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Perivascular spaces (PVS) relate to poor cognition, depression in older age, Parkinson's disease, inflammation, hypertension and cerebral small vessel disease when they are enlarged and visible in magnetic resonance imaging (MRI). In this paper we explore how to classify the density of the enlarged PVS in the basal ganglia (BG) using texture description of structural brain MRI. The texture of the BG region is described by means of first order statistics and features derived from the co-occurrence matrix, both computed from the original image and the coefficients yielded by the discrete wavelet transform (WSF and WCF, respectively), and local binary patterns (LBP). Experimental results with a Support Vector Machine (SVM) classifier show that WCF achieves an accuracy of 80.03%. [ABSTRACT FROM AUTHOR]

Background: Apparent diffusion coefficient (ADC) thresholds are used to determine acute stroke lesion volume, but the reliability of this approach and comparability to the volume of the magnetic resonance diffusion-weighted imaging (MR-DWI) hyperintense lesion is unclear. Methods: We prospectively recruited and clinically assessed patients who had experienced acute ischemic stroke and performed DWI less than 24 hours and at 3 to 7 days after stroke. We compared the volume of the manually outlined DW hyperintense lesion (reference standard) with lesion volumes derived from 3 commonly used ADC thresholds: .55 × 10−3/mm2/second−1, .65 × 10−3/mm2/second−1, and .75 × 10−3/mm2/second−1, with and without “editing” of erroneous tissue. We compared the volumes obtained by reference standard, “raw,” and “edited” thresholds. Results: Among 33 representative patients, the acute DWI lesion volume was 15,284 mm3; the median unedited/edited ADC volumes were 52,972/2786 mm3, 92,707/6,987 mm3, and 227,681/unmeasureable mm3 (.55 × 10−3/mm2/second−1, .65 × 10−3/mm2/second−1, and .75 × 10−3/mm2/second−1 thresholds, respectively). Subacute lesions gave similar differences. These differences between edited and unedited diffusion-weighted imaging and ADC volumes were statistically significant. Conclusions: Threshold-derived ADC volumes require substantial manual editing to avoid over- or underestimating the visible DWI lesion and should be used with caution. [Copyright &y& Elsevier]

Abstract: There is growing interest in investigating the role of subtle changes in blood–brain barrier (BBB) function in common neurological disorders and the possible use of imaging techniques to assess these abnormalities. Some studies have used dynamic contrast-enhanced MR imaging (DCE-MRI) and these have demonstrated much smaller signal changes than obtained from more traditional applications of the technique, such as in intracranial tumors and multiple sclerosis. In this work, preliminary results are presented from a DCE-MRI study of patients with mild stroke classified according to the extent of visible underlying white matter abnormalities. These data are used to estimate typical signal enhancement profiles in different tissue types and by degrees of white matter abnormality. The effect of scanner noise, drift and different intrinsic tissue properties on signal enhancement data is also investigated and the likely implications for interpreting the enhancement profiles are discussed. No significant differences in average signal enhancement or contrast agent concentration were observed between patients with different degrees of white matter abnormality, although there was a trend towards greater signal enhancement with more abnormal white matter. Furthermore, the results suggest that many of the factors considered introduce uncertainty of a similar magnitude to expected effect sizes, making it unclear whether differences in signal enhancement are truly reflective of an underlying BBB abnormality or due to an unrelated effect. As the ultimate aim is to achieve a reliable quantification of BBB function in subtle disorders, this study highlights the factors which may influence signal enhancement and suggests that further work is required to address the challenging problems of quantifying contrast agent concentration in healthy and diseased living human tissue and of establishing a suitable model to enable quantification of relevant physiological parameters. Meanwhile, it is essential that future studies use an appropriate control group to minimize these influences. [Copyright &y& Elsevier]

Abstract: There is increasing interest in obtaining quantitative imaging parameters to aid in the assessment of tumor responses to treatment. In this study, the feasibility of performing integrated diffusion, perfusion and permeability magnetic resonance imaging (MRI) for characterizing responses to dexamethasone in intracranial tumors was assessed. Eight patients with glioblastoma, five with meningioma and three with metastatic carcinoma underwent MRI prior to and 48–72 h following dexamethasone administration. The MRI protocol enabled quantification of the volume transfer constant (K trans), extracellular space volume fraction (ν e), plasma volume fraction (ν p), regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), longitudinal relaxation time (T 1) and mean diffusivity (D av). All subjects successfully completed the imaging protocol for the presteroid and poststeroid scans. Significant reductions were observed after the treatment for K trans, ν e and ν p in enhancing tumor as well as for T 1 and D av in the edematous brain in glioblastoma; on the other hand, for meningioma, significant differences were seen only in edematous brain T 1 and D av. No significant difference was observed for any parameter in metastatic carcinoma, most likely due to the small sample size. In addition, no significant difference was observed for enhancing tumor rCBF and rCBV in any of the tumor types, although the general trend was for rCBV to be reduced and for rCBF to be more variable. The yielded parameters provide a wealth of physiologic information and contribute to the understanding of dexamethasone actions on different types of intracranial tumors. [Copyright &y& Elsevier]

