Whole Volume Apparent Diffusion Coefficient (ADC) Histogram as a Quantitative Imaging Biomarker to Differentiate Breast Lesions: Correlation with the Ki-67 Proliferation Index

• Main Authors: Yuan Guo, Qing-cong Kong, Li-qi Li, Wen-jie Tang, Wan-li Zhang, Guan-yuan Ning, Jun Xue, Qian-wei Zhou, Ying-ying Liang, Mei Wu, Xin-qing Jiang
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: BioMed Research International
• Online Access: http://dx.doi.org/10.1155/2021/4970265

Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age (P<0.001) and lesion size (P=0.006) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P<0.001). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P=0.001) and estrogen receptor (ER)/progesterone receptor (PR) status (P=0.020 and P=0.041, respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group (Ki−67<14%) and 70 tumours in the high-proliferation group (Ki−67≥14) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status (P=0.007 and P<0.001, respectively), and there were weak correlations between ADC entropy (r=0.383) and skewness (r=0.209) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.