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Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results., (Copyright © 2021. Published by Elsevier Inc.)

One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data. This study aims to apply oversampling strategies in an attempt to balance the classes and improve classification performance. We evaluated four different classifiers from k-nearest neighbors (k-NN), support vector machine (SVM), multilayer perceptron (MLP) and decision trees (DT) with 73 oversampling strategies. In this work, we used imbalanced learning oversampling techniques to improve classification in datasets that are distinctively sparser and clustered. This work reports the best oversampling and classifier combinations and concludes that the usage of oversampling methods always outperforms no oversampling strategies hence improving the classification results., Competing Interests: The authors have declared that no competing interests exist.

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., Competing Interests: Declaration of competing interest None., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: 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., Materials and Methods: 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., 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)., Conclusions: 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., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Purpose: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metric of white matter (WM) damage that addresses this need., Methods: We obtained WMH and normal-appearing white matter (NAWM) volumes from brain structural MRI from community dwelling older individuals and stroke patients enrolled in three different studies, using two automatic methods followed by manual editing by two to four observers blind to each other. We calculated the average intensity values on brain structural fluid-attenuation inversion recovery (FLAIR) MRI for the NAWM and WMH. The white matter damage metric is calculated as the proportion of WMH in brain tissue weighted by the relative image contrast of the WMH-to-NAWM. The new metric was evaluated using tissue microstructure parameters and visual ratings of small vessel disease burden and WMH: Fazekas score for WMH burden and Prins scale for WMH change., Results: The correlation between the WM damage metric and the visual rating scores (Spearman ρ > =0.74, p < 0.0001) was slightly stronger than between the latter and WMH volumes (Spearman ρ > =0.72, p < 0.0001). The repeatability of the WM damage metric was better than WM volume (average median difference between measurements 3.26% (IQR 2.76%) and 5.88% (IQR 5.32%) respectively). The follow-up WM damage was highly related to total Prins score even when adjusted for baseline WM damage (ANCOVA, p < 0.0001), which was not always the case for WMH volume, as total Prins was highly associated with the change in the intense WMH volume (p = 0.0079, increase of 4.42 ml per unit change in total Prins, 95%CI [1.17 7.67]), but not with the change in less-intense, subtle WMH, which determined the volumetric change., Conclusion: The new metric is practical and simple to calculate. It is robust to variations in image processing methods and scanning protocols, and sensitive to subtle and severe white matter damage.

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.

Objective: Interpretation of magnetic resonance (MR) imaging of the fetal brain in utero is primarily undertaken using 2D images to provide anatomical information about structural abnormalities. It is now possible to obtain 3D image acquisitions that allow measurement of fetal brain volumes that are potentially useful clinically. The aim of our current work is to provide reference values of total brain volumes obtained from a cohort of low risk fetuses with no abnormalities on ante-natal ultrasonography and in utero MR imaging., Method: Images from volume MR acquisitions of 132 fetuses were used to extract brain volumes by manual segmentation. Reproducibility and reliability were assessed by analysis of the results of two subgroups who had repeated measurements made by the primary and a secondary observer., Results: Intra-observer and inter-observer agreement was high with no statistically significant differences between and within observers (p = 0.476 and p = 0.427, respectively). The results of the brain volume assessments are presented graphically with mean and 95% prediction limits alongside estimates of normal growth rates., Conclusion: We have shown that fetal brain volumes can be reliably extracted from in utero MR (iuMR) imaging 3D datasets with a high degree of reproducibility. The resultant data could potentially be used as a reference tool in the clinical setting. © 2016 John Wiley & Sons, Ltd., (© 2016 John Wiley & Sons, Ltd.)

