Dynamic contrast-enhanced MRI and CT provide comparable measurement of blood-brain barrier permeability in a rodent stroke model

Gingipains may be one of the key virulence factors of Porphyromonas gingivalis to impair cognition and enhance blood-brain barrier permeability: An animal study

AIM

Blood-brain barrier (BBB) disorder is one of the early findings in cognitive impairments. We have recently found that Porphyromonas gingivalis bacteraemia can cause cognitive impairment and increased BBB permeability. This study aimed to find out the possible key virulence factors of P. gingivalis contributing to the pathological process.

MATERIALS AND METHODS

C57/BL6 mice were infected with P. gingivalis or gingipains or P. gingivalis lipopolysaccharide (P. gingivalis LPS group) by tail vein injection for 8 weeks. The cognitive behaviour changes in mice, the histopathological changes in the hippocampus and cerebral cortex, the alternations of BBB permeability, and the changes in Mfsd2a and Cav-1 levels were measured. The mechanisms of Ddx3x-induced regulation on Mfsd2a by arginine-specific gingipain A (RgpA) in BMECs were explored.

RESULTS

P. gingivalis and gingipains significantly promoted mice cognitive impairment, pathological changes in the hippocampus and cerebral cortex, increased BBB permeability, inhibited Mfsd2a expression and up-regulated Cav-1 expression. After RgpA stimulation, the permeability of the BBB model in vitro increased, and the Ddx3x/Mfsd2a/Cav-1 regulatory axis was activated.

CONCLUSIONS

Gingipains may be one of the key virulence factors of P. gingivalis to impair cognition and enhance BBB permeability by the Ddx3x/Mfsd2a/Cav-1 axis.

Multi-Scale Imaging of Vascular Pathologies in Cardiovascular Disease

Cardiovascular disease entails systemic changes in the vasculature. The endothelial cells lining the blood vessels are crucial in the pathogenesis of cardiovascular disease. Healthy endothelial cells direct the blood flow to tissues as vasodilators and act as the systemic interface between the blood and tissues, supplying nutrients for vital organs, and regulating the smooth traffic of leukocytes into tissues. In cardiovascular diseases, when inflammation is sensed, endothelial cells adjust to the local or systemic inflammatory state. As the inflamed vasculature adjusts, changes in the endothelial cells lead to endothelial dysfunction, altered blood flow and permeability, expression of adhesion molecules, vessel wall inflammation, thrombosis, angiogenic processes, and extracellular matrix production at the endothelial cell level. Preclinical multi-scale imaging of these endothelial changes using optical, acoustic, nuclear, MRI, and multimodal techniques has progressed, due to technical advances and enhanced biological understanding on the interaction between immune and endothelial cells. While this review highlights biological processes that are related to changes in the cardiac vasculature during cardiovascular diseases, it also summarizes state-of-the-art vascular imaging techniques. The advantages and disadvantages of the different imaging techniques are highlighted, as well as their principles, methodologies, and preclinical and clinical applications with potential future directions. These multi-scale approaches of vascular imaging carry great potential to further expand our understanding of basic vascular biology, to enable early diagnosis of vascular changes and to provide sensitive diagnostic imaging techniques in the management of cardiovascular disease.

Imaging Acute Stroke: From One-Size-Fit-All to Biomarkers

In acute stroke management, time window has been rigidly used as a guide for decades and the reperfusion treatment is only available in the first few limited hours. Recently, imaging-based selection of patients has successfully expanded the treatment window out to 16 and even 24 h in the DEFUSE 3 and DAWN trials, respectively. Recent guidelines recommend the use of imaging techniques to guide therapeutic decision-making and expanded eligibility in acute ischemic stroke. A tissue window is proposed to replace the time window and serve as the surrogate marker for potentially salvageable tissue. This article reviews the evolution of time window, addresses the advantage of a tissue window in precision medicine for ischemic stroke, and discusses both the established and emerging techniques of neuroimaging and their roles in defining a tissue window. We also emphasize the metabolic imaging and molecular imaging of brain pathophysiology, and highlight its potential in patient selection and treatment response prediction in ischemic stroke.

