Role of mammogram and ultrasound imaging in predicting breast cancer subtypes in screening and symptomatic patients

Abstract

BACKGROUND: Breast cancer (BC) radiogenomics, or correlation analysis of imaging features and BC molecular subtypes, can complement genetic analysis with less resource-intensive diagnostic methods to provide an early and accurate triage of BC. This is pertinent because BC is the most prevalent cancer amongst adult women, resulting in rising demands on public health resources. AIM: To find combinations of mammogram and ultrasound imaging features that predict BC molecular subtypes in a sample of screening and symptomatic patients. METHODS: a screening program. All the patients underwent mammography and ultrasound imaging prior to biopsy. The images were retrospectively read by two breast-imaging radiologists with 5-10 years of experience with no knowledge of the histology results to ensure statistical independence. To test the hypothesis that imaging features are correlated with tumor subtypes, univariate binomial and multinomial logistic regression models were performed. Our study also used the multivariate logistic regression (with and without interaction terms) to identify combinations of mammogram and ultrasound (US) imaging characteristics predictive of molecular subtypes. RESULTS: is characterized by small size on ultrasound, absence of posterior acoustic features, and architectural distortion on mammogram, while luminal subtypes tend to be small, with spiculated margins and posterior acoustic shadowing (Luminal A type). These results are broadly consistent with findings from prior studies. In addition, we also find that US size signals a higher odds ratio for TNBC if presented during screening. As TNBC tends to display sonographic features such as circumscribed margins and posterior enhancement, resulting in visual similarity with benign common lesions, at the screening stage, size may be a useful factor in deciding whether to recommend a biopsy. CONCLUSION: Several imaging features were shown to be independent variables predicting molecular subtypes of BC. Knowledge of such correlations could help clinicians stratify BC patients, possibly enabling earlier treatment or aiding in therapeutic decisions in countries where receptor testing is not readily available.

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