Wang Hao, Zhou Yongkang, Wang Xiao, Zhang Yin, Ma Chi, Liu Bo, Kong Qing, Yue Ning, Xu Zhiyong, Nie Ke
Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiaotong University, Shanghai, China.
Department of Radiation Oncology, Rutgers Cancer Institute of New Jersey, Rutgers-Robert Wood Johnson Medical School, New Brunswick, NJ, United States.
Front Oncol. 2021 Nov 17;11:773512. doi: 10.3389/fonc.2021.773512. eCollection 2021.
This study was conducted in order to determine the reproducibility and repeatability of cone-beam computed tomography (CBCT) radiomics features.
The first-, second-, and fifth-day CBCT images from 10 head and neck (H&N) cancer patients and 10 pelvic cancer patients were retrospectively collected for this study. Eighteen common radiomics features were extracted from the longitudinal CBCT images using two radiomics packages. The reproducibility of CBCT-derived radiomics features was assessed using the first-day image as input and compared across the two software packages. The site-specific intraclass correlation coefficient (ICC) was used to quantitatively assess the agreement between packages. The repeatability of CBCT-based radiomics features was evaluated by comparing the following days of CBCT to the first-day image and quantified using site-specific concordance correlation coefficient (CCC). Furthermore, the correlation with volume for all the features was assessed with linear regression and as correlation parameters.
The first-order histogram-based features such as skewness and entropy showed good agreement computed in either software package (ICCs ≥ 0.80), while the kurtosis measurements were consistent in H&N patients between the two software tools but not in pelvic cases. The ICCs for GLCM-based features showed good agreement (ICCs ≥ 0.80) between packages in both H&N and pelvic groups except for the GLCM-correction. The GLRLM-based texture features were overall less consistent as calculated by the two different software packages compared with the GLCM-based features. The CCC values of all first-order and second-order GLCM features (except GLCM-energy) were all above 0.80 from the 2-day part test-retest set, while the CCC values all dropped below the cutoff after 5-day treatment scans. All first-order histogram-based and GLCM-texture-based features were not highly correlated with volume, while two GLRLM features, in both H&N and pelvic cohorts, showed ≥0.8, meaning a high correlation with volume.
The reproducibility and repeatability of CBCT-based radiomics features were assessed and compared for the first time on both H&N and pelvic sites. There were overlaps of stable features in both disease sites, yet the overall stability of radiomics features may be disease-/protocol-specific and a function of time between scans.
本研究旨在确定锥形束计算机断层扫描(CBCT)影像组学特征的可重复性和重复性。
本研究回顾性收集了10例头颈(H&N)癌患者和10例盆腔癌患者第一天、第二天和第五天的CBCT图像。使用两个影像组学软件包从纵向CBCT图像中提取18个常见的影像组学特征。以第一天的图像作为输入,评估CBCT衍生影像组学特征的可重复性,并在两个软件包之间进行比较。使用特定部位的组内相关系数(ICC)定量评估软件包之间的一致性。通过将后续几天的CBCT与第一天的图像进行比较来评估基于CBCT的影像组学特征的重复性,并使用特定部位的一致性相关系数(CCC)进行量化。此外,使用线性回归和 作为相关参数评估所有特征与体积的相关性。
基于一阶直方图的特征,如偏度和熵,在任何一个软件包中计算时都显示出良好的一致性(ICC≥0.80),而峰度测量在两个软件工具之间的H&N患者中是一致的,但在盆腔病例中不一致。基于灰度共生矩阵(GLCM)的特征的ICC在H&N组和盆腔组的软件包之间显示出良好的一致性(ICC≥0.80),除了GLCM校正。与基于GLCM的特征相比,由两个不同软件包计算的基于灰度游程长度矩阵(GLRLM)的纹理特征总体上不太一致。来自2天部分重测集的所有一阶和二阶GLCM特征(除GLCM能量外)的CCC值均高于0.80,而在5天治疗扫描后,CCC值均降至临界值以下。所有基于一阶直方图和基于GLCM纹理的特征与体积均无高度相关性,而在H&N和盆腔队列中,两个GLRLM特征显示 ≥0.8,意味着与体积高度相关。
首次在H&N和盆腔部位评估和比较了基于CBCT的影像组学特征的可重复性和重复性。两个疾病部位都有稳定特征的重叠,但影像组学特征的总体稳定性可能因疾病/方案而异,并且是扫描之间时间的函数。