Introduction: Subtle inhomogeneities in the scanner's magnetic fields (B0 and B1) alter the intensity levels of the structural magnetic resonance imaging (MRI) affecting the volumetric assessment of WMH changes. Here, we investigate the influence that (1) correcting the images for the B1 inhomogeneities (i.e. bias field correction (BFC)) and (2) selection of the WMH change assessment method can have on longitudinal analyses of WMH progression and discuss possible solutions., Methods: We used brain structural MRI from 46 mild stroke patients scanned at stroke onset and 3 years later. We tested three BFC approaches: FSL-FAST, N4 and exponentially entropy-driven homomorphic unsharp masking (E(2)D-HUM) and analysed their effect on the measured WMH change. Separately, we tested two methods to assess WMH changes: measuring WMH volumes independently at both time points semi-automatically (MCMxxxVI) and subtracting intensity-normalised FLAIR images at both time points following image gamma correction. We then combined the BFC with the computational method that performed best across the whole sample to assess WMH changes., Results: Analysis of the difference in the variance-to-mean intensity ratio in normal tissue between BFC and uncorrected images and visual inspection showed that all BFC methods altered the WMH appearance and distribution, but FSL-FAST in general performed more consistently across the sample and MRI modalities. The WMH volume change over 3 years obtained with MCMxxxVI with vs. without FSL-FAST BFC did not significantly differ (medians(IQR)(with BFC) = 3.2(6.3) vs. 2.9(7.4)ml (without BFC), p = 0.5), but both differed significantly from the WMH volume change obtained from subtracting post-processed FLAIR images (without BFC)(7.6(8.2)ml, p < 0.001). This latter method considerably inflated the WMH volume change as subtle WMH at baseline that became more intense at follow-up were counted as increase in the volumetric change., Conclusions: Measurement of WMH volume change remains challenging. Although the overall volumetric change was not significantly affected by the application of BFC, these methods distorted the image intensity distribution affecting subtle WMH. Subtracting the FLAIR images at both time points following gamma correction seems a promising technique but is adversely affected by subtle WMH. It is important to take into account not only the changes in volume but also in the signal intensity.

Rationale: Cerebral small vessel disease (SVD) is common in ageing and patients with dementia and stroke. Its manifestations on magnetic resonance imaging (MRI) include white matter hyperintensities, lacunes, microbleeds, perivascular spaces, small subcortical infarcts, and brain atrophy. Many studies focus only on one of these manifestations. A protocol for the differential assessment of all these features is, therefore, needed., Aims: To identify ways of quantifying imaging markers in research of patients with SVD and operationalize the recommendations from the STandards for ReportIng Vascular changes on nEuroimaging guidelines. Here, we report the rationale, design, and methodology of a brain image analysis protocol based on our experience from observational longitudinal studies of patients with nondisabling stroke., Design: The MRI analysis protocol is designed to provide quantitative and qualitative measures of disease evolution including: acute and old stroke lesions, lacunes, tissue loss due to stroke, perivascular spaces, microbleeds, macrohemorrhages, iron deposition in basal ganglia, substantia nigra and brain stem, brain atrophy, and white matter hyperintensities, with the latter separated into intense and less intense. Quantitative measures of tissue integrity such as diffusion fractional anisotropy, mean diffusivity, and the longitudinal relaxation time are assessed in regions of interest manually placed in anatomically and functionally relevant locations, and in others derived from feature extraction pipelines and tissue segmentation methods. Morphological changes that relate to cognitive deficits after stroke, analyzed through shape models of subcortical structures, complete the multiparametric image analysis protocol., Outcomes: Final outcomes include guidance for identifying ways to minimize bias and confounds in the assessment of SVD and stroke imaging biomarkers. It is intended that this information will inform the design of studies to examine the underlying pathophysiology of SVD and stroke, and to provide reliable, quantitative outcomes in trials of new therapies and preventative strategies.

Object: We sought to measure brain metabolite levels in healthy older people., Materials and Methods: Spectroscopic imaging at the level of the basal ganglia was applied in 40 participants aged 73-74 years. Levels of the metabolites N-acetyl aspartate (NAA), choline, and creatine were determined in "institutional units" (IU) corrected for T1 and T2 relaxation effects. Structural imaging enabled determination of grey matter (GM), white matter (WM), and cerebrospinal fluid content. ANOVA analysis was carried out for voxels satisfying quality criteria., Results: Creatine levels were greater in GM than WM (57 vs. 44 IU, p < 0.001), whereas choline and NAA levels were greater in WM than GM [13 vs. 10 IU (p < 0.001) and 76 versus 70 IU (p = 0.03), respectively]. The ratio of NAA/cre was greater in WM than GM (2.1 vs. 1.4, p = 0.001) as was that of cho/cre (0.32 vs. 0.16, p < 0.001). A low voxel yield was due to brain atrophy and the difficulties of shimming over an extended region of brain., Conclusion: This study addresses the current lack of information on brain metabolite levels in older adults. The normal features of ageing result in a substantial loss of reliable voxels and should be taken into account when planning studies. Improvements in shimming are also required before the methods can be applied more widely.

Background: Paediatric diffuse intrinsic pontine glioma (DIPG) is noteworthy for its fibrillary infiltration through neuroparenchyma and its resultant irregular shape. Conventional volumetry methods aim to approximate such irregular tumours to a regular ellipse, which could be less accurate when assessing treatment response on surveillance MRI. Region-of-interest (ROI) volumetry methods, using manually traced tumour profiles on contiguous imaging slices and subsequent computer-aided calculations, may prove more reliable., Objective: To evaluate whether the reliability of MRI surveillance of DIPGs can be improved by the use of ROI-based volumetry., Materials and Methods: We investigated the use of ROI- and ellipsoid-based methods of volumetry for paediatric DIPGs in a retrospective review of 22 MRI examinations. We assessed the inter- and intraobserver variability of the two methods when performed by four observers., Results: ROI- and ellipsoid-based methods strongly correlated for all four observers. The ROI-based volumes showed slightly better agreement both between and within observers than the ellipsoid-based volumes (inter-[intra-]observer agreement 89.8% [92.3%] and 83.1% [88.2%], respectively). Bland-Altman plots show tighter limits of agreement for the ROI-based method., Conclusion: Both methods are reproducible and transferrable among observers. ROI-based volumetry appears to perform better with greater intra- and interobserver agreement for complex-shaped DIPG.

Objectives: To create and evaluate an interactive software tool for measuring imaging data in situations where hand-drawn region-of-interest measurements are unfeasible, for example, when the structure of interest is patchy with ill-defined boundaries., Methods: An interactive grid overlay software tool was implemented that enabled coding of voxels dependent on their imaging appearance with a series of user-defined classes. The Grid Analysis Tool (GAT) was designed to automatically extract quantitative imaging data, grouping the results by tissue class. Inter- and intra-observer reproducibility was evaluated by six observers of various backgrounds in a study of acute stroke patients., Results: The software tool enabled a more detailed classification of the stroke lesion than would be possible with a region-of-interest approach. However, inter-observer coefficients of variation (CVs) were relatively high, reaching 70% in "possibly abnormal" tissue and around 15-20% in normal appearing tissues, while intra-observer CVs were no more than 13% in "possibly abnormal" tissue and generally less than 1% in normal-appearing tissues., Conclusions: The grid-overlay method overcomes some of the limitations of conventional Region Of Interest (ROI) approaches, providing a viable alternative for segmenting patchy lesions with ill-defined boundaries, but care is required to ensure acceptable reproducibility if the method is applied by multiple observers., Key Points: Computer software developed to overcome limitations of conventional regions of interest measurements • This software is suitable for patchy lesions with ill-defined borders • Allows a more detailed assessment of imaging data.

Imaging-based markers of treatment response are increasingly being used in studies of brain-tumour therapies, for evaluating novel treatments and further understanding of existing therapies. An ultimate goal of these studies is to identify pre- or early-stage treatment imaging biomarkers that enable prediction of subsequent treatment response. We hypothesised that pretreatment MRI-based measurements of tumoural perfusion may provide a suitable imaging-based biomarker for prediction of subsequent treatment response and evaluated this in a group of nine high-grade glioma patients undergoing dexamethasone treatment. A strong positive correlation was observed between tumoural blood flow (R(2)=0.90, p<0.001) and tumoural blood volume (R(2)=0.76, p=0.002), and subsequent treatment response as measured by alterations in tumour leakage properties. These preliminary results indicate that measurements of tumoural perfusion may provide useful imaging biomarkers for predicting treatment response to dexamethasone and would therefore also be worth evaluating in newer emerging therapies.

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.

Background and Purpose: Lacunar stroke is associated with endothelial dysfunction and histologically with intrinsic cerebral microvascular disease of unknown cause. Endothelial dysfunction could impair blood-brain barrier integrity. We assessed background blood-brain barrier leakage in patients with lacunar ischemic stroke compared with cortical stroke controls., Methods: We recruited patients with lacunar or mild cortical ischemic stroke and assessed generalized cerebral blood-brain barrier leak with MRI and intravenous gadolinium at least 1 month after stroke. We used detailed image processing to compare signal change before and for 30 minutes postcontrast throughout gray matter, white matter, and cerebrospinal fluid with summary analyses and general linear modeling., Results: Among 48 patients (29 lacunar, 19 cortical), postcontrast enhancement was significantly higher in cerebrospinal fluid (P=0.04, Mann-Whitney U), and nonsignificantly higher in white matter, in lacunar than in cortical strokes, with no difference in gray matter. General linear modeling confirmed significantly greater postcontrast enhancement in cerebrospinal fluid in lacunar patients than in cortical controls (t=3.37, P<0.0008)., Conclusions: These preliminary data suggest that the blood-brain barrier may be dysfunctional throughout subcortical white matter (white matter drains via interstitial spaces to cerebrospinal fluid) in patients with lacunar stroke. Further studies are required to confirm these findings and determine whether abnormal blood-brain barrier might predate development of lacunar disease. Blood-brain barrier dysfunction may be an important mechanism for brain damage in cerebral microvascular disease.

