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Diagnostic Accuracy of Ultrasonography in Differentiating Benign and Malignant Breast Masses with Histopathological Correlation

Year: 2025
Type: article
Abstract: Introduction: Breast cancer remains the most common malignancy in women worldwide, with a rise in incidence in younger populations. Early and accurate diagnosis is critical for the improvement of outcomes. Ultrasonography (USG), a non-surgical modality with extensive availability, is a useful technique in assessing breast masses, albeit histopathology being the gold standard. Objectives: The aim of this study was to assess the diagnostic accuracy of ultrasonography in differentiating between benign and malignant breast lesions by histopathological correlation. Methods & Materials: This cross-sectional observational study was conducted in the Department of Radiology and Imaging, Community Based Medical College Bangladesh, Mymensingh, Bangladesh Jan 2020 to Dec 2020. Total 116 patients who presented with palpable or clinically suspected breast masses and were referred for ultrasonography were included in the study. Results: The age of the patient was on average 36.5 ± 12.6 years, with most cases falling in the 35–44 years age group. Histopathology confirmed 60.3% benign and 39.7% malignant lesions. Ultrasonographic BI-RADS classification placed 47.6% of the lesions in suspicious or malignant categories (BI-RADS 4 and 5). Compared with histopathology, ultrasonography correctly diagnosed 42 out of 46 malignant and 62 out of 70 benign lesions, with statistically significant correlation (p < 0.001). Diagnostic accuracy was 91.3% sensitive, 88.6% specific, 84.0% PPV, 93.9% NPV, and 89.7% overall accuracy. Conclusion: Ultrasonography is very accurate in diagnosis and correlates well with histopathology in the evaluation of breast masses, warranting its status as a useful diagnostic modality in practice.
Source: The Insight
DOI: 10.5281/zenodo.17380303
Authors: Mukthadira, Rahman, Meher Angez
Language: English
Field: Medicine
Open Access status: diamond
OpenAlex ID: W7092289057
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