Abstract
Improving the assessment of breast imaging reporting and data system (BI-RADS) 4 lesions and reducing unnecessary biopsies are urgent clinical issues. In this prospective study, a radiomic nomogram based on the automated breast volume scanner (ABVS) was constructed to identify benign and malignant BI-RADS 4 lesions and evaluate its value in reducing unnecessary biopsies. A total of 223 histologically confirmed BI-RADS 4 lesions were enrolled and assigned to the training and validation cohorts. A radiomic score was generated from the axial, sagittal, and coronal ABVS images. Combining the radiomic score and clinical-ultrasound factors, a radiomic nomogram was developed by multivariate logistic regression analysis. The nomogram integrating the radiomic score, lesion size, and BI-RADS 4 subcategories showed good discrimination between malignant and benign BI-RADS 4 lesions in the training (AUC, 0.959) and validation (AUC, 0.925) cohorts. Moreover, 42.5% of unnecessary biopsies would be reduced by using the nomogram, but nine (4%) malignant BI-RADS 4 lesions were unfortunately missed, of which 4A (77.8%) and small-sized (<10 mm) lesions (66.7%) accounted for the majority. The ABVS radiomics nomogram may be a potential tool to reduce unnecessary biopsies of BI-RADS 4 lesions, but its ability to detect small BI-RADS 4A lesions needs to be improved.
Highlights
Breast cancer is still the most common malignant tumor and the leading cause of cancer-related death in females [1]
Breast lesions detected by US can be classified into seven categories according to the fifth edition of the Breast Imaging Reporting and Data System (BI-RADS) [4]
For bridging the gap and taking full use of automated breast volume scanner (ABVS) images to promote precision medicine, this prospective study aimed to investigate the ability of the ABVS radiomic nomogram to distinguish benign and malignant BI-RADS 4 lesions, and evaluate its potential value in reducing unnecessary biopsies of these lesions
Summary
Breast cancer is still the most common malignant tumor and the leading cause of cancer-related death in females [1]. A noninvasive, quantitative and objective image analysis method named radiomic nomogram has attracted attention. It can extract high-throughput quantitative features that may not be observed directly by the naked eye from single or multiple medical images, and subsequently combine these features with clinical information to improve disease diagnosis and prognostic evaluation [11]. To our knowledge, whether ABVSbased radiomic nomogram has potential to identify benign and malignant breast lesions, especially BI-RADS 4 lesions, remains unknown. For bridging the gap and taking full use of ABVS images to promote precision medicine, this prospective study aimed to investigate the ability of the ABVS radiomic nomogram to distinguish benign and malignant BI-RADS 4 lesions, and evaluate its potential value in reducing unnecessary biopsies of these lesions
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