To investigate the link between blood-brain-barrier (BBB) permeability and cerebral blood flow (CBF) and the relation with white matter hyperintensities (WMH) in cerebral small vessel disease (cSVD).
...Twenty-seven patients with cSVD received dynamic susceptibility contrast and dynamic contrast-enhanced MRI to determine CBF and BBB permeability (expressed as leakage rate and volume), respectively. Structural MRI were segmented into normal-appearing white matter (NAWM) and WMH, for which a perilesional zone was defined. In these regions, we investigated the BBB permeability, CBF, and their relation using Pearson correlation
.
We found a decrease in CBF of 2.2 mL/min/100 g (
< 0.01) and an increase in leakage volume of 0.7% (
< 0.01) per mm closer to the WMH in the perilesional zones. Lower CBF values correlated with higher leakage measures in the NAWM and WMH (-0.53 <
< -0.40,
< 0.05). This relation was also observed in the perilesional zones, which became stronger in the proximity of WMH (
= 0.03).
BBB impairment and hypoperfusion appear in the WMH and NAWM, which increase in the proximity of the WMH, and are linked. Both BBB and CBF are regulated in the neurovascular unit (NVU) and the observed link might be due to the physiologic regulation mechanism of the NVU. This link may suggest an early overall deterioration of this unit.
Cerebral small vessel disease (cSVD) comprises pathological processes of the small vessels in the brain that may manifest clinically as stroke, cognitive impairment, dementia, or gait disturbance. It ...is generally accepted that endothelial dysfunction, including blood-brain barrier (BBB) failure, is pivotal in the pathophysiology. Recent years have seen increasing use of imaging, primarily dynamic contrast-enhanced magnetic resonance imaging, to assess BBB leakage, but there is considerable variability in the approaches and findings reported in the literature. Although dynamic contrast-enhanced magnetic resonance imaging is well established, challenges emerge in cSVD because of the subtle nature of BBB impairment. The purpose of this work, authored by members of the HARNESS Initiative, is to provide an in-depth review and position statement on magnetic resonance imaging measurement of subtle BBB leakage in clinical research studies, with aspects requiring further research identified. We further aim to provide information and consensus recommendations for new investigators wishing to study BBB failure in cSVD and dementia.
Abstract The emphasis in contemporary medical oncology has been “precision” or “personalized” medicine, terms that imply a strategy to improve efficacy through targeted therapies. Similar attempts at ...precision are occurring in surgical oncology. Sentinel lymph node (SLN) mapping has recently been introduced into the surgical staging of endometrial cancer with the goal to reduce morbidity associated with comprehensive lymphadenectomy, yet obtain prognostic information from lymph node status. The Society of Gynecologic Oncology's (SGO) Clinical Practice Committee and SLN Working Group reviewed the current literature for preparation of this document. Literature-based recommendations for the inclusion of SLN assessment in the treatment of patients with endometrial cancer are presented. This article examines: • History and various techniques of SLN mapping in endometrial cancer • Pathology and clinical outcomes from SLN assessment • Controversies and future directions for research in SLN assessment in endometrial cancer.
Background and Purpose- Cerebral amyloid angiopathy (CAA) is a common small vessel disease that independently effects cognition in older individuals. The pathophysiology of CAA and CAA-related ...bleeding remains poorly understood. In this postmortem study, we explored whether blood-brain barrier leakage is associated with CAA and microvascular lesions. Methods- Eleven CAA cases (median IQR age=69 years 65-79 years, 8 males) and 7 cases without neurological disease or brain lesions (median IQR age=77 years 68-92 years, 4 males) were analyzed. Cortical sections were sampled from each lobe, and IgG and fibrin extravasation (markers of blood-brain barrier leakage) were assessed with immunohistochemistry. We hypothesized that IgG and fibrin extravasation would be increased in CAA cases compared with controls, that this would be more pronounced in parietooccipital brain regions compared with frontotemporal brain regions in parallel with the posterior predilection of CAA, and would be associated with CAA severity and number of cerebral microbleeds and cerebral microinfarcts counted on ex vivo magnetic resonance imaging of the intact brain hemisphere. Results- Our results demonstrated increased IgG positivity in the frontotemporal ( P=0.044) and parietooccipital ( P=0.001) cortex in CAA cases compared with controls. Within CAA cases, both fibrin and IgG positivity were increased in parietooccipital brain regions compared with frontotemporal brain regions ( P=0.005 and P=0.006, respectively). The percentage of positive vessels for fibrin and IgG was associated with the percentage of amyloid-β-positive vessels (Spearman ρ=0.71, P=0.015 and Spearman ρ=0.73, P=0.011, respectively). Moreover, the percentage of fibrin and IgG-positive vessels, but not amyloid-β-positive vessels, was associated with the number of cerebral microbleeds on magnetic resonance imaging (Spearman ρ=0.77, P=0.005 and Spearman ρ=0.70, P=0.017, respectively). Finally, we observed fibrin deposition in walls of vessels involved in cerebral microbleeds. Conclusions- Our results raise the possibility that blood-brain barrier leakage may be a contributory mechanism for CAA-related brain injury.
