Measuring Computed Tomography Scanner Variability of Radiomics Features.
Measuring Computed Tomography Scanner Variability of Radiomics Features.
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DOI：
10.1097/rli.0000000000000180
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发表时间：
2015-11
影响因子：
6.7
通讯作者：
Court L
中科院分区：
文献类型：
--
作者：
Mackin D;Fave X;Zhang L;Fried D;Yang J;Taylor B;Rodriguez-Rivera E;Dodge C;Jones AK;Court L
本研究的目的是确定CT图像放射组学研究中扫描仪间变异的意义。我们比较了20名患者的非小细胞肺癌（NSCLC）肿瘤的放射组学特征与17次专门设计的放射组学体模扫描的放射组学特征。体模包括10个药筒，每个药筒填充有不同的材料以产生广泛的放射组学特征值。使用来自四个医疗中心的通用电气、飞利浦、西门子和东芝扫描仪，使用其常规胸部成像方案进行扫描。研究的放射组学特征包括CT数的平均值和标准差以及来自邻域灰度差矩阵的纹理。为了量化扫描仪间变异性的重要性，我们引入了度量特征噪声。为了寻找扫描中的模式，我们对每个测试卡片进行了分层聚类。体模盒的17次CT扫描的平均CT值范围为-864至652 Hounsfield单位，而NSCLC肿瘤的CT扫描范围为-186至35 Hounsfield单位，表明体模的动态范围包括肿瘤的动态范围。特征值的扫描仪间变异性取决于检测盒材料和特征，对于某些特征，变异性相对于NSCLC肿瘤的患者间变异性较大。扫描仪间的特征噪声对于繁忙度最大，而对于纹理强度最小。尽管扫描仪制造商有一些一致的聚类，但分层聚类为每个检测盒产生了不同的体模扫描聚类。在来自不同CT扫描仪的CT图像上计算的放射组学特征值的变异性可以与在NSCLC肿瘤的CT图像中发现的这些特征的变异性相当。这些扫描仪间的差异应予以考虑，其影响应尽量减少在未来的放射组学研究。
The purpose of this study was to determine the significance of inter-scanner variability in CT image radiomics studies. We compared the radiomics features calculated for non-small cell lung cancer (NSCLC) tumors from 20 patients with those calculated for 17 scans of a specially designed radiomics phantom. The phantom comprised 10 cartridges, each filled with different materials to produce a wide range of radiomics feature values. The scans were acquired using General Electric, Philips, Siemens, and Toshiba scanners from four medical centers using their routine thoracic imaging protocol. The radiomics feature studied included the mean and standard deviations of the CT numbers as well as textures derived from the neighborhood gray-tone difference matrix. To quantify the significance of the inter-scanner variability, we introduced the metric feature noise. To look for patterns in the scans, we performed hierarchical clustering for each cartridge. The mean CT numbers for the 17 CT scans of the phantom cartridges spanned from -864 to 652 Hounsfield units compared with a span of -186 to 35 Hounsfield units for the CT scans of the NSCLC tumors, showing that the phantom’s dynamic range includes that of the tumors. The inter-scanner variability of the feature values depended on both the cartridge material and the feature, and the variability was large relative to the inter-patient variability in the NSCLC tumors for some features. The feature inter-scanner noise was greatest for busyness and least for texture strength. Hierarchical clustering produced different clusters of the phantom scans for each cartridge, although there was some consistent clustering by scanner manufacturer. The variability in the values of radiomics features calculated on CT images from different CT scanners can be comparable to the variability in these features found in CT images of NSCLC tumors. These inter-scanner differences should be considered, and their effects should be minimized in future radiomics studies.