Prediction of low-risk breast cancer using perfusion parameters and apparent diffusion coefficient

Purpose: To assess whether perfusion and diffusion parameters were different between low-risk tumors and non-low-risk tumors. Materials and Methods: We prospectively enrolled 87 patients with 91 tumors patients (mean, 49.6 years; range, 29-74 years) who underwent definitive surgery. We defined estrogen receptor (ER)-positive tumors with low histologic grade (HG), low Ki67 (<14%), and negative lymph node metastasis as a low-risk breast cancer. We obtained quantitative and semiquantitative perfusion parameters and apparent diffusion coefficient (ADC) for all tumors. We compared perfusion parameters and ADCs between low-risk tumors (n = 33; 36%) and the others (n = 58; 64%) using Fisher's exact test, Chi-square test, and student t-test. We developed empirical model to predict low-risk tumor using logistic regression analysis and receiver operating characteristics (ROC) analysis. Results: On univariate analysis, wash-in and the initial area under the curve on qualitative analysis (iAUC(qualitative)) were significantly different according to HG, ER, HER-2, Ki67 and lymphovascular invasion (P < .05 for all variables). ADC(diff) was significantly different according to HG, HER-2, and 1067 status (P = .010, .007, and .013). On multivariate analysis, K-trans, iAUC(qualitative), and ADC(diff) were the significant variables for the prediction of low-risk tumors, and the area under the ROC curve (AUC) of combined parameters was 0.78, which was higher than those of the individual parameter. ADC(diff) was positively correlated with wash-in (r = 0.263) and iAUC(qualitative) (r = 0.245), respectively. Conclusion: The prediction model using K-trans, wash in, iAUC(qualitative), and ADC(diff) on DCE-MRI and DWI could be helpful for identifying of low-risk breast cancer and may be used as an imaging biomarker to guide the treatment plan. (C) 2015 Elsevier Inc. All rights reserved.