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Articles Published Processes
6/20/2016 1:48:00 PM | Browse: 1121 | Download: 1759
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Received |
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2015-11-06 09:02 |
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Peer-Review Started |
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2015-11-06 11:36 |
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To Make the First Decision |
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2015-11-24 14:14 |
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Return for Revision |
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2015-11-29 20:22 |
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Revised |
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2015-12-07 20:43 |
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Second Decision |
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2016-03-07 15:51 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2016-03-18 15:57 |
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Articles in Press |
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2016-03-18 15:57 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2016-06-11 17:05 |
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Publish the Manuscript Online |
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2016-06-18 17:56 |
ISSN |
1949-8470 (online) |
Open Access |
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
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Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Radiology, Nuclear Medicine & Medical Imaging |
Manuscript Type |
Clinical Trials Study |
Article Title |
Predictive model for contrast-enhanced ultrasound of the breast: Is it feasible in malignant risk assessment of breast imaging reporting and data system 4 lesions?
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
Jun Luo, Ji-Dong Chen, Qing Chen, Lin-Xian Yue, Guo Zhou, Cheng Lan, Yi Li, Chi-Hua Wu and Jing-Qiao Lu |
Funding Agency and Grant Number |
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Corresponding Author |
Ji-Dong Chen, BM, Department of Ultrasound, Sichuan Provincial People’s Hospital, No. 32 First Ring Road, Chengdu 610072, Sichuan Province,
China. 13666129119@163.com
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Key Words |
Breast; Contrast-enhanced ultrasound; Qualitative analysis; Breast imaging reporting and data system; Predictive model |
Core Tip |
Many studies published show that there are some enhanced patterns such as rapid, hyper-enhancement or enlarged size after contrast may predict malignant, but none of them reliably differentiates malignant from benign nodules. We try to build 6 predictive models (3 malignant and 3 benign) using a qualitative analysis of enhancement patterns, and get diagnostic sensitivity, specificity, and accuracy of the malignant vs benign contrast-enhanced ultrasound (CEUS) models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. It shows that the breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate breast imaging reporting and data system classification.
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Publish Date |
2016-06-18 17:56 |
Citation |
Luo J, Chen JD, Chen Q, Yue LX, Zhou G, Lan C, Li Y, Wu CH, Lu JQ. Predictive model for contrast-enhanced ultrasound of the breast: Is it feasible in malignant risk assessment of breast imaging reporting and data system 4 lesions? World J Radiol 2016; 8(6): 600-609 |
URL |
http://www.wjgnet.com/1949-8470/full/v8/i6/600.htm |
DOI |
http://dx.doi.org/10.4329/wjr.v8.i6.600 |
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