Which supplementary imaging modality should be used for breast ultrasonography? Comparison of the diagnostic performance of elastography and computer-aided diagnosis.
- Author:
Si Eun LEE
1
;
Ji Eun MOON
;
Yun Ho RHO
;
Eun Kyung KIM
;
Jung Hyun YOON
Author Information
- Publication Type:Original Article
- Keywords: Breast; Ultrasonography; BI-RADS; Elasticity imaging techniques; Diagnosis, computer-assisted
- MeSH: Area Under Curve; Breast*; Diagnosis*; Diagnosis, Computer-Assisted; Diagnosis, Differential; Elasticity; Elasticity Imaging Techniques*; Female; Humans; Information Systems; Sensitivity and Specificity; Ultrasonography; Ultrasonography, Mammary*
- From: Ultrasonography 2017;36(2):153-159
- CountryRepublic of Korea
- Language:English
- 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.
