Clinical Trials Study
Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Jun 28, 2016; 8(6): 600-609
Published online Jun 28, 2016. doi: 10.4329/wjr.v8.i6.600
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?
Jun Luo, Ji-Dong Chen, Qing Chen, Lin-Xian Yue, Guo Zhou, Cheng Lan, Yi Li, Chi-Hua Wu, Jing-Qiao Lu
Jun Luo, Ji-Dong Chen, Qing Chen, Lin-Xian Yue, Guo Zhou, Cheng Lan, Department of Ultrasound, Sichuan Provincial People’s Hospital, Chengdu 610072, Sichuan Province, China
Yi Li, Chi-Hua Wu, Department of Breast Surgery, Sichuan Provincial People’s Hospital, Chengdu 610072, Sichuan Province, China
Jing-Qiao Lu, Department of Otolaryngology, School of Medicine, Emory University, Atlanta, GA 30322, United States
Author contributions: Luo J designed research; Luo J, Chen JD, Chen Q, Yue LX, Zhou G, Lan C, Li Y, Wu CH performed research; Lu JQ analyzed data; Luo J wrote the paper.
Institutional review board statement: The study was reviewed and approved by the Institutional review board of Sichuan Provincial People’s Hospital.
Clinical trial registration statement: This registration policy applies to retrospective study only.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: Not declared.
Data sharing statement: No additional data are available.
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/
Correspondence to: 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
Telephone: +86-28-87394616 Fax: +86-28-87394616
Received: October 9, 2015
Peer-review started: November 6, 2015
First decision: November 29, 2015
Revised: March 1, 2016
Accepted: March 17, 2016
Article in press: March 18, 2016
Published online: June 28, 2016
Processing time: 226 Days and 0.9 Hours
Abstract

AIM: To build and evaluate predictive models for contrast-enhanced ultrasound (CEUS) of the breast to distinguish between benign and malignant lesions.

METHODS: A total of 235 breast imaging reporting and data system (BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve (ROC).

RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant (P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively.

CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BI-RADS classification.

Keywords: 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.