 95%CI [0.99 to 2.85], p < 0.001), WMH volume (0.065, 95%CI [0.034 to 0.096], p < 0.001), and whole brain atrophy visual rating (1.01, 95%CI [0.49 to 1.53], p < 0.001). BGPVS count increased as brain volume (as % of ICV) decreased (−0.33, 95%CI [−0.53 to −0.13], p = 0.002). Comparison with existing method BGPVS count and volume increased with the overall increase of BGPVS visual scores (2.11, 95%CI [1.36 to 2.86] for count and 0.022, 95%CI [0.012 to 0.031] for volume, p < 0.001). Distributions for PVS count and visual scores were also similar. Conclusions This semi-automatic method is applicable to clinical protocols and offers quantitative surrogates for PVS load. It shows good agreement with a visual rating scale and confirmed that BGPVS are associated with WMH and atrophy measurements. [ABSTRACT FROM AUTHOR]

Background and aims Enlarged perivascular spaces (also known as Virchow- Robin spaces) on T2-weighted brain magnetic resonance imaging are common, but their etiology, and specificity to small vessel as opposed to general cerebrovascular disease or ageing, is unclear. We tested the association between enlarged perivascular spaces and ischemic stroke subtype, other markers of small vessel disease, and common vascular risk factors. Methods We prospectively recruited patients with acute stroke, diagnosed and subtyped by a stroke physician using clinical features and brain magnetic resonance imaging. A neuroradiologist rated basal ganglia and centrum semiovale enlarged perivascular spaces on a five-point scale, white matter lesions, recent and old infarcts, and cerebral atrophy. We assessed associations between basal ganglia-, centrum semiovale- and total (combined basal ganglia and centrum semiovale) enlarged perivascular spaces, stroke subtype, white matter lesions, atrophy, and vascular risk factors. Results Among 298 patients (mean age 68 years), after adjusting for vascular risk factors and white matter lesions, basal ganglia-enlarged perivascular spaces were associated with increasing age ( P = 0·001), centrum semiovale-enlarged perivascular spaces ( P < 0·001), cerebral atrophy ( P = 0·03), and lacunar stroke subtype ( P = 0·04). Centrum semiovale-enlarged perivascular spaces were associated mainly with basal ganglia-enlarged perivascular spaces. Total enlarged perivascular spaces were associated with increasing age ( P = 0·01), deep white matter lesions ( P = 0·005), and previous stroke ( P = 0·006). Conclusions Enlarged perivascular spaces are associated with age, lacunar stroke subtype and white matter lesions and should be considered as another magnetic resonance imaging marker of cerebral small vessel disease. Further evaluation of enlarged perivascular spaces in studies of ageing, stroke, and dementia is needed to determine their pathophysiological importance. [ABSTRACT FROM AUTHOR]

Background: Diabetes-related lower limb amputations are associated with considerable morbidity and mortality and are usually preceded by foot ulceration. The available systematic reviews of aggregate data are compromised because the primary studies report both adjusted and unadjusted estimates. As adjusted meta-analyses of aggregate data can be challenging, the best way to standardise the analytical approach is to conduct a meta-analysis based on individual patient data (IPD).There are however many challenges and fundamental methodological omissions are common; protocols are rare and the assessment of the risk of bias arising from the conduct of individual studies is frequently not performed, largely because of the absence of widely agreed criteria for assessing the risk of bias in this type of review. In this protocol we propose key methodological approaches to underpin our IPD systematic review of prognostic factors of foot ulceration in diabetes.Review questions;1. What are the most highly prognostic factors for foot ulceration (i.e. symptoms, signs, diagnostic tests) in people with diabetes?2. Can the data from each study be adjusted for a consistent set of adjustment factors?3. Does the model accuracy change when patient populations are stratified according to demographic and/or clinical characteristics?Methods: MEDLINE and EMBASE databases from their inception until early 2012 were searched and the corresponding authors of all eligible primary studies invited to contribute their raw data. We developed relevant quality assurance items likely to identify occasions when study validity may have been compromised from several sources. A confidentiality agreement, arrangements for communication and reporting as well as ethical and governance considerations are explained.We have agreement from the corresponding authors of all studies which meet the eligibility criteria and they collectively possess data from more than 17000 patients. We propose, as a provisional analysis plan, to use a multi-level mixed model, using "study" as one of the levels. Such a model can also allow for the within-patient clustering that occurs if a patient contributes data from both feet, although to aid interpretation, we prefer to use patients rather than feet as the unit of analysis. We intend to only attempt this analysis if the results of the investigation of heterogeneity do not rule it out and the model diagnostics are acceptable.Discussion: This review is central to the development of a global evidence-based strategy for the risk assessment of the foot in patients with diabetes, ensuring future recommendations are valid and can reliably inform international clinical guidelines. [ABSTRACT FROM AUTHOR]

