Enhancement of Perivascular Spaces in 7 T MR Image using Haar Transform of Non-local Cubes and Block-matching Filtering.
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ABSTRACT:
SUBMITTER: Hou Y
PROVIDER: S-EPMC5561084 | biostudies-other | 2017 Aug
REPOSITORIES: biostudies-other
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Project description:Perivascular Spaces (PVS) are a feature of Small Vessel Disease (SVD), and are an important part of the brain's circulation and glymphatic drainage system. Quantitative analysis of PVS on Magnetic Resonance Images (MRI) is important for understanding their relationship with neurological diseases. In this work, we propose a segmentation technique based on the 3D Frangi filtering for extraction of PVS from MRI. We used ordered logit models and visual rating scales as alternative ground truth for Frangi filter parameter optimization and evaluation. We optimized and validated our proposed models on two independent cohorts, a dementia sample (N?=?20) and patients who previously had mild to moderate stroke (N?=?48). Results demonstrate the robustness and generalisability of our segmentation method. Segmentation-based PVS burden estimates correlated well with neuroradiological assessments (Spearman's ??=?0.74, p?<?0.001), supporting the potential of our proposed method.
| S-EPMC5794857 | biostudies-literature
Project description:Purpose To describe a fully automated segmentation method that yields object-based morphologic estimates of enlarged perivascular spaces (ePVSs) in clinical-field-strength (3.0-T) magnetic resonance (MR) imaging data. Materials and Methods In this HIPAA-compliant study, MR imaging data were obtained with a 3.0-T MR imager in research participants without dementia (mean age, 85.3 years; range, 70.4-101.2 years) who had given written informed consent. This method is built on (a) relative normalized white matter, ventricular and cortical signal intensities within T1-weighted, fluid-attenuated inversion recovery, T2-weighted, and proton density data and (b) morphologic (width, volume, linearity) characterization of each resultant cluster. Visual rating was performed by three raters, including one neuroradiologist, after established single-section guidelines. Correlations between visual counts and automated counts, as well session-to-session correlation of counts within each participant, were assessed with the Pearson correlation coefficient r. Results There was a significant correlation between counts by visual raters and automated detection of ePVSs in the same section (r = 0.65, P < .001; r = 0.69, P < .001; and r = 0.54, P < .01 for raters 1, 2, and 3, respectively). With regard to visual ratings and whole-brain count consistency, average visual rating scores were highly correlated with automated detection of total burden volume (r = 0.58, P < .01) and total ePVS number (r = 0.76, P < .01). Morphology of clusters across 28 data sets was consistent with published radiographic estimates of ePVS; mean width of clusters segmented was 3.12 mm (range, 1.7-13.5 mm). Conclusion This MR imaging-based method for multimodal autoidentification of perivascular spaces yields individual whole-brain morphologic characterization of ePVS in clinical MR imaging data and is an important tool in the detailed assessment of these features. © RSNA, 2017 Online supplemental material is available for this article.
| S-EPMC5790307 | biostudies-literature
Project description:Accurate segmentation of perivascular spaces (PVSs) is an important step for quantitative study of PVS morphology. However, since PVSs are the thin tubular structures with relatively low contrast and also the number of PVSs is often large, it is challenging and time-consuming for manual delineation of PVSs. Although several automatic/semi-automatic methods, especially the traditional learning-based approaches, have been proposed for segmentation of 3D PVSs, their performance often depends on the hand-crafted image features, as well as sophisticated preprocessing operations prior to segmentation (e.g., specially defined regions-of-interest (ROIs)). In this paper, a novel fully convolutional neural network (FCN) with no requirement of any specified hand-crafted features and ROIs is proposed for efficient segmentation of PVSs. Particularly, the original T2-weighted 7T magnetic resonance (MR) images are first filtered via a non-local Haar-transform-based line singularity representation method to enhance the thin tubular structures. Both the original and enhanced MR images are used as multi-channel inputs to complementarily provide detailed image information and enhanced tubular structural information for the localization of PVSs. Multi-scale features are then automatically learned to characterize the spatial associations between PVSs and adjacent brain tissues. Finally, the produced PVS probability maps are recursively loaded into the network as an additional channel of inputs to provide the auxiliary contextual information for further refining the segmentation results. The proposed multi-channel multi-scale FCN has been evaluated on the 7T brain MR images scanned from 20 subjects. The experimental results show its superior performance compared with several state-of-the-art methods.
