Which Supplementary Imaging Modality Should Be Used for Breast Ultrasonography? Comparison of the Diagnostic Performance of Elastography and Computer-aided Diagnosis

Overview

Journal Ultrasonography

Date 2016 Oct 22

PMID 27764908

Citations 3

Authors

Si Eun Lee

Ji Eun Moon

Yun Ho Rho

Eun-Kyung Kim

Jung Hyun Yoon

Affiliations

Soon will be listed here.

Abstract

Purpose: The aim of this study was to evaluate and compare the diagnostic performance of grayscale ultrasonography (US), US elastography, and US computer-aided diagnosis (US-CAD) in the differential diagnosis of breast masses.

Methods: A total of 193 breast masses in 175 consecutive women (mean age, 46.4 years) from June to August 2015 were included. US and elastography images were obtained and recorded. A US-CAD system was applied to the grayscale sonograms, which were automatically analyzed and visualized in order to generate a final assessment. The final assessments of breast masses were based on the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories, while elasticity scores were assigned using a 5-point scoring system. The diagnostic performance of grayscale US, elastography, and US-CAD was calculated and compared.

Results: Of the 193 breast masses, 120 (62.2%) were benign and 73 (37.8%) were malignant. Breast masses had significantly higher rates of malignancy in BI-RADS categories 4c and 5, elastography patterns 4 and 5, and when the US-CAD assessment was possibly malignant (all P<0.001). Elastography had higher specificity (40.8%, P=0.042) than grayscale US. US-CAD showed the highest specificity (67.5%), positive predictive value (PPV) (61.4%), accuracy (74.1%), and area under the curve (AUC) (0.762, all P<0.05) among the three diagnostic tools.

Conclusion: US-CAD had higher values for specificity, PPV, accuracy, and AUC than grayscale US or elastography. Computer-based analysis based on the morphologic features of US may be very useful in improving the diagnostic performance of breast US.

Citing Articles

Analysis of the accuracy of ultrasound elastography and BI-RADS classification of breast masses located within the superficial fat layer of the glands.

Xue N, Zhang S Gland Surg. 2022; 11(10):1722-1729.

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A Review of the Role of the S-Detect Computer-Aided Diagnostic Ultrasound System in the Evaluation of Benign and Malignant Breast and Thyroid Masses.

Zhang D, Jiang F, Yin R, Wu G, Wei Q, Cui X Med Sci Monit. 2021; 27:e931957.

PMID: 34552043 PMC: 8477643. DOI: 10.12659/MSM.931957.

Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience.

Choi J, Kang B, Baek J, Lee H, Kim S Ultrasonography. 2017; 37(3):217-225.

PMID: 28992680 PMC: 6044219. DOI: 10.14366/usg.17046.

References

Lazarus E, Mainiero M, Schepps B, Koelliker S, Livingston L . BI-RADS lexicon for US and mammography: interobserver variability and positive predictive value. Radiology. 2006; 239(2):385-91. DOI: 10.1148/radiol.2392042127. View

Alhabshi S, Rahmat K, Abdul Halim N, Aziz S, Radhika S, Gan G . Semi-quantitative and qualitative assessment of breast ultrasound elastography in differentiating between malignant and benign lesions. Ultrasound Med Biol. 2013; 39(4):568-78. DOI: 10.1016/j.ultrasmedbio.2012.10.016. View

Hao S, Ou B, Li L, Peng Y, Wang Y, Liu L . Could ultrasonic elastography help the diagnosis of breast cancer with the usage of sonographic BI-RADS classification?. Eur J Radiol. 2015; 84(12):2492-500. DOI: 10.1016/j.ejrad.2015.08.015. View

Burnside E, Hall T, Sommer A, Hesley G, Sisney G, Svensson W . Differentiating benign from malignant solid breast masses with US strain imaging. Radiology. 2007; 245(2):401-10. DOI: 10.1148/radiol.2452061805. View

Berg W, Cosgrove D, Dore C, Schafer F, Svensson W, Hooley R . Shear-wave elastography improves the specificity of breast US: the BE1 multinational study of 939 masses. Radiology. 2012; 262(2):435-49. DOI: 10.1148/radiol.11110640. View