Background: White matter lesions (WML) and brain atrophy are important biomarkers in stroke and dementia. Stroke lesions, either acute or old, symptomatic or silent, are common in older people. Such stroke lesions can have similar signals to WML and cerebrospinal fluid (CSF) on magnetic resonance (MR) images, and may be classified accidentally as WML or CSF by MR image processing algorithms, distorting WML and brain atrophy volume from the true volume. We evaluated the effect that acute or old stroke lesions at baseline, and new stroke lesions occurring during follow-up, could have on measurement of WML volume, cerebral atrophy and their longitudinal progression. Methods: We used MR imaging data from patients who had originally presented with acute lacunar or minor cortical ischaemic stroke symptoms, recruited prospectively, who were scanned at baseline and about 3 years later. We measured WML and CSF volumes (ml) semi-automatically. We manually outlined the acute index stroke lesion (ISL), any old stroke lesions present at baseline, and new lesions appearing de novo during follow-up. We compared baseline and follow-up WML volume, cerebral atrophy and their longitudinal progression excluding and including the acute ISL, old and de novo stroke lesions. A non-parametric test (Wilcoxon's signed rank test) was used to compare the effects. Results: Among 46 patients (mean age 72 years), 33 had an ISL visible on MR imaging (median volume 2.05 ml, IQR 0.88-8.88) and 7 of the 33 had old lacunes at baseline: WML volume was 8.54 ml (IQR 5.86-15.80) excluding versus 10.98 ml (IQR 6.91-24.86) including ISL (p < 0.001). At follow-up, median 39 months later (IQR 30-45), 3 patients had a de novo stroke lesion; total stroke lesion volume had decreased in 11 and increased in 22 patients: WML volume was 12.17 ml (IQR 8.54-19.86) excluding versus 14.79 ml (IQR 10.02-38.03) including total stroke lesions (p < 0.001). Including/excluding lacunes at baseline or follow-up also made small differences. Twenty-two of the 33 patients had tissue loss due to stroke lesions between baseline and follow-up, resulting in a net median brain tissue volume loss (i.e. atrophy) during follow-up of 24.49 ml (IQR 12.87-54.01) excluding versus 24.61 ml (IQR 15.54-54.04) including tissue loss due to stroke lesions (p < 0.001). Including stroke lesions in the WML volume added substantial noise, reduced statistical power, and thus increased sample size estimated for a clinical trial. Conclusions: Failure to exclude even small stroke lesions distorts WML volume, cerebral atrophy and their longitudinal progression measurements. This has important implications for design and sample size calculations for observational studies and randomised trials using WML volume, WML progression or brain atrophy as outcome measures. Improved methods of discriminating between stroke lesions and WML, and between tissue loss due to stroke lesions and true brain atrophy are required. Copyright © 2012 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Background: Early signs of ischaemic stroke on computerised tomography (CT) scanning are subtle but CT is the most widely available diagnostic test for stroke. Scoring methods that code for the extent of brain ischaemia may improve stroke diagnosis and quantification of the impact of ischaemia. Methodology and Principal Findings: We showed CT scans from patients with acute ischaemic stroke (n = 32, with different patient characteristics and ischaemia signs) to doctors in stroke-related specialties world-wide over the web. CT scans were shown twice, randomly and blindly. Observers entered their scan readings, including early ischaemic signs by three scoring methods, into the web database. We compared observers' scorings to a reference standard neuroradiologist using area under receiver operator characteristic curve (AUC) analysis, Cronbach's alpha and logistic regression to determine the effect of scales, patient, scan and observer variables on detection of early ischaemic changes. Amongst 258 readers representing 33 nationalities and six specialties, the AUCs comparing readers with the reference standard detection of ischaemic signs were similar for all scales and both occasions. Being a neuroradiologist, slower scan reading, more pronounced ischaemic signs and later time to CT all improved detection of early ischaemic signs and agreement on the rating scales. Scan quality, stroke severity and number of years of training did not affect agreement. Conclusions: Large-scale observer reliability studies are possible using web-based tools and inform routine practice. Slower scan reading and use of CT infarct rating scales improve detection of acute ischaemic signs and should be encouraged to improve stroke diagnosis. [ABSTRACT FROM AUTHOR]

