Evaluation of Carotid Plaque Rupture and Neovascularization by Contrast-Enhanced Ultrasound Imaging: an Exploratory Study Based on Histopathology

Lyu, Qi; Tian, Xiaojie; Ding, Yao; Yan, Yanhong; Huang, Yabo; Zhou, Peng; Hui, Pinjing

doi:10.1007/s12975-020-00825-w

Cited by 41 publications

(23 citation statements)

References 29 publications

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“…Among them, 100 were further excluded due to different research designs or insufficient data. Finally, 10 papers were included in this metaanalysis [16][17][18][19][20][21][22][23][24][25]. Further information about the search process and inclusion and exclusion criteria was shown in Figure 1.…”

Section: Search Processmentioning

confidence: 99%

Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis

Dong

Hou

Zhang

et al. 2022

Computational and Mathematical Methods in Medicine

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Objectives. To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for atherosclerotic carotid plaque neovascularization. Methods. The electronic databases like PubMed, Embase, OVID, and Web of Science were used to search for the relevant studies, which are involved in the evaluation of the diagnostic parameters of QUS for atherosclerotic carotid plaque neovascularization. Review Manager 5.4 and Stata 14.0 were used to estimate the pooled diagnostic value of CEUS. Forest plots, sensitivity analysis, and Deeks’ funnel plots were performed on the included studies. Results. Ten studies eventually met the final inclusion criteria. For diagnostic performance, CUES showed that the pooled values of sensitivity, specificity, positive likelihood odds ratios, negative likelihood odds ratios, and diagnostic odds ratios were 0.83 (95% CI 0.78-0.86), 0.77 (95% CI 0.68-0.84), 3.61 (95% CI 2.59-5.03), 0.23 (95% CI 0.18-0.28), and 16.02 (95% CI 10.02-25.60), respectively. The estimate of the area under curve (AUC) was 0.85 (95% CI 0.82-0.88). Conclusion. Our research supported that CEUS had high sensitivity and specificity in the diagnosis of atherosclerotic carotid plaque neovascularization. More high-quality prospective multicenter studies focusing on the accuracy of CEUS for carotid atherosclerotic plaque should be performed to verify our conclusions.

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Section: Search Processmentioning

confidence: 99%

Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis

Dong

Hou

Zhang

et al. 2022

Computational and Mathematical Methods in Medicine

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“…Contrast‐enhanced ultrasound (US) imaging, [ 2 ] dynamic contrast‐enhanced magnetic resonance imaging (MRI), [ 3 ] and optical coherence tomography [ 4 ] are the traditional imaging techniques used to detect plaque neovascularization. However, they are unable to assess plaque angiogenesis at the cellular and molecular levels.…”

Section: Introductionmentioning

confidence: 99%

Low‐Intensity Focused Ultrasound‐Responsive Ferrite‐Encapsulated Nanoparticles for Atherosclerotic Plaque Neovascularization Theranostics

et al. 2021

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Pathological angiogenesis is a crucial factor that causes atherosclerotic plaque rupture. Sinoporphyrin sodium-mediated sonodynamic therapy (DVDMS-SDT) induces regression of plaque neovascularization in humans without causing obvious side effects. However, a clinical noninvasive theranostic strategy for atherosclerotic plaque neovascularization is urgently needed. A nanoplatform designed for multimodality imaging-guided SDT in plaque angiogenesis theranostics, termed PFP-HMME@PLGA/ MnFe 2 O 4 -ramucirumab nanoparticles (PHPMR NPs), is fabricated. It encapsulates manganese ferrite (MnFe 2 O 4 ), hematoporphyrin monomethyl ether (HMME), and perfluoropentane (PFP) stabilized by polylactic acid-glycolic acid (PLGA) shells and is conjugated to an anti-VEGFR-2 antibody. With excellent magnetic resonance imaging (MRI)/photoacoustic/ ultrasound imaging ability, the distribution of PHPMR NPs in plaque can be observed in real time. Additionally, they actively accumulate in the mitochondria of rabbit aortic endothelial cells (RAECs), and the PHPMR NP-mediated SDT promotes mitochondrial-caspase apoptosis via the production of reactive oxygen species and inhibits the proliferation, migration, and tubulogenesis of RAECs. On day 3, PHPMR NP-mediated SDT induces apoptosis in neovessel endothelial cells and improves hypoxia in the rabbit advanced plaque. On day 28, PHPMR NP-mediated SDT reduces the density of neovessels, subsequently inhibiting intraplaque hemorrhage and inflammation and eventually stabilizing the plaque. Collectively, PHPMR NP-mediated SDT presents a safe and effective theranostic strategy for inhibiting plaque angiogenesis.

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“…The bilateral common carotid arteries (CCA), carotid artery bulb (CAB), and internal carotid arteries (ICA) were observed by gray scale imaging, color flow imaging, and spectral Doppler analysis. If plaques were observed, the plaque size, shape, echo, integrity, and degree of vascular stenosis were determined using multi-section and multi-angle imaging, as well as the peak systolic velocity, the end-diastolic velocity, and the resistance index (Lyu et al, 2021a). All the images of carotid atherosclerotic plaques were saved and analyzed.…”

Section: Carotid Ultrasound Protocolmentioning

confidence: 99%

Texture Analysis Based on Vascular Ultrasound to Identify the Vulnerable Carotid Plaques

Zhang

Lyu²,

Ding³

et al. 2022

Front. Neurosci.

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Vulnerable carotid plaques are closely related to the occurrence of ischemic stroke. Therefore, accurate and rapid identification of the nature of carotid plaques is essential. This study aimed to determine whether texture analysis based on a vascular ultrasound can be applied to identify vulnerable plaques. Data from a total of 150 patients diagnosed with atherosclerotic plaque (AP) by carotid ultrasound (CDU) and high-resolution magnetic resonance imaging (HRMRI) were collected. HRMRI is the in vivo reference to assess the nature of AP. MaZda software was used to delineate the region of interest and extract 303 texture features from ultrasonic images of plaques. Following regression analysis using the least absolute shrinkage and selection operator (LASSO) algorithm, the overall cohort was randomized 7:3 into the training (n = 105) and testing (n = 45) sets. In the training set, the conventional ultrasound model, the texture feature model, and the conventional ultrasound-texture feature combined model were constructed. The testing set was used to validate the model’s effectiveness by calculating the area under the curve (AUC), accuracy, sensitivity, and specificity. Based on the combined model, a nomogram risk prediction model was established, and the consistency index (C-index) and the calibration curve were obtained. In the training and testing sets, the AUC of the prediction performance of the conventional ultrasonic-texture feature combined model was higher than that of the conventional ultrasonic model and the texture feature model. In the training set, the AUC of the combined model was 0.88, while in the testing set, AUC was 0.87. In addition, the C-index results were also favorable (0.89 in the training set and 0.84 in the testing set). Furthermore, the calibration curve was close to the ideal curve, indicating the accuracy of the nomogram. This study proves the performance of vascular ultrasound-based texture analysis in identifying the vulnerable carotid plaques. Texture feature extraction combined with CDU sonogram features can accurately predict the vulnerability of AP.

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Evaluation of Carotid Plaque Rupture and Neovascularization by Contrast-Enhanced Ultrasound Imaging: an Exploratory Study Based on Histopathology

Cited by 41 publications

References 29 publications

Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis

Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis

Low‐Intensity Focused Ultrasound‐Responsive Ferrite‐Encapsulated Nanoparticles for Atherosclerotic Plaque Neovascularization Theranostics

Texture Analysis Based on Vascular Ultrasound to Identify the Vulnerable Carotid Plaques

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