Background and Purpose: Several methods are available to assess the magnetic resonance perfusion lesion in acute ischemic stroke. We tested 10 of these to compare perfusion lesion sizes and to assess the relation to clinical scores and final infarct extent., Methods: We recruited patients with acute ischemic stroke, performed diffusion- and perfusion-weighted imaging, and recorded stroke severity at baseline, final infarct size on T2-weighted imaging at >or=1 month, and Rankin Scale score at 3 months. We calculated 10 perfusion parameters (6 of mean transit time, MTT; 3 of cerebral blood flow; 1 of cerebral blood volume; 7 relative and 3 quantitative), measured the perfusion-weighted imaging lesion and diffusion/perfusion mismatch volumes, and compared each with clinical and radiologic outcomes., Results: Among 32 patients, the median perfusion lesion volume varied from 0 to 14,882 voxels (P<0.0001); the proportion of patients with mismatch varied from 9% to 72% (P<0.05), depending on the perfusion parameter. Five measures of relative MTT were associated with baseline National Institutes of Health Stroke Scale score; 1 (arrival time fitted) was also associated with clinical outcome. Final infarct size was most strongly associated with MTT measures, including arrival time fitted. There was no advantage of quantitative perfusion measures and no relation between mismatch presence/absence and infarct expansion with any of the 10 perfusion measures., Conclusions: Perfusion lesion size differs markedly depending on the parameter calculated. Relative perfusion parameters performed as well as quantitative ones. Some parameters (mainly representing MTT measures) were correlated with clinical scores; others were correlated with final infarct size; and arrival time fitted was correlated with both. These findings should be validated in other datasets. A consensus is required on which perfusion measurement and processing methods should be used.

Background and Purpose: Some infarcts have persistently hyperintense areas on diffusion-weighted MRI (DWI) even at 1 month after stroke, whereas others have become isointense to normal brain. We hypothesized that late DWI hyperintensity reflected different infarct evolution compared with areas that were isointense by 1 month., Methods: We recruited patients prospectively with ischemic stroke, performed DWI and perfusion-weighted MRI (PWI) on admission, at 5 days, 14 days, and 1 month after stroke, and assessed functional outcome at 3 months (Rankin Scale). Patient characteristics and DWI/PWI values were compared for patients with or without "still hyperintense" infarct areas on 1-month DWI., Results: Among 42 patients, 27 (64%) had "still hyperintense" infarct regions at 1 month, mostly in white matter. Patients with "still hyperintense" regions at 1 month had lower baseline apparent diffusion coefficient ratio (ADCr; mean+/-SD 0.76+/-0.12 versus 0.85+/-0.12; hyperintense versus isointense; P<0.05), prolonged reduction of ADCr (repeated-measures ANOVA; P<0.01), no difference in baseline perfusion but delayed normalization of mean transit time (P<0.05) and cerebral blood flow ratios (repeated measures ANOVA; P<0.05), initially more severe stroke, and worse 3-month outcome than patients whose lesions were isointense by 1 month., Conclusions: The late DWI lesion hyperintensity emphasizes the heterogeneity in temporal evolution of stroke injury and suggests ongoing "ischemia." Lower baseline ADCr precedes delayed perfusion normalization, suggesting that worse cell swelling impedes reperfusion. Further study is required to determine underlying mechanisms and any potential for subacute intervention to improve recovery.

An analysis procedure is presented that enables the acquisition and visualization of physiologically relevant parameters using dynamic contrast-enhanced magnetic resonance imaging. The first stage of the process involves the use of a signal model that relates the measured magnetic resonance signal to the contrast agent concentration. Since the model requires knowledge of the longitudinal relaxation time T(1), a novel optimization scheme is presented which ensures a reliable measurement. Pharmacokinetic modelling of the observed contrast agent uptake is then performed to obtain physiological parameters relating to microvessel leakage permeability and volume fraction and the assumptions made in the derivation of these parameters are discussed. A simple colour representation is utilized that enables the relevant physiological information to be conveyed to the clinician in a visually efficient and meaningful manner. A second representation, based on vector maps, is also devised and it is demonstrated how this can be used for malignant tumour segmentation. Finally, the procedure is applied to 14 pre- and post-chemotherapy breast cases to demonstrate the clinical value of the technique. In particular, the apparent improved representation of tissue vascularity when compared to conventional methods and the implications for this in treatment assessment are discussed.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to examine the distribution of an intravenous contrast agent within the brain. Computational methods have been devised to analyse the contrast uptake/washout over time as reflections of cerebrovascular dysfunction. However, there have been few direct comparisons of their relative strengths and weaknesses. In this paper, we compare five semiquantitative methods comprising the slope and area under the enhancement-time curve, the slope and area under the concentration-time curve (SlopeCon and AUCCon), and changes in the power spectrum over time. We studied them in cerebrospinal fluid, normal tissues, stroke lesions, and white matter hyperintensities (WMH) using DCE-MRI scans from a cohort of patients with small vessel disease (SVD) who presented mild stroke. The total SVD score was associated with AUCCon in WMH (p < 0.05), but not with the other four methods. In WMH, we found higher AUCCon was associated with younger age (p < 0.001) and fewer WMH (p < 0.001), whereas SlopeCon increased with younger age (p > 0.05) and WMH burden (p > 0.05). Our results show the potential of different measures extracted from concentration-time curves extracted from the same DCE examination to demonstrate cerebrovascular dysfunction better than those extracted from enhancement-time curves. [ABSTRACT FROM AUTHOR]