Methods used for the measurement of blood-brain barrier integrity

The blood-brain barrier (BBB) comprises the interface between blood, brain and cerebrospinal fluid. Its primary function, which is mainly carried out by tight junctions, is to stabilize the tightly controlled microenvironment of the brain. To study the development and maintenance of the BBB, as well as various roles their intrinsic mechanisms that play in neurological disorders, suitable measurements are required to demonstrate integrity and functional changes at the interfaces between the blood and brain tissue. Markers and plasma proteins with different molecular weight (MW) are used to measure the permeability of BBB. In addition, the expression changes of tight-junction proteins form the basic structure of BBB, and imaging modalities are available to study the disruption of BBB. In the present review, above mentioned methods are depicted in details, together with the pros and cons as well as the differences between these methods, which maybe benefit research studies focused on the detection of BBB breakdown.

Not Just a Bystander: The Emerging Role of Astrocytes and Research Tools in Studying Cognitive Dysfunctions in Schizophrenia

Cognitive dysfunction is one of the core symptoms in schizophrenia, and it is predictive of functional outcomes and therefore useful for treatment targets. Rather than improving cognitive deficits, currently available antipsychotics mainly focus on positive symptoms, targeting dopaminergic/serotoninergic neurons and receptors in the brain. Apart from investigating the neural mechanisms underlying schizophrenia, emerging evidence indicates the importance of glial cells in brain structure development and their involvement in cognitive functions. Although the etiopathology of astrocytes in schizophrenia remains unclear, accumulated evidence reveals that alterations in gene expression and astrocyte products have been reported in schizophrenic patients. To further investigate the role of astrocytes in schizophrenia, we highlighted recent progress in the investigation of the effect of astrocytes on abnormalities in glutamate transmission and impairments in the blood–brain barrier. Recent advances in animal models and behavioral methods were introduced to examine schizophrenia-related cognitive deficits and negative symptoms. We also highlighted several experimental tools that further elucidate the role of astrocytes. Instead of focusing on schizophrenia as a neuron-specific disorder, an additional astrocytic perspective provides novel and promising insight into its causal mechanisms and treatment. The involvement of astrocytes in the pathogenesis of schizophrenia and other brain disorders is worth further investigation.

Automated Assessment of Hematoma Volume of Rodents Subjected to Experimental Intracerebral Hemorrhagic Stroke by Bayes Segmentation Approach

Simulating a clinical condition of intracerebral hemorrhage (ICH) in animals is key to research on the development and testing of diagnostic or treatment strategies for this high-mortality disease. In order to study the mechanism, pathology, and treatment for hemorrhagic stroke, various animal models have been developed. Measurement of hematoma volume is an important assessment parameter to evaluate post-ICH outcomes. However, due to tissue preservation conditions and variables in digitization, quantification of hematoma volume is usually labor intensive and sometimes even subjective. The objective of this study is to develop an automated method that can accurately and efficiently obtain unbiased cerebral hematoma volume. We developed an application (MATLAB program) that can delineate the brain slice from the background and use the Hue information in the Hue/Saturation/Value (HSV) color space to segment the hematoma region. The segmentation threshold of Hue is calculated based on the Bayes classifier theorem so that the minimum error is mathematically ensured and automated processing is enabled. To validate the developed method, we compared the outcomes from the developed method with the hemoglobin content by the spectrophotometric assay method. The results were linearly correlated with statistical significance. The method was also validated by digital phantoms with an error less than 5% compared with the ground truth from the phantoms. Hematoma volumes yielded by the automated processing and those obtained by the operator's manual operation are highly correlated. This automated segmentation approach can be potentially used to quantify hemorrhagic outcomes in rodent stroke models in an unbiased and efficient way.

Imaging the aged brain: pertinence and methods

The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.

Unified platform for multimodal voxel-based analysis to evaluate tumour perfusion and diffusion characteristics before and after radiation treatment evaluated in metastatic brain cancer

OBJECTIVE:

Early changes in tumour behaviour following stereotactic radiosurgery) are potential biomarkers of response. To-date quantitative model-based measures of dynamic contrast-enhanced (DCE) and diffusion-weighted (DW) MRI parameters have shown widely variable findings, which may be attributable to variability in image acquisition, post-processing and analysis. Big data analytic approaches are needed for the automation of computationally intensive modelling calculations for every voxel, independent of observer interpretation.