Background: In acute ischemic stroke, magnetic resonance diffusion-weighted imaging (DWI) is increasingly used to select patients for inclusion or as a surrogate outcome marker in clinical trials, or in routine practice. Little is known of what factors might affect DWI lesion size measurement. We examined morphologic factors that might affect DWI lesion measurement. Methods: On DWI obtained less than 24 hours after stroke, we categorized lesions according to DWI appearance (solitary or multifocal; well-defined or ill-defined edges), lesion size (5 cm3), and time to imaging (<6, 6–12, and 12–24 hours). Two observers (senior neuroradiologist; less-experienced imaging neuroscientist) measured all lesions. In 4 representative cases we assessed DWI lesion volume using two apparent diffusion coefficient thresholds (0.55 and 0.65 × 10−3 mm2/s). Results: Among 63 patients (33% imaged < 6 hours after stroke), the neuroradiologist measured larger lesion volumes than the imaging neuroscientist (median 4.29 v 3.50 cm3, respectively, P < .01). Differences between observers were greatest in patients scanned within 6 hours of stroke, in multifocal ill-defined or large lesions (all P < .01). Both apparent diffusion coefficient thresholds underestimated lesion extent and included remote normal tissue, particularly in multifocal ill-defined large lesions. Conclusion: DWI lesion characteristics influence lesion volume measurement. Large, multifocal, ill-defined DWI lesions obtained in less than 6 hours have the greatest variability. Trials using DWI should account for this in their study design. [Copyright &y& Elsevier]

Celiac disease is an autoimmune disorder induced by ingestion of gluten that affects 1% of the population and is characterized by gastrointestinal symptoms, weight loss, and anemia. We evaluated the presence of neurologic deficits and investigated whether the presence of antibodies to Transglutaminase 6 (TG6) increases the risk of neurologic defects in patients with a new diagnosis of celiac disease. We performed a prospective cohort study at a secondary-care gastroenterology center of 100 consecutive patients who received a new diagnosis of celiac disease based on gastroscopy and duodenal biopsy. We collected data on neurologic history, and patients were evaluated in a clinical examination along with magnetic resonance imaging of the brain, magnetic resonance (MR) spectroscopy of the cerebellum, and measurements of antibodies against TG6 in serum samples. The first 52 patients recruited underwent repeat MR spectroscopy at 1 year after a gluten-free diet (GFD). The primary aim was to establish if detection of antibodies against TG6 can be used to identify patients with celiac disease and neurologic dysfunction. Gait instability was reported in 24% of the patients, persisting sensory symptoms in 12%, and frequent headaches in 42%. Gait ataxia was found in 29% of patients, nystagmus in 11%, and distal sensory loss in 10%. Sixty percent of patients had abnormal results from magnetic resonance imaging, 47% had abnormal results from MR spectroscopy of the cerebellum, and 25% had brain white matter lesions beyond that expected for their age group. Antibodies against TG6 were detected in serum samples from 40% of patients—these patients had significant atrophy of subcortical brain regions compared with patients without TG6 autoantibodies. In patients with abnormal results from MR spectroscopy of the cerebellum, those on the GFD had improvements detected in the repeat MR spectroscopy 1 year later. In a prospective cohort study of patients with a new diagnosis of celiac disease at a gastroenterology clinic, neurologic deficits were common and 40% had circulating antibodies against TG6. We observed a significant reduction in volume of specific brain regions in patients with TG6 autoantibodies, providing evidence for a link between autoimmunity to TG6 and brain atrophy in patients with celiac disease. There is a need for early diagnosis, increased awareness of the neurologic manifestations among clinicians, and reinforcement of adherence to a strict GFD by patients to avoid permanent neurologic disability. [ABSTRACT FROM AUTHOR]

