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 (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. CONCLUSION The 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.
Magnetic resonance imaging