Correlation Between Ultrasound Imaging Features and Histopathological Findings in Differentiating Benign and Malignant Breast Masses

Abstract

Background: Breast cancer is a leading cause of morbidity and mortality worldwide, necessitating effective diagnostic techniques to differentiate benign and malignant breast masses. Objective: This study aims to assess the correlation between ultrasound imaging features and histopathological findings in differentiating benign and malignant breast masses. Methods: A total of 232 patients with suspected breast masses underwent both ultrasound and histopathological evaluation between January 2020 and December 2021 at the Department of Radiology & Imaging, Islami Bank Medical College Hospital. Ultrasound features, including lesion shape, margin, echogenicity, and vascularity, were recorded and compared with histopathological findings using statistical analysis. Sensitivity, specificity, and diagnostic accuracy were calculated, and a p-value of <0.05 was considered statistically significant. Results: Of the 232 patients, 145 had malignant masses (62.5%), and 87 had benign lesions (37.5%). The sensitivity of ultrasound for detecting malignant masses was 90.3%, and the specificity was 82.1%. The positive predictive value (PPV) was 88.5%, while the negative predictive value (NPV) was 85.2%. The standard deviation (SD) for lesion size measurement by ultrasound was 1.5 mm (mean size 25.3 mm), and for vascularity analysis, it was 2.1 mm (mean vascularity score 3.8). Further, the standard deviation for the echogenicity of malignant masses was found to be 0.75 (mean score 1.9), indicating a moderate range of variability in feature assessments. The p-value of 0.02 indicated that the correlation between ultrasound features and histopathology was statistically significant. Additionally, lesion size (SD = 1.4 mm) correlated with the degree of malignancy, where malignant masses showed a higher mean size compared to benign lesions (mean size 22.3 mm with SD = 1.3 mm). Conclusion: Ultrasound imaging features are highly correlated with histopathological findings in differentiating malignant from benign breast masses, providing a reliable, non-invasive diagnostic tool with high sensitivity and specificity.