Abstract: Blood-brain barrier (BBB) dysfunction may contribute to the risk of Alzheimer''s disease (AD). Dynamic contrast-enhanced magnetic resonance imaging (MRI) was performed repeatedly nine times before and up to 30 min following a 20 ml Gd-DTPA bolus injection in 15 AD participants and 15 healthy older people. For each participant, small circular regions of interest (size: 9 voxels) were placed to sample widely the deep gray matter (12 regions), cortical gray matter (72 regions), white matter (72 regions) and CSF (8 regions) as well as the basilar and internal carotid arteries (3 regions). Data were analysed using mixed effects models. There was no overall significant difference for AD subjects versus controls, but there was a significant effect for the time-by-AD interaction. Estimated marginal means remained essentially unchanged in AD subjects, but increased slowly after 15 min in healthy controls. An initial rise in gray matter MRI signal intensity followed by a later increase was also seen in AD participants after adjusting for CSF MRI signal intensities. The data suggest that BBB permeability is present even at an early stage of AD. Though the extent of leakage was no greater than that of non-demented people of a similar age in this small sample, the temporal pattern differed, indicating different blood–brain–CSF compartmental kinetics. [Copyright &y& Elsevier]

Abstract: The choice of the number (N) and orientation of diffusion sampling gradients required to measure accurately the water diffusion tensor remains contentious. Monte Carlo studies have suggested that between 20 and 30 uniformly distributed sampling orientations are required to provide robust estimates of water diffusions parameters. These simulations have not, however, taken into account what effect random subject motion, specifically rotation, might have on optimised gradient schemes, a problem which is especially relevant to clinical diffusion tensor MRI (DT-MRI). Here this question is investigated using Monte Carlo simulations of icosahedral sampling schemes and in vivo data. These polyhedra-based schemes, which have the advantage that large N can be created from optimised subsets of smaller N, appear to be ideal for the study of restless subjects since if scanning needs to be prematurely terminated it should be possible to identify a subset of images that have been acquired with a near optimised sampling scheme. The simulations and in vivo data show that as N increases, the rotational variance of fractional anisotropy (FA) estimates becomes progressively less dependent on the magnitude of subject rotation (α), while higher FA values are progressively underestimated as α increases. These data indicate that for large subject rotations the B-matrix should be recalculated to provide accurate diffusion anisotropy information. [Copyright &y& Elsevier]

Abstract: Eddy current-induced geometric distortions of single-shot, diffusion-weighted, echo-planar (DW-EP) images are a major confounding factor to the accurate determination of water diffusion parameters in diffusion tensor MRI (DT-MRI). Previously, it has been suggested that these geometric distortions can be removed from brain DW-EP images using affine transformations determined from phantom calibration experiments using iterative cross-correlation (ICC). Since this approach was first described, a number of image-based registration methods have become available that can also correct eddy current-induced distortions in DW-EP images. However, as yet no study has investigated whether separate eddy current calibration or image-based registration provides the most accurate way of removing these artefacts from DT-MRI data. Here we compare how ICC phantom calibration and affine FLIRT (http://www.fmrib.ox.ac.uk), a popular image-based multi-modal registration method that can correct both eddy current-induced distortions and bulk subject motion, perform when registering DW-EP images acquired with different slice thicknesses (2.8 and 5 mm) and b-values (1000 and 3000 s/mm2). With the use of consistency testing, it was found that ICC was a more robust algorithm for correcting eddy current-induced distortions than affine FLIRT, especially at high b-value and small slice thickness. In addition, principal component analysis demonstrated that the combination of ICC phantom calibration (to remove eddy current-induced distortions) with rigid body FLIRT (to remove bulk subject motion) provided a more accurate registration of DT-MRI data than that achieved by affine FLIRT. [Copyright &y& Elsevier]

Early ischemic change after stroke can be demonstrated with diffusion-weighted imaging (DWI) and quantified by measuring the apparent diffusion coefficient (ADC) and/or lesion volume. We examined the reliability and reproducibility of lesion volume and ADC measurement on DWI images, and discuss the implications for clinical studies. Using 38 DWI scans from 15 stroke patients, two observers (a physicist and a neuroscience graduate) blind to each other, recorded the lesion volume on DWI sequences, measured the ADC values in this volume and calculated the ratio of ischemic: control ADC (ADCr). One observer repeated his measurements blind to his first, and also examined the effect on lesion volume and ADC of deliberately varying by only one pixel, the outline of the visible boundary of the lesion. The inter and intra-rater reliability were worse for lesion volume than ADC or ADCr measurements: lesion volume, inter-rater coefficient of variation (CoV) 85 ± 130%, intra-rater CoV 20+/−SD80% (p < 0.05); ADC inter-rater CoV 7.7 ± SD 19%, intra-rater CoV 0.2 ± SD 12% (p = NS); and ADCr inter-rater CoV 8 ± SD27%, intra-rater CoV 0.8 ± SD73% (p = NS). Altering the position of the outline tracing of the lesion boundary by one pixel altered the measured volumes by 22 ± SD25% (p < 0.05), but ADC values were altered by only 2.9 ± SD4.9% and ADCr by 2.7 ± SD4.8% (p = NS). ADC and ADCr values are more reliable and reproducible than DWI lesion size in acute ischemic stroke because altering where the lesion boundary is measured has a much greater impact on lesion volume than on the ADC or ADCr. This effect is greatest in large lesions. [Copyright &y& Elsevier]

