Xue Cindy, Yuan Jing, Zhou Yihang, Wong Oi Lei, Cheung Kin Yin, Yu Siu Ki
Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China.
Medical Physics Department, Hong Kong Sanatorium & Hospital, Hong Kong, China.
Vis Comput Ind Biomed Art. 2022 Apr 1;5(1):10. doi: 10.1186/s42492-022-00106-3.
Radiomics has increasingly been investigated as a potential biomarker in quantitative imaging to facilitate personalized diagnosis and treatment of head and neck cancer (HNC), a group of malignancies associated with high heterogeneity. However, the feature reliability of radiomics is a major obstacle to its broad validity and generality in application to the highly heterogeneous head and neck (HN) tissues. In particular, feature repeatability of radiomics in magnetic resonance imaging (MRI) acquisition, which is considered a crucial confounding factor of radiomics feature reliability, is still sparsely investigated. This study prospectively investigated the acquisition repeatability of 93 MRI radiomics features in ten HN tissues of 15 healthy volunteers, aiming for potential magnetic resonance-guided radiotherapy (MRgRT) treatment of HNC. Each subject underwent four MRI acquisitions with MRgRT treatment position and immobilization using two pulse sequences of 3D T1-weighed turbo spin-echo and 3D T2-weighed turbo spin-echo on a 1.5 T MRI simulator. The repeatability of radiomics feature acquisition was evaluated in terms of the intraclass correlation coefficient (ICC), whereas within-subject acquisition variability was evaluated in terms of the coefficient of variation (CV). The results showed that MRI radiomics features exhibited heterogeneous acquisition variability and uncertainty dependent on feature types, tissues, and pulse sequences. Only a small fraction of features showed excellent acquisition repeatability (ICC > 0.9) and low within-subject variability. Multiple MRI scans improved the accuracy and confidence of the identification of reliable features concerning MRI acquisition compared to simple test-retest repeated scans. This study contributes to the literature on the reliability of radiomics features with respect to MRI acquisition and the selection of reliable radiomics features for use in modeling in future HNC MRgRT applications.
作为定量成像中的一种潜在生物标志物，放射组学越来越多地被用于促进头颈癌（HNC）的个性化诊断和治疗，头颈癌是一组具有高度异质性的恶性肿瘤。然而，放射组学的特征可靠性是其在高度异质的头颈部（HN）组织中广泛应用的有效性和普遍性的主要障碍。特别是，放射组学在磁共振成像（MRI）采集过程中的特征重复性，被认为是放射组学特征可靠性的一个关键混杂因素，目前仍缺乏充分研究。本研究前瞻性地调查了15名健康志愿者的10个HN组织中93个MRI放射组学特征的采集重复性，旨在对头颈癌进行潜在的磁共振引导放疗（MRgRT）治疗。每位受试者在1.5 T MRI模拟器上，使用3D T1加权快速自旋回波和3D T2加权快速自旋回波两种脉冲序列，以MRgRT治疗位置和固定方式进行了四次MRI采集。放射组学特征采集的重复性通过组内相关系数（ICC）进行评估，而受试者内部采集变异性则通过变异系数（CV）进行评估。结果表明，MRI放射组学特征表现出取决于特征类型、组织和脉冲序列的异质采集变异性和不确定性。只有一小部分特征显示出优异的采集重复性（ICC > 0.9）和低受试者内部变异性。与简单的重测重复扫描相比，多次MRI扫描提高了关于MRI采集的可靠特征识别的准确性和可信度。本研究为有关放射组学特征在MRI采集中的可靠性以及在未来头颈癌MRgRT应用中用于建模的可靠放射组学特征选择的文献做出了贡献。
