Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, 3740 McClintock Avenue, Los Angeles, CA, 90089, USA.
Department of Radiology, University of Southern California, 1500 San Pablo Street, Los Angeles, CA, 90033, USA.
J Digit Imaging. 2021 Oct;34(5):1156-1170. doi: 10.1007/s10278-021-00506-6. Epub 2021 Sep 20.
The image biomarkers standardization initiative (IBSI) was formed to address the standardization of extraction of quantifiable imaging metrics. Despite its effort, there remains a lack of consensus or established guidelines regarding radiomic feature terminology, the underlying mathematics and their implementation across various software programs. This creates a scenario where features extracted using different toolboxes cannot be used to build or validate the same model leading to a non-generalization of radiomic results. In this study, IBSI-established phantom and benchmark values were used to compare the variation of the radiomic features while using 6 publicly available software programs and 1 in-house radiomics pipeline. All IBSI-standardized features (11 classes, 173 in total) were extracted. The relative differences between the extracted feature values from the different software programs and the IBSI benchmark values were calculated to measure the inter-software agreement. To better understand the variations, features are further grouped into 3 categories according to their properties: 1) morphology, 2) statistic/histogram and 3)texture features. While a good agreement was observed for a majority of radiomics features across the various tested programs, relatively poor agreement was observed for morphology features. Significant differences were also found in programs that use different gray-level discretization approaches. Since these software programs do not include all IBSI features, the level of quantitative assessment for each category was analyzed using Venn and UpSet diagrams and quantified using two ad hoc metrics. Morphology features earned lowest scores for both metrics, indicating that morphological features are not consistently evaluated among software programs. We conclude that radiomic features calculated using different software programs may not be interchangeable. Further studies are needed to standardize the workflow of radiomic feature extraction.
图像生物标志物标准化倡议 (IBSI) 的成立是为了解决可量化成像指标提取的标准化问题。尽管 IBSI 做出了努力，但在放射组特征术语、潜在数学原理及其在各种软件程序中的实施方面，仍然缺乏共识或既定的准则。这就造成了一个使用不同工具箱提取的特征无法用于构建或验证同一个模型的情况，从而导致放射组学结果无法推广。在这项研究中，使用 IBSI 确立的体模和基准值来比较使用 6 个公开可用的软件程序和 1 个内部放射组学管道时的放射组学特征的变化。所有 IBSI 标准化的特征（共 11 类，173 个）都被提取出来。计算不同软件程序提取的特征值与 IBSI 基准值之间的相对差异，以衡量软件之间的一致性。为了更好地理解变化，根据特征的性质将特征进一步分为 3 类：1）形态学，2）统计/直方图和 3）纹理特征。虽然在各种测试的程序中，大多数放射组学特征的一致性都很好，但形态学特征的一致性较差。使用不同灰度离散化方法的程序也存在显著差异。由于这些软件程序并不包含所有 IBSI 特征，因此使用 Venn 和 UpSet 图分析每个类别的定量评估，并使用两个特定指标进行量化。形态学特征在这两个指标中得分最低，这表明形态学特征在软件程序之间没有得到一致的评估。我们得出结论，使用不同软件程序计算的放射组学特征可能不可互换。需要进一步的研究来标准化放射组学特征提取的工作流程。