Cerebral small vessel disease (SVD) comprises various pathological processes affecting small brain vessels and damaging white and grey matter. In this paper, we propose a framework comprising region of interest sampling, dynamic spectral and texture description, functional principal component analysis, and statistical analysis to study exogenous contrast agent distribution over time in various brain regions in patients with recent mild stroke and SVD features.We compared our results against current semi-quantitative surrogates of dysfunction such as signal enhancement area and slope. Biological sex, stroke lesion type and overall burden of white matter hyperintensities (WMH) were significant predictors of intensity, spectral, and texture features extracted from the ventricular region (p -value < 0.05), explaining between a fifth and a fourth of the data variance (0.20 ≤Adj. R 2 ≤ 0.25). We observed that spectral feature reflected more the dysfunction compared to other descriptors since the overall WMH burden explained consistently the power spectra variability in blood vessels, cerebrospinal fluid, deep grey matter and white matter. Our preliminary results show the potential of the framework for the analysis of dynamic contrast-enhanced brain magnetic resonance imaging acquisitions in SVD since significant variation in our metrics was related to the burden of SVD features. Therefore, our proposal may increase sensitivity to detect subtle features of small vessel dysfunction. A public version of the code will be released on our research website. [ABSTRACT FROM AUTHOR]

• Radiomics in conventionally segmented tissues can identify MRI scans that had a stroke. • Patient's advanced age can negatively influence classification results. • Feature selection and stroke subtype influence but do not determine accuracy. • Stroke subtype cannot be ascertained from texture analysis in brain tissues. The differential quantification of brain atrophy, white matter hyperintensities (WMH) and stroke lesions is important in studies of stroke and dementia. However, the presence of stroke lesions is usually overlooked by automatic neuroimage processing methods and the-state-of-the-art deep learning schemes, which lack sufficient annotated data. We explore the use of radiomics in identifying whether a brain magnetic resonance imaging (MRI) scan belongs to an individual that had a stroke or not. We used 1800 3D sets of MRI data from three prospective studies: one of stroke mechanisms and two of cognitive ageing, evaluated 114 textural features in WMH, cerebrospinal fluid, deep grey and normal-appearing white matter, and attempted to classify the scans using a random forest and support vector machine classifiers with and without feature selection. We evaluated the discriminatory power of each feature independently in each population and corrected the result against Type 1 errors. We also evaluated the influence of clinical parameters in the classification results. Subtypes of ischaemic strokes (i.e. lacunar vs. cortical) cannot be discerned using radiomics, but the presence of a stroke-type lesion can be ascertained with accuracies ranging from 0.7 < AUC < 0.83. Feature selection, tissue type, stroke subtype and MRI sequence did not seem to determine the classification results. From all clinical variables evaluated, age correlated with the proportion of images classified correctly using either different or the same descriptors (Pearson r = 0.31 and 0.39 respectively, p < 0.001). Texture features in conventionally automatically segmented tissues may help in the identification of the presence of previous stroke lesions on an MRI scan, and should be taken into account in transfer learning strategies of the-state-of-the-art deep learning schemes. [ABSTRACT FROM AUTHOR]

Abstract: A magnetic resonance proton spectroscopic imaging (SI) technique was developed to measure regional brain temperatures in human subjects. The technique was validated in a homogeneous phantom and in four healthy volunteers. Simulations and calculations determined the theoretical measurement precision as approximately ±0.3°C for individual 1-ml voxels. In healthy volunteers, repeated measurements on individual voxels had an S.D.=1.2°C. In a clinical study, 40 patients with acute ischemic stroke were imaged within 26 h (mean, 10 h) of onset. Temperatures were highest in the region that appeared abnormal (i.e., ischemic) on diffusion-weighted imaging (DWI) compared with a normal-appearing brain. The mean temperature difference between the DWI “lesion” area and the “normal brain” was 0.17°C [P<10−3; range, 2.45°C (hotter)–2.17°C (cooler)]. Noninvasive temperature measurement by SI has sufficient precision to be used in studies of pathophysiology in stroke and in other brain disorders and to monitor therapies. [Copyright &y& Elsevier]