Diffusion weighted imaging in breast cancer – Can it be a noninvasive predictor of nuclear grade?

Abstract

Background: DWI and ADC values are noninvasive MRI techniques, which provide quantitative information about tumor heterogeneity. Aim: To determine the minimum and mean ADC values in breast carcinoma and to correlate ADC values with various prognostic factors. Settings and Design: Prospective observational study. Materials and Methods: Fifty-five patients with biopsy-proven breast carcinoma were included in this study. MRI with DWI was performed with Siemens 3T Skyra scanner. ADC values were measured by placing regions of interest (ROIs) within the targeted lesions on ADC maps manually. The histopathological and immunohistochemical analysis of surgical specimen was done to determine the prognostic factors. Statistical Analysis: Students T test and ANOVA were used to study the difference in ADC between two groups. Pearson correlation coefficient was used to quantify the correlation between ADC values and prognostic factors. Results: Lower grade (grade I) breast carcinoma had a significantly high ADC value as compared to higher grade carcinoma (grade II and III). For differentiating Grade I tumors from grade II and III, a minimum ADC cut-off value was 0.79 × 10−3 mm2/sec (83% sensitivity and 84% specificity) and a mean ADC cut-off value was 0.82 × 10-3 mm2/sec (83% sensitivity and 71% specificity) was derived. There was no significant correlation between ADC and other prognostic factors. Conclusion: ADC values can be used to differentiate lower grade breast carcinoma (grade I) from higher grades (grade II and III). Minimum ADC values are more accurate in predicting the grade of the breast tumor than mean ADC value.

Keywords

• breast cancer
• diffusion
• imaging
• predictor
• prognosis