Evaluation of Background Parenchymal Enhancement and Histogram-Based Diffusion-Weighted Image in Determining the Molecular Subtype of Breast Cancer.

Abstract

This study aimed to evaluate the value of background parenchymal enhancement (BPE) and diffusion-weighted image (DWI) histogram features in differentiating among different molecular subtypes of breast cancers and investigate the relationship between BPE and DWI features. We prospectively enrolled 142 patients with breast cancer between January and November 2018. All patients underwent breast magnetic resonance imaging before core needle biopsy. The quantitative BPE from dynamic enhanced images and the first-order histogram features extracted from DWI were analyzed. Univariate analysis of variance was used to compare differences in DWI histogram features and BPE characteristics among different molecular subtypes. Spearman test was used to compare the correlation between these imaging indexes. A total of 142 patients had 142 lesions, including 17 cases of triple-negative breast cancer, 12 cases of luminal A type breast cancer, 39 cases of luminal B type breast cancer, and 74 cases of human epidermal growth factor receptor 2-positive breast cancer. The apparent diffusion coefficient (ADC) 95th percentile, ADC kurtosis, and BPE were significantly different among 4 subtype groups (P < 0.05), especially between the triple-negative subtype and any other subtype (P < 0.05 in pairwise comparisons). There was a weak but significant correlation between BPE and kurtosis of ADC (r = -0.176, P = 0.036). Diffusion-weighted image histogram features (95th percentile ADC value and kurtosis value of ADC) and BPE features were different in the 4 molecular subtypes of breast cancer, especially in the triple-negative breast cancer subtype. Background parenchymal enhancement was negatively correlated with the kurtosis value of ADC.