Original Articles
Role of MRI in non mass enhancing lesions in breast | |
Dr. Paresh Kumar Sukhani P, Dr. Neerja Meena, Dr. Nirmala Kalwaniya, Dr. Jai Chowdhary | |
Breast cancer is the most prevalent cancer among women worldwide, with an incidence rate of approximately 12%. Accurate diagnosis of breast lesions requires a combination of clinical evaluation, radiological imaging, and pathological analysis. Among imaging modalities, breast MRI is recognized for its high sensitivity in detecting breast abnormalities, particularly in high-risk populations. Diffusion-weighted imaging (DWI), which measures water molecule diffusion through apparent diffusion coefficient (ADC) values, has emerged as a valuable tool for differentiating benign and malignant lesions. This hospital-based, prospective, cross-sectional study was conducted at Mahatma Gandhi Medical College and Hospital, Jaipur, India, to assess the radiological characteristics of non-mass enhancing (NME) breast lesions using MRI and to determine their correlation with histopathological findings. A total of 69 patients were included in the study, with MRI findings categorized using BI-RADS descriptors. Biopsy samples were obtained for definitive diagnosis. Findings revealed that MRI exhibited high sensitivity (97.22%) and specificity (90.91%) in detecting malignant lesions. The mean ADC value of benign lesions (1.44±0.27) was significantly higher than that of malignant lesions (1.00±0.31) (p<0.05). NME lesions with linear, regional, or segmental distribution and heterogeneous or clumped internal enhancement were significantly associated with malignancy (p<0.05). These findings underscore the potential of MRI in improving diagnostic accuracy and reducing unnecessary biopsies. In conclusion, integrating morphological features, enhancement patterns, and ADC values enhances the accuracy of breast lesion characterization. MRI, particularly DWI, proves to be a valuable non-invasive tool for assessing NME lesions, aiding in early and precise breast cancer diagnosis. Further multicentric studies with larger sample sizes are recommended to validate these findings. |
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