OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.
Sci Rep. 2019 Jan 24;9(1):614. doi: 10.1038/s41598-018-36938-4.
Image features need to be robust against differences in positioning, acquisition and segmentation to ensure reproducibility. Radiomic models that only include robust features can be used to analyse new images, whereas models with non-robust features may fail to predict the outcome of interest accurately. Test-retest imaging is recommended to assess robustness, but may not be available for the phenotype of interest. We therefore investigated 18 combinations of image perturbations to determine feature robustness, based on noise addition (N), translation (T), rotation (R), volume growth/shrinkage (V) and supervoxel-based contour randomisation (C). Test-retest and perturbation robustness were compared for combined total of 4032 morphological, statistical and texture features that were computed from the gross tumour volume in two cohorts with computed tomography imaging: I) 31 non-small-cell lung cancer (NSCLC) patients; II): 19 head-and-neck squamous cell carcinoma (HNSCC) patients. Robustness was determined using the 95% confidence interval (CI) of the intraclass correlation coefficient (1, 1). Features with CI ≥ 0:90 were considered robust. The NTCV, TCV, RNCV and RCV perturbation chain produced similar results and identified the fewest false positive robust features (NSCLC: 0.2-0.9%; HNSCC: 1.7-1.9%). Thus, these perturbation chains may be used as an alternative to test-retest imaging to assess feature robustness.
图像特征需要对定位、获取和分割的差异具有鲁棒性，以确保可重复性。仅包含稳健特征的放射组学模型可用于分析新图像，而具有非稳健特征的模型可能无法准确预测感兴趣的结果。建议进行测试-重测成像以评估稳健性，但对于感兴趣的表型可能不可用。因此，我们研究了 18 种图像扰动组合，以确定基于噪声添加（N）、平移（T）、旋转（R）、体积增长/收缩（V）和超体素轮廓随机化（C）的特征稳健性。对来自两个使用计算机断层扫描成像的队列的总共有 4032 个形态学、统计学和纹理特征进行了测试-重测和扰动稳健性比较：I）31 名非小细胞肺癌（NSCLC）患者；II）：19 名头颈部鳞状细胞癌（HNSCC）患者。稳健性是使用组内相关系数（1, 1）的 95%置信区间（CI）来确定的。CI≥0.90 的特征被认为是稳健的。NTCV、TCV、RNCV 和 RCV 扰动链产生了相似的结果，并确定了最少的假阳性稳健特征（NSCLC：0.2-0.9%；HNSCC：1.7-1.9%）。因此，这些扰动链可替代测试-重测成像来评估特征稳健性。
