A prospective observational study assessing the correlation between ultrasonography features and histopathological findings in breast cancer
DOI:
https://doi.org/10.18203/2349-2902.isj20253017Keywords:
Breast cancer, BI-RADS, Histopathology, UltrasonographyAbstract
Background: Breast cancer is the most commonly diagnosed malignancy in India, where early detection is crucial for improving survival. Ultrasonography (USG) is a widely available imaging tool, especially beneficial in resource-limited settings and among younger women with dense breasts. This research sought to examine the association between sonographic features and histopathological findings in breast cancer patients.
Methods: A prospective observational study was conducted from May 2024 to April 2025 at Dr. R.P.G.M.C. Kangra, Himachal Pradesh, involving 50 female patients with clinically suspected breast malignancies. All participants underwent standardized breast ultrasonography, followed by histopathological confirmation through fine-needle aspiration cytology (FNAC) or core biopsy. Lesions were evaluated for shape, margins, echogenicity, posterior acoustic features and BI-RADS classification. The association between imaging findings and histopathological results was statistically analyzed.
Results: The mean age among patients was 47.56 years, with painless breast lumps noted as the initial symptom in all individuals. Common ultrasonographic findings included hypo echogenicity (82%), irregular margins (78%), posterior acoustic shadowing (70%) and a taller-than-wide shape (66%). Histopathology confirmed cancer in (96%) of the cases, with invasive ductal carcinoma observed in (85.4%) of these instances. A statistically significant correlation was found between ultrasonographic features and histopathological diagnosis (p < 0.05). USG demonstrated a sensitivity of 91.6%, specificity of 85.7% and diagnostic accuracy of 85%.
Conclusions: Ultrasonography is a reliable, accessible and effective imaging modality for evaluating breast lesions, with strong diagnostic utility in resource-constrained healthcare environments.
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References
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