The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, China.
Department of Radiology, Guangzhou First People's Hospital, South China University of Technology, Guangzhou 510180, China.
Biomed Res Int. 2021 Jun 24;2021:4970265. doi: 10.1155/2021/4970265. eCollection 2021.
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.
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.
Of the 189 breast lesions included, there were significant differences in patient age ( < 0.001) and lesion size ( = 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 < 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 = 0.001) and estrogen receptor (ER)/progesterone receptor (PR) status ( = 0.020 and = 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 ( = 0.007 and < 0.001, respectively), and there were weak correlations between ADC entropy ( = 0.383) and skewness ( = 0.209) and the Ki-67 index.
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.
评估全容积表观扩散系数(ADC)直方图在鉴别良恶性乳腺病变以及区分不同分子亚型乳腺癌方面的价值,并评估 ADC 直方图参数与乳腺癌中 Ki-67 表达之间的相关性。
本回顾性研究获得机构审查委员会批准。2016 年 9 月至 2019 年 2 月,189 例患者(84 例良性病变和 105 例乳腺癌)接受了磁共振成像(MRI)检查。通过在整个病变上放置感兴趣区(ROI)来创建容积 ADC 直方图。使用 Spearman 相关分析来分析 ADC 参数与 Ki-67 之间的关系。
在纳入的 189 个乳腺病变中,良性和恶性病变之间的患者年龄(<0.001)和病变大小(=0.006)存在显著差异。结果还表明,良性和恶性病变之间的所有 ADC 直方图参数均存在显著差异(均<0.001)。中位数和平均值 ADC 直方图参数的表现优于其他 ADC 直方图参数(AUC 分别为 0.943 和 0.930)。受试者工作特征(ROC)分析显示,第 10 百分位数 ADC 值和熵可以确定人表皮生长因子受体 2(HER-2)状态(均=0.001)和雌激素受体(ER)/孕激素受体(PR)状态(=0.020 和=0.041)。在所有乳腺癌病变中,分析了 35 个低增殖组(Ki-67<14%)和 70 个高增殖组(Ki-67≥14%)的肿瘤,绘制 ROC 曲线并进行相关分析。ROC 分析显示,熵和偏度可以确定 Ki-67 状态(=0.007 和<0.001),ADC 熵(=0.383)和偏度(=0.209)与 Ki-67 指数之间存在弱相关性。
容积 ADC 直方图可用作确定乳腺病变特征的影像学标志物,并且可能是预测乳腺癌肿瘤增殖的辅助方法。