Reproducibility with repeat CT in radiomics study for rectal cancer.
Reproducibility with repeat CT in radiomics study for rectal cancer.
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DOI：
10.18632/oncotarget.12199
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发表时间：
2016-11-01
期刊：
影响因子：
--
通讯作者：
Zhang Z
中科院分区：
文献类型：
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作者：
Hu P;Wang J;Zhong H;Zhou Z;Shen L;Hu W;Zhang Z
通过重复计算机断层扫描（CT）评价直肠癌放射组学特征的可重复性。选择稳定的直肠癌放射组学特征。体积归一化特征比非归一化特征更可再现。所有切片的平均值是直肠癌中最可重复的特征类型。不同的滤波器对放射组学特征的再现性几乎没有影响。对于平均类型特征，775个特征中的496个表现出高再现性（ICC ≥ 0.8），775个特征中的225个表现出中等再现性（0.8 > ICC ≥ 0.5），775个特征中的54个表现出低再现性（ICC < 0.5）。40例II期直肠癌患者入组本研究，每位患者平均在8.7天内接受两次CT扫描。在这项研究中定义了775个放射组学特征。对于每个特征，提取五个不同的值（来自最大切片的值、最大值、最小值、所有切片的平均值和来自叠加中间矩阵的值）。同时，对这些图像应用具有不同参数的滤波器，以找到稳定的滤波值。根据原始特征和体积归一化特征计算两次CT扫描的一致性相关系数（CCC）和类间相关系数（ICC），以评估重复性。在放射组学分析中，建议将特征归一化为体积。平均型放射组学特征是直肠癌最稳定的特征。进一步分析直肠癌的这些特征可以保证治疗监测和预后预测。
To evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer. Volume normalized features are much more reproducible than unnormalized features. The average value of all slices is the most reproducible feature type in rectal cancer. Different filters have little effect for the reproducibility of radiomics features. For the average type features, 496 out of 775 features showed high reproducibility (ICC ≥ 0.8), 225 out of 775 features showed medium reproducibility (0.8 > ICC ≥ 0.5) and 54 out of 775 features showed low reproducibility (ICC < 0.5). 40 rectal cancer patients with stage II were enrolled in this study, each of whom underwent two CT scans within average 8.7 days. 775 radiomics features were defined in this study. For each features, five different values (value from the largest slice, maximum value, minimum value, average value of all slices and value from superposed intermediate matrix) were extracted. Meanwhile a LOG filter with different parameters was applied to these images to find stable filter value. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) of two CT scans were calculated to assess the reproducibility, based on original features and volume normalized features. Features are recommended to be normalized to volume in radiomics analysis. The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.