Analysis of the application value of BI-RADS classification grading diagnosis based on imaging examinations for predicting atypical breast ductal hyperplasia and breast cancer

Background: To investigate the application value of Breast Imaging Reporting and Data System (BI-RADS) classification grading diagnosis based on breast ultrasound, molybdenum target radiography mammography and MRI imaging for predicting atypicalbreast ductal hyperplasia (ADH) and breast cancer (BC).Materials and Methods: Retrospective analysis of patients who visited the Department of Mammary Gynecology and Obstetrics of Nanjing Medical University for breast lumps between January 2015 and July 2021, based on the pathological findings of breast lumps, included 150 patients with benign breast usual ductal hyperplasia (UDH), 100 patients with atypical breast hyperplasia ADH, and 100 patients with breast cancer BC.The masses were evaluated and graded according to the fifth edition of the BI-RADS criteria, and the receiver operating characteristic (ROC) curves) were drawn based on ultrasound, molybdenum target radiography mammography, and MRI for BI-RADS grading to identify atypical hyperplasia (ADH) and breast cancer and the feasibility of the three imaging methods for predicting breast atypical hyperplasia ADH and breast cancer BC was compared.Results: The best cut-off value for breast ultrasound prediction of breast atypical hyperplasia ADH and breast cancer BC was BI-RADS grade 3 and the best cut-off value for molybdenum target radiography mammography and MRI prediction of breast atypical hyperplasia ADH and breast cancer BC was BI-RADS grade 4A, with corresponding area under the curve (AUC) of 0.691, 0.757, 0.866; the Jorden index was 0.363, 0.448, 0.662; the sensitivity was 56.30%, 48.20%, 71.20%; specificity 80.00%, 96.60%, 95.00%; positive predictive value 78.87%, 97.22%, 98.11%; negative predictive value 57.97%, 53.43%, 47.50%, respectively.Conclusion: BI-RADs classification grading diagnosis based on imaging examination has a high value in predicting breast dysplasia ADH and breast cancer BC.BI-RADs classification grading can be given priority in clinical prediction of breast dysplasia ADH and breast cancer BC to reduce unnecessary invasive examination.