Literature DB >> 26211685

Spatio-temporal Quantification of Carotid Plaque Neovascularization on Contrast Enhanced Ultrasound: Correlation with Visual Grading and Histopathology.

Q Zhang1, C Li2, H Han2, W Dai3, J Shi3, Y Wang4, W Wang2.   

Abstract

OBJECTIVE/
BACKGROUND: To evaluate whether carotid intraplaque neovascularization (IPN) can be accurately assessed by two types of quantitative analysis on contrast enhanced ultrasound (CEUS), the time intensity curve analysis and the analysis of contrast agent spatial distributions, and whether the quantitative analysis correlates with semiquantitative visual interpretation and histopathology.
METHODS: Forty-four plaques in 34 patients were included for CEUS examination. A three point score system (absent, moderate, and extensive) was used for semiquantitative grading of IPN. Eight spatial quantitative parameters were derived, including the IPN area ratio in plaque (AR) and the AR in plaque core (AR13). Two temporal quantitative parameters were obtained, namely the enhanced intensity in plaque (EI) and the enhanced intensity ratio (EIR). Histopathology with CD34 staining for quantification of microvessel density (MVD) was performed on 12 plaques excised by carotid endarterectomy.
RESULTS: Both spatial and temporal parameters were correlated with MVD on histology (AR: r = .854; AR13: r = .858; EI: r = .767; EIR: r = .750 [p < .01]), as well as with semiquantitative grading (p < .01). Five mutually independent factors were condensed from 10 interrelated parameters by using factor analysis, and they significantly predicted MVD with an radj value as high as .932 (p = .01).
CONCLUSION: Both spatial and temporal analysis on CEUS can accurately assess IPN. Combining them provides better IPN assessment and may be useful for plaque vulnerability evaluation and risk stratification.
Copyright © 2015 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Carotid plaque; Contrast enhanced ultrasound; Intraplaque neovascularization; Microvessels; Quantitative analysis; Spatial and temporal analysis

Mesh:

Substances:

Year:  2015        PMID: 26211685     DOI: 10.1016/j.ejvs.2015.06.077

Source DB:  PubMed          Journal:  Eur J Vasc Endovasc Surg        ISSN: 1078-5884            Impact factor:   7.069


  7 in total

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Authors:  Bin Xu; Jin Xing; Wenqing Wu; Wen-Jing Zhang; Qian-Qian Zhu; Dan Zhang; Nan-Nan Sun; Chan Wu; Geng-Jie Kang; Lin Zhai; Wei-Dong Li; Yan Meng; Tie-Ying Du
Journal:  Exp Ther Med       Date:  2018-03-06       Impact factor: 2.447

2.  Quantification of carotid artery plaque stability with multiple region of interest based ultrasound strain indices and relationship with cognition.

Authors:  N H Meshram; T Varghese; C C Mitchell; D C Jackson; S M Wilbrand; B P Hermann; R J Dempsey
Journal:  Phys Med Biol       Date:  2017-07-17       Impact factor: 3.609

3.  Multilevel Strip Pooling-Based Convolutional Neural Network for the Classification of Carotid Plaque Echogenicity.

Authors:  Wei Ma; Xinyao Cheng; Xiangyang Xu; Furong Wang; Ran Zhou; Aaron Fenster; Mingyue Ding
Journal:  Comput Math Methods Med       Date:  2021-08-18       Impact factor: 2.238

4.  Object-Specific Four-Path Network for Stroke Risk Stratification of Carotid Arteries in Ultrasound Images.

Authors:  Wei Ma; Yujiao Xia; Xiaoyan Wu; Zheng Yue; Xinyao Cheng; Aaron Fenster; Mingyue Ding
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Review 5.  Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.

Authors:  Qinghua Huang; Fan Zhang; Xuelong Li
Journal:  Biomed Res Int       Date:  2018-03-04       Impact factor: 3.411

6.  Dual-mode ultrasound radiomics and intrinsic imaging phenotypes for diagnosis of lymph node lesions.

Authors:  Ying Chen; Jianwei Jiang; Jie Shi; Wanying Chang; Jun Shi; Man Chen; Qi Zhang
Journal:  Ann Transl Med       Date:  2020-06

7.  The association of lipoprotein(a) and intraplaque neovascularization in patients with carotid stenosis: a retrospective study.

Authors:  Shuang Xia; Weida Qiu; Anping Cai; Bo Kong; Lan Xu; Zejia Wu; Liwen Li
Journal:  BMC Cardiovasc Disord       Date:  2021-06-09       Impact factor: 2.298

  7 in total

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