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Abstract

Difference Analysis of Sensitivity of BI-RADS Classification of Breast Mass with Different Pathological Types

Author(s): Y. Tan, S. Liu, L. Ma and W. Du*
Department of Ultrasound, the People's Hospital of Shizhu County, Shizhu Chongqing 409100, China

Correspondence Address:
Department of Ultrasound, the People's Hospital of Shizhu County, Shizhu Chongqing 409100, China, E-mail: [email protected]

In order to study the differences in the sensitivity of various types of detection during the diagnosis of different pathological types of breast mass by ultrasound breast imaging reporting and data system classification, 3000 patients with breast disease treated in a hospital were selected for research in this study. The selected patient data had ultrasound effects and subsequent biopsy pathology reports, and the patient's basic data were also counted. The detection methods used for patients include ultrasound breast imaging reporting and data system classification and pathological tissue biopsy. The results of the study showed that the sensitivity of the ultrasound breast imaging reporting and data system classification was 87.75 %, the specificity was 90.89 %, the accuracy was 91.04 %, the positive predictive value was 79.24 %, the negative predictive value was 96.13 %, and through the receiver operating characteristic curve, the ultrasonic breast imaging reporting and data system classification test was verified to be an excellent detection method. Ultrasound breast imaging reporting and data system grading is generally more accurate for benign tumors, and the accuracy of detecting malignant tumors is slightly lower. This study demonstrated the differences in the detection sensitivity of different types of breast masses by ultrasound breast imaging reporting and data system grading. It provided a theoretical basis for the physician to judge whether the patient needs biopsy after receiving the ultrasound test, avoiding the unnecessary suffering of pain of biopsy in all patients, and reducing the pressure on both patients and physicians. The findings of this study is expected to enable breast imaging reporting and data system grading detection to exert a better effect.

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