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

Abstract

PurposeTo assess whether perfusion and diffusion parameters were different between low-risk tumors and non-low-risk tumors. Materials and MethodsWe prospectively enrolled 87 patients with 91 tumors patients (mean, 49.6years; 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. ResultsOn univariate analysis, wash-in and the initial area under the curve on qualitative analysis (iAUCqualitative) were significantly different according to HG, ER, HER-2, Ki67 and lymphovascular invasion (P<.05 for all variables). ADCdiff was significantly different according to HG, HER-2, and Ki67 status (P=.010, .007, and .013). On multivariate analysis, Ktrans, iAUCqualitative, and ADCdiff 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. ADCdiff was positively correlated with wash-in (r=0.263) and iAUCqualitative (r=0.245), respectively. ConclusionThe prediction model using Ktrans, wash in, iAUCqualitative, and ADCdiff 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.