Abstract
Purpose: To determine the independent risk factors associated with malignant nonspiculate and noncalcified masses (NSNCMs) and evaluate the predictive values of extratumoral structural abnormalities on digital mammography. Methods: A total of 435 patients were included between January and May 2018. Tumor signs included shape, density, and margin, which were evaluated. Extratumoral signs were classified into extratumoral structural abnormalities (parenchymal and trabecular) and halo; subclassification included contraction, distortion, pushing and atrophy sign of parenchyma, parallel, vertical, and reticular trabecula sign, and narrow and wide halo. Univariate and multivariate analysis was performed. The positive predictive value (PPV) of the independent predictor was calculated, and diagnostic performance was evaluated using the receiver operating characteristic curve. Results: Of all cases, 243 (55.8%) were benign and 192 (44.2%) were malignant. Extratumoral contraction sign of parenchyma was the strongest independent predictor of malignancy (odds ratio [OR] 36.2, p < 0.001; PPV = 96.6%), followed by parenchymal distortion sign (OR 10.2, p < 0.001; PPV = 92%), parallel trabecula sign (OR 7.2, p < 0.001; PPV = 85.6%), and indistinct margin of tumor (OR 4.3, p < 0.001; PPV =70.9%), and also parenchymal atrophy sign, wide halo, vertical trabecula, age ≥ 47.5 years, irregular shape, and size ≥ 22.5 mm of tumor (OR range, 1.3-4.0; PPV range, 56.6-83.6%). The diagnostic performance of most of the extratumoral signs was between that of indistinct margin and irregular shape of tumor. Conclusion: The subclassification of extratumoral structural abnormalities has important predictive value for mammographic malignant NSNCM, which should be given more attention.
Highlights
Breast cancer remains a global public health problem (Masood and Rosa, 2011)
Digital mammography descriptors include shape, density, and margin according to the Breast Imaging Data and Reporting System (BI-RADS), which are further classified in detail (Fischer et al, 2006; Zeeshan et al, 2018)
Spiculate mass is more likely to be evaluated as malignancy because of its very high positive predictive value (Burrell et al, 1996; Liberman et al, 1998)
Summary
Breast cancer remains a global public health problem (Masood and Rosa, 2011). The incidence of breast cancer in Chinese women continues to rise (Bai et al, 2020). Digital mammography is one of the important imaging tools for breast cancer screening and diagnosis (Fischer et al, 2006; Zeeshan et al, 2018). Mass is the most common imaging manifestation of breast cancer and the main sign of benign disease. Digital mammography descriptors include shape, density, and margin according to the Breast Imaging Data and Reporting System (BI-RADS), which are further classified in detail (Fischer et al, 2006; Zeeshan et al, 2018). Calcifications may be associated with mass, and the type of calcification will increase radiologists’ confidence in evaluating mass. We are interested in these types of masses because more attention is often required to consider malignant possibility
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