Blood-brain barrier (BBB) leakage is considered an important underlying process in both cerebral small vessel disease (cSVD) and Alzheimer's disease (AD). The objective of this study was to examine ...associations between BBB leakage, cSVD, neurodegeneration, and cognitive performance across the spectrum from normal cognition to dementia. Leakage was measured with dynamic contrast-enhanced magnetic resonance imaging in 80 older participants (normal cognition, n = 32; mild cognitive impairment, n = 34; clinical AD-type dementia, n = 14). Associations between leakage and white matter hyperintensity (WMH) volume, hippocampal volume, and cognition (information processing speed and memory performance) were examined with multivariable linear regression and mediation analyses. Leakage within the gray and white matter was positively associated with WMH volume (gray matter, p = 0.03; white matter, p = 0.01). A negative association was found between white matter BBB leakage and information processing speed performance, which was mediated by WMH volume. Leakage was not associated with hippocampal volume. WMH pathology is suggested to form a link between leakage and decline of information processing speed in older individuals with and without cognitive impairment.
•BBB leakage throughout the whole brain is positively related to cSVD severity.•BBB leakage forms an indirect process underlying processing speed deterioration.•This process is independent of clinical diagnosis.
Purpose To investigate whether the blood-brain barrier (BBB) leaks blood-circulating substances in patients with early forms of Alzheimer disease (AD), and if so, to examine the extent and pattern of ...leakage. Materials and Methods This study was approved by the local medical ethical committees of the Maastricht University Medical Center and Leiden University Medical Center, and written informed consent was obtained from all subjects. For this pilot study, 16 patients with early AD and 17 healthy age-matched control subjects underwent dynamic contrast material-enhanced magnetic resonance (MR) imaging sequence with dual time resolution for 25 minutes. The Patlak graphical approach was used to quantify the BBB leakage rate and local blood plasma volume. Subsequent histogram analysis was used to determine the volume fraction of the leaking brain tissue. Differences were assessed with linear regression analysis, adjusted for confounding variables. Results The BBB leakage rate was significantly higher in patients compared with that in control subjects in the total gray matter (P < .05) and cortex (P = .03). Patients had a significantly higher volume fraction of the leaking brain tissue in the gray matter (P = .004), normal-appearing white matter (P < .04), deep gray matter (P = .01), and cortex (P = .004). When all subjects were considered, scores on the Mini-Mental State Examination decreased significantly with increasing leakage in the deep gray matter (P = .007) and cortex (P < .05). Conclusion The results of this study showed global BBB leakage in patients with early AD that is associated with cognitive decline. A compromised BBB may be part of a cascade of pathologic events that eventually lead to cognitive decline and dementia.
RSNA, 2016 Online supplemental material is available for this article.
•ME-ICA and ICA-AROMA provide effective denoising for multi-echo 7T fMRI data.•High tSNR can be achieved in the brainstem with a multi-echo acquisition at 7T.•After ME-ICA, the data is best ...post-processed to correct for spatially diffuse noise.•ICA-AROMA-aggr might be too aggressive in denoising the multi-echo 7T fMRI data.
In functional magnetic resonance imaging (fMRI) of the brain the measured signal is corrupted by several (e.g. physiological, motion, and thermal) noise sources and depends on the image acquisition. Imaging at ultrahigh field strength is becoming increasingly popular as it offers increased spatial accuracy. The latter is of particular benefit in brainstem neuroimaging given the small cross-sectional area of most nuclei. However, physiological noise scales with field strength in fMRI acquisitions. Although this problem is in part solved by decreasing voxel size, it is clear that adequate physiological denoising is of utmost importance in brainstem-focused fMRI experiments. Multi-echo sequences have been reported to facilitate highly effective denoising through TE-dependence of Blood Oxygen Level Dependent (BOLD) signals, in a denoising method referred to as multi-echo independent component analysis (ME-ICA). It has not been explored previously how ME-ICA compares to other data-driven denoising approaches at ultrahigh field strength. In the current study, we compared the efficacy of several denoising methods, including anatomical component based correction (aCompCor), Automatic Removal of Motion Artifacts (ICA-AROMA) aggressive and non-aggressive options, ME-ICA, and a combination of ME-ICA and aCompCor. We assessed several data quality metrics, including temporal signal-to-noise ratio (tSNR), delta variation signal (DVARS), spectral density of the global signal, functional connectivity and Shannon spectral entropy. Moreover, we looked at the ability of each method to uncouple the global signal and respiration. In line with previous reports at lower field strengths, we demonstrate that after applying ME-ICA, the data is best post-processed in order to remove spatially diffuse noise with a method such as aCompCor. Our findings indicate that ME-ICA combined with aCompCor and the aggressive option of ICA-AROMA are highly effective denoising approaches for multi-echo data acquired at 7T. ME-ICA combined with aCompCor potentially preserves more signal-of-interest as compared to the aggressive option of ICA-AROMA.