Chang J, Won J, Lee K, Park I, Yi A, Moon W . Comparison of shear-wave and strain ultrasound elastography in the differentiation of benign and malignant breast lesions. AJR Am J Roentgenol. 2013; 201(2):W347-56. DOI: 10.2214/AJR.12.10416. View

Yerli H, Yilmaz T, Kaskati T, Gulay H . Qualitative and semiquantitative evaluations of solid breast lesions by sonoelastography. J Ultrasound Med. 2011; 30(2):179-86. DOI: 10.7863/jum.2011.30.2.179. View

Kim K, Song M, Kim E, Yoon J . Clinical application of S-Detect to breast masses on ultrasonography: a study evaluating the diagnostic performance and agreement with a dedicated breast radiologist. Ultrasonography. 2016; 36(1):3-9. PMC: 5207353. DOI: 10.14366/usg.16012. View

Yoon J, Kim M, Moon H, Kwak J, Kim E . Subcategorization of ultrasonographic BI-RADS category 4: positive predictive value and clinical factors affecting it. Ultrasound Med Biol. 2011; 37(5):693-9. DOI: 10.1016/j.ultrasmedbio.2011.02.009. View

10.

Zhu Q, Jiang Y, Liu J, Liu H, Sun Q, Dai Q . Real-time ultrasound elastography: its potential role in assessment of breast lesions. Ultrasound Med Biol. 2008; 34(8):1232-8. DOI: 10.1016/j.ultrasmedbio.2008.01.004. View

11.

Kaisar Alam S, Feleppa E, Rondeau M, Kalisz A, Garra B . Ultrasonic multi-feature analysis procedure for computer-aided diagnosis of solid breast lesions. Ultrason Imaging. 2011; 33(1):17-38. DOI: 10.1177/016173461103300102. View

12.

Jalalian A, Mashohor S, Mahmud H, Saripan M, Ramli A, Karasfi B . Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review. Clin Imaging. 2012; 37(3):420-6. DOI: 10.1016/j.clinimag.2012.09.024. View

13.

Shan J, Kaisar Alam S, Garra B, Zhang Y, Ahmed T . Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods. Ultrasound Med Biol. 2016; 42(4):980-8. DOI: 10.1016/j.ultrasmedbio.2015.11.016. View

14.

Gong X, Xu Q, Xu Z, Xiong P, Yan W, Chen Y . Real-time elastography for the differentiation of benign and malignant breast lesions: a meta-analysis. Breast Cancer Res Treat. 2011; 130(1):11-8. DOI: 10.1007/s10549-011-1745-2. View

15.

Dromain C, Boyer B, Ferre R, Canale S, Delaloge S, Balleyguier C . Computed-aided diagnosis (CAD) in the detection of breast cancer. Eur J Radiol. 2012; 82(3):417-23. DOI: 10.1016/j.ejrad.2012.03.005. View

16.

Hatzung G, Grunwald S, Zygmunt M, Geaid A, Behrndt P, Isermann R . Sonoelastography in the diagnosis of malignant and benign breast lesions: initial clinical experiences. Ultraschall Med. 2010; 31(6):596-603. DOI: 10.1055/s-0029-1245526. View

17.

Park J, Woo O, Shin H, Cho K, Seo B, Kang E . Diagnostic performance and color overlay pattern in shear wave elastography (SWE) for palpable breast mass. Eur J Radiol. 2015; 84(10):1943-8. DOI: 10.1016/j.ejrad.2015.06.020. View

18.

Cho N, Moon W, Kim H, Chang J, Park S, Lyou C . Sonoelastographic strain index for differentiation of benign and malignant nonpalpable breast masses. J Ultrasound Med. 2009; 29(1):1-7. DOI: 10.7863/jum.2010.29.1.1. View

19.

Costantini M, Belli P, Lombardi R, Franceschini G, Mule A, Bonomo L . Characterization of solid breast masses: use of the sonographic breast imaging reporting and data system lexicon. J Ultrasound Med. 2006; 25(5):649-59. DOI: 10.7863/jum.2006.25.5.649. View

20.

Yoon J, Kim M, Kim E, Moon H, Kwak J, Kim M . Interobserver variability of ultrasound elastography: how it affects the diagnosis of breast lesions. AJR Am J Roentgenol. 2011; 196(3):730-6. DOI: 10.2214/AJR.10.4654. View