| S-EPMC6430123 | biostudies-literature
Project description:Background and purposePerivascular spaces play a role in cerebral waste removal and neuroinflammation. Our aim was to provide data regarding the burden of MR imaging-visible perivascular spaces in white matter in healthy adolescents using an automated segmentation method and to establish relationships between common demographic characteristics and perivascular space burden.Materials and methodsOne hundred eighteen 12- to 21-year-old subjects underwent T1- and T2-weighted 3T MR imaging as part of the National Consortium on Alcohol and Neurodevelopment in Adolescence. Perivascular spaces were identified in WM on T2-weighted imaging using a local heterogeneity approach coupled with morphologic constraints, and their spatial distribution and geometric characteristics were assessed.ResultsMR imaging-visible perivascular spaces were identified in all subjects (range, 16-287). Males had a significantly higher number of perivascular spaces than females: males, mean, 98.4 ± 50.5, versus females, 70.7 ± 36.1, (P < .01). Perivascular space burden was bilaterally symmetric (r > 0.4, P < .01), and perivascular spaces were more common in the frontal and parietal lobes than in the temporal and occipital lobes (P < .01). Age and pubertal status were not significantly associated with perivascular space burden.ConclusionsDespite a wide range of burden, perivascular spaces are present in all healthy adolescents. Perivascular space burden is higher in adolescent males than in females, regardless of age and pubertal status. In this population, perivascular spaces are highly symmetric. Although widely reported as a feature of the aging brain, awareness of the presence of perivascular spaces in a cohort of healthy adolescents provides the foundation for further research regarding the role of these structural variants in health and disease.
| S-EPMC7658833 | biostudies-literature
Project description:Neural activity leads to hemodynamic changes which can be detected by functional magnetic resonance imaging (fMRI). The determination of blood flow changes in individual vessels is an important aspect of understanding these hemodynamic signals. Blood flow can be calculated from the measurements of vessel diameter and blood velocity. When using line-scan imaging, the movement of blood in the vessel leads to streaks in space-time images, where streak angle is a function of the blood velocity. A variety of methods have been proposed to determine blood velocity from such space-time image sequences. Of these, the Radon transform is relatively easy to implement and has fast data processing. However, the precision of the velocity measurements is dependent on the number of Radon transforms performed, which creates a trade-off between the processing speed and measurement precision. In addition, factors like image contrast, imaging depth, image acquisition speed, and movement artifacts especially in large mammals, can potentially lead to data acquisition that results in erroneous velocity measurements. Here we show that pre-processing the data with a Sobel filter and iterative application of Radon transforms address these issues and provide more accurate blood velocity measurements. Improved signal quality of the image as a result of Sobel filtering increases the accuracy and the iterative Radon transform offers both increased precision and an order of magnitude faster implementation of velocity measurements. This algorithm does not use a priori knowledge of angle information and therefore is sensitive to sudden changes in blood flow. It can be applied on any set of space-time images with red blood cell (RBC) streaks, commonly acquired through line-scan imaging or reconstructed from full-frame, time-lapse images of the vasculature.
| S-EPMC3684769 | biostudies-literature
Project description:As a common ocular complication for diabetic patients, diabetic retinopathy has become an important public health problem in the world. Early diagnosis and early treatment with the help of fundus imaging technology is an effective control method. In this paper, a robust inverse diffusion equation combining a self-similarity filtering is presented to detect and evaluate diabetic retinopathy using retinal image enhancement. A flux corrected transport technique is used to control diffusion flux adaptively, which eliminates overshoots inherent in the Laplacian operation. Feature preserving denoising by the self-similarity filtering ensures a robust enhancement of noisy and blurry retinal images. Experimental results demonstrate that this algorithm can enhance important details of retinal image data effectively, affording an opportunity for better medical interpretation and subsequent processing.
| S-EPMC4936706 | biostudies-literature
Project description:Scanning acoustic microscopy (SAM) is a label-free imaging technique used in biomedical imaging, non-destructive testing, and material research to visualize surface and sub-surface structures. In ultrasonic imaging, noises in images can reduce contrast, edge and texture details, and resolution, negatively impacting post-processing algorithms. To reduce the noises in the scanned image, we have employed a 4D block-matching (BM4D) filter that can be used to denoise acoustic volumetric signals. BM4D filter utilizes the transform domain filtering technique with hard thresholding and Wiener filtering stages. The proposed algorithm produces the most suitable denoised output compared to other conventional filtering methods (Gaussian filter, median filter, and Wiener filter) when applied to noisy images. The output from the BM4D-filtered images was compared to the noise level with different conventional filters. Filtered images were qualitatively analyzed using metrics such as structural similarity index matrix (SSIM) and peak signal-to-noise ratio (PSNR). The combined qualitative and quantitative analysis demonstrates that the BM4D technique is the most suitable method for denoising acoustic imaging from the SAM. The proposed block matching filter opens a new avenue in the field of acoustic or photoacoustic image denoising, particularly in scenarios with poor signal-to-noise ratios.
