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Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?

机译:用于放射组学特征稳定性分析的重测数据:可通用还是特定于研究?

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摘要

Radiomics is an objective method for extracting quantitative information from medical images. However, in radiomics, standardization, overfitting, and generalization are major challenges to be overcome. Test–retest experiments can be used to select robust radiomic features that have minimal variation. Currently, it is unknown whether they should be identified for each disease (disease specific) or are only imaging device-specific (computed tomography [CT]-specific). Here, we performed a test–retest analysis on CT scans of 40 patients with rectal cancer in a clinical setting. Correlation between radiomic features was assessed using the concordance correlation coefficient (CCC). In total, only 9/542 features have a CCC > 0.85. Furthermore, results were compared with the test–retest results on CT scans of 27 patients with lung cancer with a 15-minute interval. Results show that 446/542 features have a higher CCC for the test–retest analysis of the data set of patients with lung cancer than for patients with rectal cancer. The importance of controlling factors such as scanners, imaging protocol, reconstruction methods, and time points in a radiomics analysis is shown. Moreover, the results imply that test–retest analyses should be performed before each radiomics study. More research is required to independently evaluate the effect of each factor.
机译:放射线学是一种从医学图像中提取定量信息的客观方法。然而,在放射学中,标准化,过度拟合和泛化是需要克服的主要挑战。重新测试实验可用于选择变化最小的健壮放射学特征。目前,尚不清楚是针对每种疾病(疾病特异性)还是仅针对成像设备(计算机断层扫描[CT]特异性)进行识别。在这里,我们对40例临床直肠癌患者的CT扫描进行了测试-再测试分析。使用一致性相关系数(CCC)评估放射特征之间的相关性。总共只有9/542个功能的CCC> 0.85。此外,将结果与间隔15分钟的27例肺癌患者的CT扫描重测结果进行了比较。结果表明,对于肺癌患者的数据集进行再测试分析,446/542特征具有比直肠癌患者更高的CCC。显示了在放射分析中控制诸如扫描仪,成像协议,重建方法和时间点等因素的重要性。此外,结果暗示应在每次放射学研究之前进行重新测试分析。需要更多研究来独立评估每个因素的影响。

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