Ki-67
磁共振成像
峰度
相关性
乳腺癌
直方图
增殖指数
医学
病理
癌症
放射科
免疫组织化学
数学
人工智能
内科学
计算机科学
统计
几何学
图像(数学)
作者
Ma‐Wen Juan,Yu Ji,Guo‐Xin Peng,Liu‐Jun Jun,Sun‐Peng Feng,Liu‐Pei Fang
出处
期刊:Oncology Letters
[Spandidos Publications]
日期:2018-08-06
卷期号:16 (4): 5084-5090
被引量:44
摘要
The aim of the present study was to investigate the association between Ki-67 expression and radiomics features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in patients with invasive breast cancer. A total of 53 cases with low-Ki-67 expression (Ki-67 proliferation index <14%) and 106 cases with high-Ki-67 expression (Ki-67 proliferation index >14%) were investigated. A systematic approach was applied that focused on the automated segmentation of lesions and extraction of radiomics features. For each lesion 5 morphology, 4 gray-scale histogram and 6 texture features were obtained, and statistical analyzes were performed to assess the differences in these features between the low- and high-Ki-67 expressions. One morphology metric (area), 3 gray-scale histogram indexes (standard deviation, skewness and kurtosis) and 3 texture features (contrast, homogeneity and inverse differential moment) demonstrated a significant difference (P<0.05), with low-Ki-67 expression lesions tending to be smaller, clearer and heterogeneous when compared with the high-Ki-67 expressed cases. These results may provide a noninvasive means to better understand the proliferation of breast cancer.
科研通智能强力驱动
Strongly Powered by AbleSci AI