METHODS:

This unified platform is a voxel-based, multimodality architecture that brings complimentary solute transport processes such as perfusion and diffusion into a common framework. The methodology was tested on synthetic data and digital reference objects and consequently evaluated in patients who underwent volumetric DCE-CT, DCE-MRI and DWI-MRI scans before and after treatment. Three-dimensional pharmacokinetic parameter maps from both modalities were compared as well as the correlation between apparent diffusion coefficient (ADC) values and the extravascular, extracellular volume (V_e). Comparison of histogram parameters was done via Bland-Altman analysis, as well as Student's t-test and Pearson's correlation using two-sided analysis.

RESULTS:

System testing on synthetic Tofts model data and digital reference objects recovered the ground truth parameters with mean relative percent error of 1.07 × 10^-7 and 5.60 × 10^-4 respectively. Direct voxel-to-voxel Pearson's analysis showed statistically significant correlations between CT and MR which peaked at Day 7 for K_trans (R = 0.74, p <= 0.0001). Statistically significant correlations were also present between ADC and Ve derived from both DCE-MRI and DCE-CT with highest median correlations found at Day 3 between median ADC and Ve,_MRI values (R = 0.6, p < 0.01) The strongest correlation to DCE-CT measurements was found with DCE-MRI analysis using voxelwise T₁₀ maps (R = 0.575, p < 0.001) instead of assigning a fixed T₁₀ value.

CONCLUSION:

The unified implementation of multiparametric transport modelling allowed for more robust and timely observer-independent data analytics. Utility of a common analysis platform has shown higher correlations between pharmacokinetic parameters obtained from different modalities than has previously been reported.

ADVANCES IN KNOWLEDGE:

Utility of a common analysis platform has shown statistically higher correlations between pharmacokinetic parameters obtained from different modalities than has previously been reported.

Brain Vascular Imaging Techniques

Recent major improvements in a number of imaging techniques now allow for the study of the brain in ways that could not be considered previously. Researchers today have well-developed tools to specifically examine the dynamic nature of the blood vessels in the brain during development and adulthood; as well as to observe the vascular responses in disease situations in vivo. This review offers a concise summary and brief historical reference of different imaging techniques and how these tools can be applied to study the brain vasculature and the blood-brain barrier integrity in both healthy and disease states. Moreover, it offers an overview on available transgenic animal models to study vascular biology and a description of useful online brain atlases.

Comparison of Voxel-Wise Tumor Perfusion Changes Measured With Dynamic Contrast-Enhanced (DCE) MRI and Volumetric DCE CT in Patients With Metastatic Brain Cancer Treated with Radiosurgery

Dynamic contrast-enhanced (DCE)-MRI metrics are evaluated against volumetric DCE-CT quantitative parameters as a standard for tracer-kinetic validation using a common 4-dimensional temporal dynamic analysis platform in tumor perfusion measurements following stereotactic radiosurgery (SRS) for brain metastases. Patients treated with SRS as part of Research Ethics Board-approved clinical trials underwent volumetric DCE-CT and DCE-MRI at baseline, then at 7 and 21 days after SRS. Temporal dynamic analysis was used to create 3-dimensional pharmacokinetic parameter maps for both modalities. Individual vascular input functions were selected for DCE-CT and a population function was used for DCE-MRI. Semiquantitative and pharmacokinetic DCE parameters were assessed using a modified Tofts model within each tumor at every time point for both modalities for characterization of perfusion and capillary permeability, as well as their dependency on precontrast relaxation times (TRs), T₁₀, and input function. Direct voxel-to-voxel Pearson analysis showed statistically significant correlations between CT and magnetic resonance which peaked at day 7 for K_trans (R = 0.74, P ≤ .0001). The strongest correlation to DCE-CT measurements was found with DCE-MRI analysis using voxel-wise T₁₀ maps (R = 0.575, P < .001) instead of assigning a fixed T₁₀ value. Comparison of histogram features showed statistically significant correlations between modalities over all tumors for median K_trans (R = 0.42, P = .01), median area under the enhancement curve (iAUC₉₀) (R = 0.55, P < .01), and median iAUC₉₀ skewness (R = 0.34, P = .03). Statistically significant, strong correlations were found for voxel-wise K_trans, iAUC₉₀, and v_e values between DCE-CT and DCE-MRI. For DCE-MRI, the implementation of voxel-wise T₁₀ maps plays a key role in ensuring the accuracy of heterogeneous pharmacokinetic maps.