Objective: Brain tissue segmentation by conventional threshold-based techniques may have limited accuracy and repeatability in older subjects. We present a new multispectral magnetic resonance (MR) image analysis approach for segmenting normal and abnormal brain tissue, including white matter lesions (WMLs).Methods: We modulated two 1.5T MR sequences in the red/green colour space and calculated the tissue volumes using minimum variance quantisation. We tested it on 14 subjects, mean age 73.3 +/- 10 years, representing the full range of WMLs and atrophy. We compared the results of WML segmentation with those using FLAIR-derived thresholds, examined the effect of sampling location, WML amount and field inhomogeneities, and tested observer reliability and accuracy.Results: FLAIR-derived thresholds were significantly affected by the location used to derive the threshold (P = 0.0004) and by WML volume (P = 0.0003), and had higher intra-rater variability than the multispectral technique (mean difference +/- SD: 759 +/- 733 versus 69 +/- 326 voxels respectively). The multispectral technique misclassified 16 times fewer WMLs.Conclusion: Initial testing suggests that the multispectral technique is highly reproducible and accurate with the potential to be applied to routinely collected clinical MRI data. [ABSTRACT FROM AUTHOR]

Brain iron deposits (IDs) are inversely associated with cognitive function in community-dwelling older people, but their association with cognition after ischemic stroke, and whether that differs from microbleeds, is unknown. We quantified basal ganglia IDs (BGID) and microbleeds (BMBs) semi-automatically on brain magnetic resonance images from patients with minor stroke (NIHSS < 7), at presentation and 12 months after stroke. We administered the National Adult Reading Test (NART, estimates premorbid or peak adult cognition) and the Revised Addenbrooke's Cognitive Examination (ACE-R; current cognition) at 1 and 12 months after stroke. We adjusted analyses for baseline cognition, age, gender, white matter hyperintensity (WMH) volume and vascular risk factors. In 200 patients, mean age 65 years, striatal IDs and BMBs volumes did not change over the 12 months. Baseline BGID volumes correlated positively with NART scores at both times (ρ = 0.19, p < 0.01). Baseline and follow-up BGID volumes correlated positively with age (ρ = 0.248, p < 0.001 and ρ = 0.271, p < 0.001 respectively), but only baseline (and not follow-up) BMB volume correlated with age (ρ = 0.129, p < 0.05). Both smoking and baseline WMH burden predicted verbal fluency and visuospatial abilities scores (B = −1.13, p < 0.02 and B = −0.22, p = 0.001 respectively) at 12 months after stroke. BGIDs and BMBs are associated differently with cognition post-stroke; studies of imaging and post-stroke cognition should adjust for premorbid cognition. The positive correlation of BGID with NART may reflect the lower premorbid cognition in patients with stroke at younger vs older ages. [ABSTRACT FROM AUTHOR]