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首页> 外文会议>SPIE Medical Imaging Conference >The Effects of Variations in Parameters and Algorithm Choices on Calculated Radiomics Feature Values: Initial investigations and comparisons to feature variability across CT image acquisition conditions
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The Effects of Variations in Parameters and Algorithm Choices on Calculated Radiomics Feature Values: Initial investigations and comparisons to feature variability across CT image acquisition conditions

机译：参数和算法选择的变化对放射线学特征值的影响：CT图像采集条件下特征变化的初步研究和比较

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Translation of radiomics into clinical practice requires confidence in its interpretations. This may be obtained via understanding and overcoming the limitations in current radiomic approaches. Currently there is a lack of standardization in radiomic feature extraction. In this study we examined a few factors that are potential sources of inconsistency in characterizing lung nodules, such as l)different choices of parameters and algorithms in feature calculation, 2)two CT image dose levels, 3)different CT reconstruction algorithms (WFBP, denoised WFBP, and Iterative). We investigated the effect of variation of these factors on entropy textural feature of lung nodules. CT images of 19 lung nodules identified from our lung cancer screening program were identified by a CAD tool and contours provided. The radiomics features were extracted by calculating 36 GLCM based and 4 histogram based entropy features in addition to 2 intensity based features. A robustness index was calculated across different image acquisition parameters to illustrate the reproducibility of features. Most GLCM based and all histogram based entropy features were robust across two CT image dose levels. Denoising of images slightly improved robustness of some entropy features at WFBP. Iterative reconstruction resulted in improvement of robustness in a fewer times and caused more variation in entropy feature values and their robustness. Within different choices of parameters and algorithms texture features showed a wide range of variation, as much as 75% for individual nodules. Results indicate the need for harmonization of feature calculations and identification of optimum parameters and algorithms in a radiomics study.
机译：放射学翻译成临床实践需要对其解释有信心。这可以通过理解并克服当前放射学方法的局限性来获得。当前，在放射学特征提取方面缺乏标准化。在这项研究中，我们研究了一些可能导致肺结节特征不一致的因素，例如：l）特征计算中参数和算法的不同选择，2）两种CT图像剂量水平，3）不同的CT重建算法（WFBP，去噪WFBP，以及迭代）。我们调查了这些因素的变化对肺结节熵纹理特征的影响。从我们的肺癌筛查程序中识别出的19个肺结节的CT图像通过CAD工具和所提供的轮廓进行了识别。通过计算36个基于GLCM的熵特征和4个基于直​​方图的熵特征以及2个基于强度的特征来提取放射性组特征。计算了不同图像采集参数的鲁棒性指数，以说明特征的可再现性。大多数基于GLCM和所有基于直方图的熵特征在两个CT图像剂量水平上都很鲁棒。图像的去噪稍微改善了WFBP处某些熵特征的鲁棒性。迭代重建可在较短时间内提高鲁棒性，并导致熵特征值及其鲁棒性更多的变化。在参数和算法的不同选择中，纹理特征显示出很大的变化范围，单个结节高达75％。结果表明在放射学研究中需要统一特征计算以及确定最佳参数和算法。

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