In childhood frontal lobe epilepsy (FLE), cognitive impairment and educational underachievement are serious, well-known co-morbidities. The broad scale of affected cognitive domains suggests ...wide-spread network disturbances that not only involves, but also extends beyond the frontal lobe. In this study we have investigated whole brain connectional properties of children with FLE in relation to their cognitive impairment and compared them with healthy controls. Functional connectivity (FC) of the networks was derived from dynamic fluctuations of resting state fMRI and structural connectivity (SC) was obtained from fiber tractograms of diffusion weighted MRI. The whole brain network was characterized with graph theoretical metrics and decomposed into modules. Subsequently, the graph metrics and the connectivity within and between modules were related to cognitive performance. Functional network disturbances in FLE were related to increased clustering, increased path length, and stronger modularity compared to healthy controls, which was accompanied by stronger within- and weaker between-module functional connectivity. Although structural path length and clustering appeared normal in children with FLE, structural modularity increased with stronger cognitive impairment. It is concluded that decreased coupling between large-scale functional network modules is a hallmark for impaired cognition in childhood FLE.
Quality control of brain segmentation is a fundamental step to ensure data quality. Manual quality control strategies are the current gold standard, although these may be unfeasible for large ...neuroimaging samples. Several options for automated quality control have been proposed, providing potential time efficient and reproducible alternatives. However, those have never been compared side to side, which prevents consensus in the appropriate quality control strategy to use. This study aimed to elucidate the changes manual editing of brain segmentations produce in morphological estimates, and to analyze and compare the effects of different quality control strategies on the reduction of the measurement error.
Structural brain MRI from 259 participants of The Maastricht Study were used. Morphological estimates were automatically extracted using FreeSurfer 6.0. Segmentations with inaccuracies were manually edited, and morphological estimates were compared before and after editing. In parallel, 12 quality control strategies were applied to the full sample. Those included: two manual strategies, in which images were visually inspected and either excluded or manually edited; five automated strategies, where outliers were excluded based on the tools “MRIQC” and “Qoala-T”, and the metrics “morphological global measures”, “Euler numbers” and “Contrast-to-Noise ratio”; and five semi-automated strategies, where the outliers detected through the mentioned tools and metrics were not excluded, but visually inspected and manually edited. In order to quantify the effects of each quality control strategy, the proportion of unexplained variance relative to the total variance was extracted after the application of each strategy, and the resulting differences compared.
Manually editing brain surfaces produced particularly large changes in subcortical brain volumes and moderate changes in cortical surface area, thickness and hippocampal volumes. The performance of the quality control strategies depended on the morphological measure of interest. Overall, manual quality control strategies yielded the largest reduction in relative unexplained variance. The best performing automated alternatives were those based on Euler numbers and MRIQC scores. The exclusion of outliers based on global morphological measures produced an increase of relative unexplained variance.
Manual quality control strategies are the most reliable solution for quality control of brain segmentation and parcellation. However, measures must be taken to prevent the subjectivity associated with these strategies. The detection of inaccurate segmentations based on Euler numbers or MRIQC provides a time efficient and reproducible alternative. The exclusion of outliers based on global morphological estimates must be avoided.
Myelin is vital for healthy neuronal development, and can therefore provide valuable information regarding neuronal maturation. Anatomical and diffusion weighted images (DWI) possess information ...related to the myelin content and the current study investigates whether quantitative myelin markers can be extracted from anatomical and DWI using neural networks.
Thirteen volunteers (mean age 29y) are included, and for each subject, a residual neural network was trained using spatially undersampled reference myelin-water markers. The network is trained on a voxel-by-voxel basis, resulting in a large amount of training data for each volunteer. The inputs used are the anatomical contrasts (cT1w, cT2w), the standardized T1w/T2w ratio, estimates of the relaxation times (T1, T2) and their ratio (T1/T2), and common DWI metrics (FA, RD, MD, λ1, λ2, λ3). Furthermore, to estimate the added value of the DWI metrics, neural networks were trained using either the combined set (DWI, T1w and T2w) or only the anatomical (T1w and T2w) images.
The reconstructed myelin-water maps are in good agreement with the reference myelin-water content in terms of the coefficient of variation (CoV) and the intraclass correlation coefficient (ICC). A 6-fold undersampling using both anatomical and DWI metrics resulted in ICC = 0.68 and CoV = 5.9%. Moreover, using twice the training data (3-fold undersampling) resulted in an ICC that is comparable to the reproducibility of the myelin-water imaging itself (CoV = 5.5% vs. CoV = 6.7% and ICC = 0.74 vs ICC = 0.80). To achieve this, beside the T1w, T2w images, DWI is required.
This preliminary study shows the potential of machine learning approaches to extract specific myelin-content from anatomical and diffusion-weighted scans.
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