The feasibility of classifying breast masses using a computer-assisted diagnosis (CAD) system based on ultrasound elastography and BI-RADS lexicon

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Abstract

Objectives: To determine the applicability of a computer-aided diagnostic system strain elastography system for the classification of breast masses diagnosed by ultrasound and scored using the criteria proposed by the breast imaging and reporting data system ultrasound lexicon and to determine the diagnostic accuracy and interobserver variability. Methods: This prospective study was conducted between March 1, 2016, and May 30, 2016. A total of 83 breast masses subjected to percutaneous biopsy were included. Ultrasound elastography images before biopsy were interpreted by 3 radiologists with and without the aid of computer-aided diagnostic system for strain elastography. The parameters evaluated by each radiologist results were sensitivity, specificity, and diagnostic accuracy, with and without computer-aided diagnostic system for strain elastography. Interobserver variability was assessed using a weighted k test and an intraclass correlation coefficient. The areas under the receiver operating characteristic curves were also calculated. Results: The areas under the receiver operating characteristic curve were 0.835, 0.801, and 0.765 for readers 1, 2, and 3, respectively, without computer-aided diagnostic system for strain elastography, and 0.900, 0.926, and 0.868, respectively, with computer-aided diagnostic system for strain elastography. The intraclass correlation coefficient between the 3 readers was 0.6713 without computer-aided diagnostic system for strain elastography and 0.811 with computer-aided diagnostic system for strain elastography. Conclusion: The proposed computer-aided diagnostic system for strain elastography system has the potential to improve the diagnostic performance of radiologists in breast examination using ultrasound associated with elastography.

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Fleury, E. F. C., Gianini, A. C., Marcomini, K., & Oliveira, V. (2018). The feasibility of classifying breast masses using a computer-assisted diagnosis (CAD) system based on ultrasound elastography and BI-RADS lexicon. Technology in Cancer Research and Treatment, 17. https://doi.org/10.1177/1533033818763461

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