A Decision Support System Based on BI-RADS and Radiomic Classifiers to Reduce False Positive Breast Calcifications at Digital Breast Tomosynthesis: A Preliminary Study

Abstract

Digital breast tomosynthesis (DBT) studies were introduced as a successful help for the detection of calcification, which can be a primary sign of cancer. Expert radiologists are able to detect suspicious calcifications in DBT, but a high number of calcifications with non-malignant diagnosis at biopsy have been reported (false positives, FP). In this study, a radiomic approach was developed and applied on DBT images with the aim to reduce the number of benign calcifications addressed to biopsy and to give the radiologists a helpful decision support system during their diagnostic activity. This allows personalizing patient management on the basis of personalized risk. For this purpose, 49 patients showing microcalcifications on DBT images were retrospectively included, classified by BI-RADS (Breast Imaging-Reporting and Data System) and analyzed. After segmentation of microcalcifications from DBT images, radiomic features were extracted. Features were then selected with respect to their stability within different segmentations and their repeatability in test–retest studies. Stable radiomic features were used to train, validate and test (nested 10-fold cross-validation) a preliminary machine learning radiomic classifier that, combined with BI-RADS classification, allowed a reduction in FP of a factor of 2 and an improvement in positive predictive value of 50%.

Machine learning and new insights for breast cancer diagnosis

“…28 This current review extracted and organized the data in tabular form and summarized the use of MG in the diagnosis of breast cancer (Table 1). 2,4,5,7,9,24,29–79…”

Radiomics Based on Digital Mammography Helps to Identify Mammographic Masses Suspicious for Cancer

“…In the fifth edition of the BI-RADS atlas (3), category 4 and 5 breast lesions are defined as suspicious cancerous lesions, and a biopsy is recommended for further diagnosis. Recent studies have shown that a large number of benign lesions are present in category 4 and 5 breast lesions, particularly in the mammography reporting system, exposing these patients to invasive biopsies (4)(5)(6). Depending on the technique, the sensitivity values of biopsy results ranged from 87% to >97% (7)(8)(9).…”