This study aims to evaluate the repeatability of radiomics and dosiomics features via image perturbation of patients with cervical cancer. A total of 304 cervical cancer patients with planning CT images and dose maps were retrospectively included. Random translation, rotation, and contour randomization were applied to CT images and dose maps before radiomics feature extraction. The repeatability of radiomics and dosiomics features was assessed using intra-class correlation of coefficient (ICC). Pearson correlation coefficient (r) was adopted to quantify the correlation between the image characteristics and feature repeatability. In general, the repeatability of dosiomics features was lower compared with CT radiomics features, especially after small-sigma Laplacian-of-Gaussian (LoG) and wavelet filtering. More repeatable features (ICC > 0.9) were observed when extracted from the original, Large-sigma LoG filtered, and LLL-/LLH-wavelet filtered images. Positive correlations were found between image entropy and high-repeatable feature number in both CT and dose (r = 0.56, 0.68). Radiomics features showed higher repeatability compared to dosiomics features. These findings highlight the potential of radiomics features for robust quantitative imaging analysis in cervical cancer patients, while suggesting the need for further refinement of dosiomics approaches to enhance their repeatability.
本研究旨在通过图像扰动评估宫颈癌患者影像组学与剂量组学特征的可重复性。回顾性纳入304例具有计划CT图像和剂量分布图的宫颈癌患者。在提取影像组学特征前，对CT图像和剂量图施加随机平移、旋转及轮廓随机化处理。采用组内相关系数评估影像组学与剂量组学特征的可重复性，并通过皮尔逊相关系数量化图像特性与特征可重复性之间的关联。总体而言，剂量组学特征的可重复性低于CT影像组学特征，尤其在经过小尺度拉普拉斯高斯滤波和小波滤波处理后更为明显。从原始图像、大尺度拉普拉斯高斯滤波图像及LLL/LLH小波滤波图像中提取的特征表现出更高的可重复性。CT图像与剂量图的熵值均与高可重复性特征数量呈正相关。影像组学特征较剂量组学特征具有更高的可重复性。这些发现凸显了影像组学特征在宫颈癌患者定量影像分析中的稳健性潜力，同时提示需要进一步优化剂量组学方法以提升其可重复性。
肿瘤(癌症)患者之家