Acquisition repeatability of MRI radiomics features in the head and neck: a dual-3D-sequence multi-scan study

被引:11
|
作者
Xue, Cindy [1 ]
Yuan, Jing [1 ]
Zhou, Yihang [1 ]
Wong, Oi Lei [1 ]
Cheung, Kin Yin [2 ]
Yu, Siu Ki [2 ]
机构
[1] Hong Kong Sanat & Hosp, Res Dept, Hong Kong, Peoples R China
[2] Hong Kong Sanat & Hosp, Med Phys Dept, Hong Kong, Peoples R China
关键词
Radiomics; Magnetic resonance guided radiotherapy; Head and neck; Repeatability; Intraclass correlation coefficient; GUIDED RADIOTHERAPY; REPRODUCIBILITY; SIGNATURE; IMAGES;
D O I
10.1186/s42492-022-00106-3
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:13
相关论文
共 8 条
  • [1] Acquisition repeatability of MRI radiomics features in the head and neck: a dual-3D-sequence multi-scan study
    Cindy Xue
    Jing Yuan
    Yihang Zhou
    Oi Lei Wong
    Kin Yin Cheung
    Siu Ki Yu
    Visual Computing for Industry, Biomedicine, and Art, 5
  • [2] Longitudinal acquisition repeatability of MRI radiomics features: An ACR MRI phantom study on two MRI scanners using a 3D T1W TSE sequence
    Wong, Oi Lei
    Yuan, JIng
    Zhou, Yihang
    Yu, Siu Ki
    Cheung, Kin Yin
    MEDICAL PHYSICS, 2021, 48 (03) : 1239 - 1249
  • [3] Quantitative assessment of acquisition imaging parameters on MRI radiomics features: a prospective anthropomorphic phantom study using a 3D-T2W-TSE sequence for MR-guided-radiotherapy
    Yuan, Jing
    Xue, Cindy
    Lo, Gladys
    Wong, Oi Lei
    Zhou, Yihang
    Yu, Siu Ki
    Cheung, Kin Yin
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2021, 11 (05) : 1870 - +
  • [4] Performance comparison of 2D and 3D MRI radiomics features in meningioma grade prediction: A preliminary study
    Duan, Chongfeng
    Li, Nan
    Liu, Xuejun
    Cui, Jiufa
    Wang, Gang
    Xu, Wenjian
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [5] Repeatability of Radiomic Features Against Simulated Scanning Position Stochasticity Across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-institutional Study on Head-and-Neck Cases
    Zhang, Jiang
    Lam, Saikit
    Teng, Xinzhi
    Zhang, Yuanpeng
    Ma, Zongrui
    Lee, Francis
    Au, Kwok-hung
    Yip, Wai Yi
    Chang, Tien Yee Amy
    Chan, Wing Chi Lawrence
    Lee, Victor
    Wu, Q. Jackie
    Cai, Jing
    COMPUTATIONAL MATHEMATICS MODELING IN CANCER ANALYSIS, CMMCA 2022, 2022, 13574 : 21 - 34
  • [6] A multi-organ cancer study of the classification performance using 2D and 3D image features in radiomics analysis
    Xu, Lei
    Yang, Pengfei
    Yen, Eric Alexander
    Wan, Yidong
    Jiang, Yangkang
    Cao, Zuozhen
    Shen, Xiaoyong
    Wu, Yan
    Wang, Jing
    Luo, Chen
    Niu, Tianye
    PHYSICS IN MEDICINE AND BIOLOGY, 2019, 64 (21)
  • [7] A pilot study of highly accelerated 3D MRI in the head and neck position verification for MR-guided radiotherapy
    Zhou, Yihang
    Wong, Oi Lei
    Cheung, Kin Lin
    Yu, Siu Ki
    Yuan, Jing
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2019, 9 (07) : 1255 - 1269
  • [8] Comparison of image quality of head and neck lesions between 3D gradient echo sequences with compressed sensing and the multi-slice spin echo sequence
    Kami, Yukiko
    Chikui, Toru
    Togao, Osamu
    Ooga, Masahiro
    Yoshiura, Kazunori
    ACTA RADIOLOGICA OPEN, 2020, 9 (09)