Literature DB >> 24029644

Two-view versus single-view shear-wave elastography: comparison of observer performance in differentiating benign from malignant breast masses.

Su Hyun Lee1, Nariya Cho, Jung Min Chang, Hye Ryoung Koo, Jin You Kim, Won Hwa Kim, Min Sun Bae, Ann Yi, Woo Kyung Moon.   

Abstract

PURPOSE: To determine whether two-view shear-wave elastography (SWE) improves the performance of radiologists in differentiating benign from malignant breast masses compared with single-view SWE.
MATERIALS AND METHODS: This prospective study was conducted with institutional review board approval, and written informed consent was obtained. B-mode ultrasonographic (US) and orthogonal SWE images were obtained for 219 breast masses (136 benign and 83 malignant; mean size, 14.8 mm) in 219 consecutive women (mean age, 47.9 years; range, 20-78 years). Five blinded radiologists independently assessed the likelihood of malignancy for three data sets: B-mode US alone, B-mode US and single-view SWE, and B-mode US and two-view SWE. Interobserver agreement regarding Breast Imaging Reporting and Data System (BI-RADS) category and the area under the receiver operating characteristic curve (AUC) of each data set were compared.
RESULTS: Interobserver agreement was moderate (κ = 0.560 ± 0.015 [standard error of the mean]) for BI-RADS category assessment with B-mode US alone. When SWE was added to B-mode US, five readers showed substantial interobserver agreement (κ = 0.629 ± 0.017 for single-view SWE; κ = 0.651 ± 0.014 for two-view SWE). The mean AUC of B-mode US was 0.870 (range, 0.855-0.884). The AUC of B-mode US and two-view SWE (average, 0.928; range, 0.904-0.941) was higher than that of B-mode US and single-view SWE (average, 0.900; range, 0.890-0.920), with statistically significant differences for three readers (P ≤ .003).
CONCLUSION: The performance of radiologists in differentiating benign from malignant breast masses was improved when B-mode US was combined with two-view SWE compared with that when B-mode US was combined with single-view SWE. © RSNA, 2013

Entities:  

Mesh:

Year:  2013        PMID: 24029644     DOI: 10.1148/radiol.13130561

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  12 in total

1.  Prediction of invasive breast cancer using shear-wave elastography in patients with biopsy-confirmed ductal carcinoma in situ.

Authors:  Jae Seok Bae; Jung Min Chang; Su Hyun Lee; Sung Ui Shin; Woo Kyung Moon
Journal:  Eur Radiol       Date:  2016-04-16       Impact factor: 5.315

2.  Update on Breast Cancer Detection Using Comb-Push Ultrasound Shear Elastography.

Authors:  Max Denis; Mahdi Bayat; Mohammad Mehrmohammadi; Adriana Gregory; Pengfei Song; Dana H Whaley; Sandhya Pruthi; Shigao Chen; Mostafa Fatemi; Azra Alizad
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2015-09       Impact factor: 2.725

3.  An investigation of the classification accuracy of a deep learning framework-based computer-aided diagnosis system in different pathological types of breast lesions.

Authors:  Mengsu Xiao; Chenyang Zhao; Qingli Zhu; Jing Zhang; He Liu; Jianchu Li; Yuxin Jiang
Journal:  J Thorac Dis       Date:  2019-12       Impact factor: 2.895

4.  Breast vibro-acoustography: initial experience in benign lesions.

Authors:  Azra Alizad; Mohammad Mehrmohammadi; Karthik Ghosh; Katrina N Glazebrook; Rickey E Carter; Leman Gunbery Karaberkmez; Dana H Whaley; Mostafa Fatemi
Journal:  BMC Med Imaging       Date:  2014-12-30       Impact factor: 1.930

5.  Comb-push ultrasound shear elastography of breast masses: initial results show promise.

Authors:  Max Denis; Mohammad Mehrmohammadi; Pengfei Song; Duane D Meixner; Robert T Fazzio; Sandhya Pruthi; Dana H Whaley; Shigao Chen; Mostafa Fatemi; Azra Alizad
Journal:  PLoS One       Date:  2015-03-16       Impact factor: 3.240

6.  Ultrasound shear wave elastography of breast lesions: correlation of anisotropy with clinical and histopathological findings.

Authors:  Ya-Ling Chen; Yi Gao; Cai Chang; Fen Wang; Wei Zeng; Jia-Jian Chen
Journal:  Cancer Imaging       Date:  2018-04-05       Impact factor: 3.909

7.  Comparison of strain and shear wave elastography for qualitative and quantitative assessment of breast masses in the same population.

Authors:  Hyo Jin Kim; Sun Mi Kim; Bohyoung Kim; Bo La Yun; Mijung Jang; Yousun Ko; Soo Hyun Lee; Heeyeong Jeong; Jung Min Chang; Nariya Cho
Journal:  Sci Rep       Date:  2018-04-18       Impact factor: 4.379

8.  Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography.

Authors:  Ji Soo Choi; Boo Kyung Han; Eun Sook Ko; Jung Min Bae; Eun Young Ko; So Hee Song; Mi Ri Kwon; Jung Hee Shin; Soo Yeon Hahn
Journal:  Korean J Radiol       Date:  2019-05       Impact factor: 3.500

Review 9.  Shear-wave elastography in breast ultrasonography: the state of the art.

Authors:  Ji Hyun Youk; Hye Mi Gweon; Eun Ju Son
Journal:  Ultrasonography       Date:  2017-04-05

10.  Diagnostic Value of Breast Lesions Between Deep Learning-Based Computer-Aided Diagnosis System and Experienced Radiologists: Comparison the Performance Between Symptomatic and Asymptomatic Patients.

Authors:  Mengsu Xiao; Chenyang Zhao; Jianchu Li; Jing Zhang; He Liu; Ming Wang; Yunshu Ouyang; Yixiu Zhang; Yuxin Jiang; Qingli Zhu
Journal:  Front Oncol       Date:  2020-07-07       Impact factor: 6.244

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.