Infantile neuroaxonal dystrophy (INAD) is a rare autosomal recessive disorder that is associated with developmental delay and regression. A female patient of consanguineous parents presented with gross motor delay at 15 months. She was known to have two paternal uncles who had died with a diagnosis of INAD. Over the next 15 months, she exhibited regression in several domains and following genetic testing was diagnosed with a PLA2G6 mutation in keeping with INAD. The cerebellar vermis demonstrated a significant reduction in the N -acetylaspartate/creatinine (NAA/Cr) ratio of 0.69. This case highlights what we believe to be a new imaging feature of a low NAA/Cr ratio in the cerebellar vermis with normal ratios in the cerebellar hemispheres and basal ganglia in a patient with genetically confirmed diagnosis of INAD. [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]

Purpose: This paper presents a statistical approach for the prediction of trabecular bone parameters from low-resolution multisequence magnetic resonance imaging (MRI) in children, thus addressing the limitations of high-resolution modalities such as HR-pQCT, including the significant exposure of young patients to radiation and the limited applicability of such modalities to peripheral bones in vivo. Methods: A statistical predictive model is constructed from a database of MRI and HR-pQCT datasets, to relate the low-resolution MRI appearance in the cancellous bone to the trabecular parameters extracted from the high-resolution images. The description of the MRI appearance is achieved between subjects by using a collection of feature descriptors, which describe the texture properties inside the cancellous bone, and which are invariant to the geometry and size of the trabecular areas. The predictive model is built by fitting to the training data a nonlinear partial least square regression between the input MRI features and the output trabecular parameters. Results: Detailed validation based on a sample of 96 datasets shows correlations >0.7 between the trabecular parameters predicted from low-resolution multisequence MRI based on the proposed statistical model and the values extracted from high-resolution HRp-QCT. Conclusions: The obtained results indicate the promise of the proposed predictive technique for the estimation of trabecular parameters in children from multisequence MRI, thus reducing the need for high-resolution radiation-based scans for a fragile population that is under development and growth. [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]

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]

Increasing use is being made of Gd-DTPA contrast-enhanced magnetic resonance imaging for breast cancer assessment since it provides 3D functional information via pharmacokinetic interaction between contrast agent and tumour vascularity, and because it is applicable to women of all ages as well as patients with post-operative scarring. Contrast-enhanced MRI (CE-MRI) is complementary to conventional X-ray mammography, since it is a relatively low-resolution functional counterpart of a comparatively high-resolution 2D structural representation. However, despite the additional information provided by MRI, mammography is still an extremely important diagnostic imaging modality, particularly for several common conditions such as ductal carcinoma in situ (DCIS) where it has been shown that there is a strong correlation between microcalcification clusters and malignancy. Pathological indicators such as calcifications and fine spiculations are not visible in CE-MRI and therefore there is clinical and diagnostic value in fusing the high-resolution structural information available from mammography with the functional data acquired from MRI imaging. This paper presents a novel data fusion technique whereby medial–lateral oblique (MLO) and cranial–caudal (CC) mammograms (2D data) are registered to 3D contrast-enhanced MRI volumes. We utilise a combination of pharmacokinetic modelling, projection geometry, wavelet-based landmark detection and thin-plate spline non-rigid ‘warping’ to transform the coordinates of regions of interest (ROIs) from the 2D mammograms to the spatial reference frame of the contrast-enhanced MRI volume. Of key importance is the use of a flexible wavelet-based feature extraction technique that enables feature correspondences to be robustly determined between the very different image characteristics of X-ray mammography and MRI. An evaluation of the fusion framework is demonstrated with a series of clinical cases and a total of 14 patient examples. [Copyright &y& Elsevier]