Imaging of Breast Lesions Using Conventional Magnetic Resonance Imaging and Diffusion Weighted Imaging

Abstract

CONTEXT: Breast cancer is the second most common cancer in the world, and the second most common in cancer in Indian women. AIMS: The aims of this study were to differentiate between benign and malignant lesions using Diffusion Weighted Imaging, T2-weighted and T1-weighted imaging, and to set a cut off value of ADC to differentiate between benign and malignant lesions. MATERIALS AND METHODS: It included 51 patients between the ages of 15 and 75 years, coming to surgical OPD, Government Medical College, Kozhikode with USG/Mammogram proven breast lesions from January 2013 to September 2014. Non contrast MR Mammography was done using 1.5 T MR system. T1WI, T2WI and Diffusion weighted imaging (b= 0, 600) were done and ADC values were calculated for all the lesions. Validity parameters were assessed for each sequence and a combination of all the sequences. ROC curve was plotted and ADC cut off was chosen with a high sensitivity and specificity. RESULTS: Twenty nine lesions were categorized as benign and twenty two lesions were categorized as malignant based on the T1, T2 and DWI. By histopathological examination of these lesions, 2 lesions characterised as malignant turned out to be benign.T1WI was not found to be helpful in differentiating between benign and malignant lesions, whereas 95% of malignant lesions appeared either intermediate signal (90%) or hypointense (5%) in T2WI, conferring a sensitivity of 90.5% and specificity of 80.6% in detection of malignant lesions using T2WI. Applying an ADC threshold of 1.255×10 −3 mm2/s benign and malignant lesions could be differentiated with 100% sensitivity and 93.5% specificity, with a PPV of 90.9% and NPV of 100%. Mean ADC value of malignant lesions was found to be 1.13±0.007 mm 2 /s. CONCLUSION: Non contrast MRI using T2WI and DWI is a useful technique for characterizing breast lesions. It is also useful in the follow up of post lumpectomy irradiated breast to detect recurrence.