Predicting Malignancy of Breast Imaging Findings Using Quantitative Analysis of Contrast-Enhanced Mammography (CEM).

ABSTRACT: We sought to develop new quantitative approaches to characterize the spatial distribution of mammographic density and contrast enhancement of suspicious contrast-enhanced mammography (CEM) findings to improve malignant vs. benign classifications of breast lesions. We retrospectively analyzed all breast lesions that underwent CEM imaging and tissue sampling at our institution from 2014-2020 in this IRB-approved study. A penalized linear discriminant analysis was used to classify lesions based on the averaged histograms of radial distributions of mammographic density and contrast enhancement. T-tests were used to compare the classification accuracies of density, contrast, and concatenated density and contrast histograms. Logistic regression and AUC-ROC analyses were used to assess if adding

SUBMITTER: Miller MM 

PROVIDER: S-EPMC10047016 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature