Dataset Information

Temporal characterization of the functional density of the vasa vasorum by contrast-enhanced ultrasonography maximum intensity projection imaging.

ABSTRACT: We sought to determine whether contrast-enhanced ultrasound (CEU) microangiography with maximum intensity projection (MIP) processing could temporally evaluate proliferation of the vasa vasorum (VV) in a model of mural hemorrhage.Expansion of the VV and plaque neovascularization contributes to plaque growth and instability and may be triggered by a variety of stimuli, including vascular hemorrhage. However, quantitative in vivo methods for temporal assessment of VV remodeling are lacking.In 24 rabbits fed a high-fat diet, either autologous whole blood or saline was percutaneously injected into the media-adventitia of the femoral artery using ultrahigh-frequency ultrasound guidance. Functional VV density at the injection site and contralateral control artery was assessed 1, 2, and 6 weeks after injection with CEU imaging with MIP processing. In vitro studies with renathane microtubes were also performed to validate linear density measurement with CEU and MIP processing.In vitro studies demonstrated that MIP processing of CEU data reflected the relative linear density of vessels in a manner that was relatively independent of contrast concentration or microtube flow rate. On CEU with MIP, there was a 3-fold increase in femoral artery VV microvascular density at 1 and 2 weeks after blood injection (p < 0.01 vs. contralateral control), whereas VV density increased minimally after saline injection. At 6 weeks, VV vascular density decreased in blood-treated vessels and was not different from saline-injected or contralateral control vessels.CEU with MIP processing can provide quantitative data on temporal changes in the functional density of the VV. This method may be useful for evaluating high-risk features of plaque neovascularization or response to therapies aimed at plaque neovessels.

SUBMITTER: Lee SC

PROVIDER: S-EPMC3341849 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Temporal characterization of the functional density of the vasa vasorum by contrast-enhanced ultrasonography maximum intensity projection imaging.

Lee Sang Chol SC Carr Chad L CL Davidson Brian P BP Ellegala Dilantha D Xie Aris A Ammi Azzdine A Belcik Todd T Lindner Jonathan R JR

JACC. Cardiovascular imaging 20101201 12

<h4>Objectives</h4>We sought to determine whether contrast-enhanced ultrasound (CEU) microangiography with maximum intensity projection (MIP) processing could temporally evaluate proliferation of the vasa vasorum (VV) in a model of mural hemorrhage.<h4>Background</h4>Expansion of the VV and plaque neovascularization contributes to plaque growth and instability and may be triggered by a variety of stimuli, including vascular hemorrhage. However, quantitative in vivo methods for temporal assessmen ...[more]

PMID: 21163455

Similar Datasets

Project description:PurposeTo investigate whether short-term, intensive lipid therapy leads to changes in microvascular characteristics, as measured by using dynamic contrast material-enhanced (DCE) magnetic resonance (MR) imaging.Materials and methodsInstitutional review board approval and informed consent were obtained for this HIPAA-compatible study. Subjects with established coronary artery disease or carotid artery stenosis of 15% or greater determined by using ultrasonography and with levels of apolipoprotein B of 120 mg/dL (1.2 g/L) or greater were enrolled in an ongoing study (clinical trial NCT00715273). All received intensive lipid therapy to achieve targeted high- and low-density lipoprotein cholesterol levels and underwent serial serum monitoring including high-sensitivity C-reactive protein (HsCRP) level measurements. Carotid artery MR imaging examinations including morphologic and DCE MR images were obtained at baseline and 1 year after treatment. In subjects with advanced lesions (>2 mm thick), MR image analysis was performed, including measurement of lipid-rich necrotic core size and kinetic modeling of DCE MR images to assess changes in the transfer constant (K(trans)). The differences in K(trans) between baseline and 1-year follow-up were compared by using the Wilcoxon signed rank test, and associations were assessed by using the Spearman rank correlation coefficient.ResultsTwenty-eight subjects with interpretable DCE MR imaging results at both baseline and 1-year follow-up were included. After 1 year of treatment, a significant reduction was found in mean K(trans) (0.085 min(-1) ± 0.037 [standard deviation] to 0.067 min(-1) ± 0.028, P = .02). Reduction in K(trans) was not significantly correlated with observed reductions in lipid-rich necrotic core size or reductions in HsCRP level.ConclusionThese findings suggest that DCE MR imaging may be a useful imaging method for the assessment of the therapeutic response of the vasa vasorum in patients with atherosclerotic plaque.

Project description:ObjectivesTo automatically detect MRI artifacts on dynamic contrast-enhanced (DCE) maximum intensity projections (MIPs) of the breast using deep learning.MethodsWomen who underwent clinically indicated breast MRI between October 2015 and December 2019 were included in this IRB-approved retrospective study. We employed two convolutional neural network architectures (ResNet and DenseNet) to detect the presence of artifacts on DCE MIPs of the left and right breasts. Networks were trained on images acquired up to and including the year 2018 using a 5-fold cross-validation (CV). Ensemble classifiers were built with the resulting CV models and applied to an independent holdout test dataset, which was formed by images acquired in 2019.ResultsOur study sample contained 2265 examinations from 1794 patients (median age at first acquisition: 50 years [IQR: 17 years]), corresponding to 1827 examinations of 1378 individuals in the training dataset and 438 examinations of 416 individuals in the holdout test dataset with a prevalence of image-level artifacts of 53% (1951/3654 images) and 43% (381/876 images), respectively. On the holdout test dataset, the ResNet and DenseNet ensembles demonstrated an area under the ROC curve of 0.92 and 0.94, respectively.ConclusionNeural networks are able to reliably detect artifacts that may impede the diagnostic assessment of MIPs derived from DCE subtraction series in breast MRI. Future studies need to further explore the potential of such neural networks to complement quality assurance and improve the application of DCE MIPs in a clinical setting, such as abbreviated protocols.Key points• Deep learning classifiers are able to reliably detect MRI artifacts in dynamic contrast-enhanced protocol-derived maximum intensity projections of the breast. • Automated quality assurance of maximum intensity projections of the breast may be of special relevance for abbreviated breast MRI, e.g., in high-throughput settings, such as cancer screening programs.

Dataset Information

Temporal characterization of the functional density of the vasa vasorum by contrast-enhanced ultrasonography maximum intensity projection imaging.

Publications

Temporal characterization of the functional density of the vasa vasorum by contrast-enhanced ultrasonography maximum intensity projection imaging.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets