Department of General Surgery, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Sawangi, Meghe, Wardha, India
Department of General Surgery, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Sawangi, Meghe, Wardha, India
Breast cancer remains a leading cause of morbidity and mortality among women worldwide. Early detection and accurate characterization of palpable breast lumps are critical for timely intervention and improved outcomes. Imaging techniques, including mammography and magnetic resonance imaging (MRI), are integral to breast lump evaluation; however, sonomammography has emerged as a pivotal diagnostic tool, especially in women with dense breast tissue and younger age groups. This narrative review explores the role of sonomammograms in the early detection and characterization of palpable breast lumps, emphasizing their clinical utility, strengths, and limitations. Sonomammography, a combination of ultrasound and mammographic evaluation, offers superior sensitivity in distinguishing benign from malignant breast lesions. Key sonographic features, such as lesion margins, shape, echogenicity, and vascularity, assist in the precise categorization of lumps on the basis of Breast Imaging Reporting and Data System (BI-RADS) criteria. Additionally, the technique excels in differentiating cystic from solid lesions and provides complementary information to physical examination and mammography, particularly in challenging cases. The review also highlights advances in sonographic technology, including elastography and artificial intelligence, which promise to further enhance diagnostic accuracy. Despite its advantages, limitations such as operator dependency and reduced sensitivity for microcalcifications underscore the need for multimodal approaches in breast imaging. Overall, sonomammography represents a noninvasive, cost-effective, and widely accessible modality for the early detection and detailed characterization of palpable breast lumps. Its integration into clinical practice offers significant potential for optimizing diagnostic pathways and improving patient outcomes.
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