| S-EPMC10425453 | biostudies-literature
Project description:The perivascular space (PVS) surrounds cerebral blood vessels and plays an important role in clearing waste products from the brain. Their anatomy and function have been described for arteries, but PVS around veins remain poorly characterized. Using in vivo 2-photon imaging in mice, we determined the size of the PVS around arteries and veins, and their connection with the subarachnoid space. After infusion of 70 kD FITC-dextran into the cerebrospinal fluid via the cisterna magna, labeled PVS were evident around arteries, but veins showed less frequent labeling of the PVS. The size of the PVS correlated with blood vessel size for both pial arteries and veins, but not for penetrating vessels. The PVS around pial arteries and veins was separated from the subarachnoid space by a thin meningeal layer, which did not form a barrier for the tracer. In vivo, FITC-dextran signal was observed adjacent to the vessel wall, but minimally within the wall itself. Post-mortem, there was a significant shift in the tracer's location within the arterial wall, extending into the smooth muscle layer. Taken together, these findings suggest that the PVS around veins has a limited role in the exchange of solutes between CSF and brain parenchyma.
| S-EPMC11291892 | biostudies-literature
Project description:Background and aimsEnlarged perivascular spaces (also known as Virchow-Robin spaces) on T2-weighted brain magnetic resonance imaging are common, but their etiology, and specificity to small vessel as opposed to general cerebrovascular disease or ageing, is unclear. We tested the association between enlarged perivascular spaces and ischemic stroke subtype, other markers of small vessel disease, and common vascular risk factors.MethodsWe prospectively recruited patients with acute stroke, diagnosed and subtyped by a stroke physician using clinical features and brain magnetic resonance imaging. A neuroradiologist rated basal ganglia and centrum semiovale enlarged perivascular spaces on a five-point scale, white matter lesions, recent and old infarcts, and cerebral atrophy. We assessed associations between basal ganglia-, centrum semiovale- and total (combined basal ganglia and centrum semiovale) enlarged perivascular spaces, stroke subtype, white matter lesions, atrophy, and vascular risk factors.ResultsAmong 298 patients (mean age 68 years), after adjusting for vascular risk factors and white matter lesions, basal ganglia-enlarged perivascular spaces were associated with increasing age (P = 0.001), centrum semiovale-enlarged perivascular spaces (P < 0.001), cerebral atrophy (P = 0.03), and lacunar stroke subtype (P = 0.04). Centrum semiovale-enlarged perivascular spaces were associated mainly with basal ganglia-enlarged perivascular spaces. Total enlarged perivascular spaces were associated with increasing age (P = 0.01), deep white matter lesions (P = 0.005), and previous stroke (P = 0.006).ConclusionsEnlarged perivascular spaces are associated with age, lacunar stroke subtype and white matter lesions and should be considered as another magnetic resonance imaging marker of cerebral small vessel disease. Further evaluation of enlarged perivascular spaces in studies of ageing, stroke, and dementia is needed to determine their pathophysiological importance.
| S-EPMC4463944 | biostudies-literature
Project description:Perivascular spaces, also known as Virchow-Robin spaces, are usually considered as a normal, asymptomatic finding. However, this finding can occasionally demonstrate an atypical appearance and can be symptomatic. We report herein a rare case of cognitive impairment associated with extremely enlarged perivascular spaces. A 68-year-old Japanese woman visited our hospital with a 1-year history of progressive memory impairment. In addition to temporal disorientation and short-term memory impairment, neuropsychological testing showed frontal lobe-related symptoms such as slowed thinking processes, reduced verbal fluency, attention deficit, and reduced working memory. Magnetic resonance imaging of the brain showed widespread enlarged perivascular spaces almost symmetrically in the subcortical white matter of bilateral hemispheres, prominently in bilateral insulas, and frontal opercula. On 99mTc-ethyl cysteinate dimer single photon emission computed tomography, hypoperfusion was apparent in bilateral insulas and frontal opercula where enlarged periventricular spaces were prominent, whereas cerebral perfusion was preserved in areas where enlargement of perivascular spaces was mild or absent. Because symptoms were consistent with the distribution of the enlarged perivascular spaces and hypoperfusion in the brain, cognitive impairment due to enlarged perivascular spaces was diagnosed. Clinicians should note enlarged perivascular spaces as a potential cause of neurological deficits including cognitive impairment.
| S-EPMC8319478 | biostudies-literature