Comparing Low and High-Temporal Resolution DCE-MRI Texture Analysis for Discrimination of Breast Lesions from Background Enhancement

Abstract Background Breast cancer is the most common cancer in women worldwide, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) can better evaluate the tissue microenvironment and texture characteristics. The purpose of this study was to investigate the value of the texture-based analysis for breast DCE-MRI in the diagnosis of breast lesions and background enhancement. Methods This study prospectively enrolled 128 patients with clinically suspected breast lesions in our hospital from April 2015 to June 2017. Among them, 62 patients underwent preoperative high temporal resolution DCE-MRI (1 + 26 phases) scan with 39 malignant and 23 benign lesions. The control group retrospectively and randomly contained 78 patients who underwent preoperative low temporal resolution DCE-MRI (1 + 5 phases) scans with 46 malignant and 32 benign lesions. Quantitative parameters were obtained using a two-compartment Extended Tofts and volume of interest model for the lesion center, surrounding peripheral area and background enhancement, including pharmacokinetic parameters (Ktrans, Kep, Ve and Vp) and texture features based on the Ktrans map. The Student’s t-test was used to compare the differences of means. LASSO was used for dimension reduction and logistic regression analysis was used for model construction. A receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance. Results Pharmacokinetic parameters were significantly different between high temporal resolution and low temporal resolution DCE-MRI (P < 0.05). In the malignant group, the average Ktrans of the lesion area on high temporal resolution DCE-MRI was significantly correlated to the pathological grading (r = 0.400, P = 0.012). In the differentiation between benign and malignant lesions, the ROC analysis demonstrated that the diagnostic value of high temporal resolution DCE-MRI offered slightly significant advantages in the realms of the lesion, peripheral areas and background enhancement. Conclusions The use of texture analysis based on high temporal resolution DCE-MRI may potentially improve breast cancer diagnostic performance. Specifically, combining the lesion, peripheral, BE area, and Ktrans-mean parameters can contribute to the diagnosis of breast lesions, background enhancement and the pathological grading of malignant tumors.