Ct-based intratumoral and peritumoral radiomics for predicting prognosis in osteosarcoma: A multicenter study

被引:1
|
作者
Su, Qiushi [1 ]
Wang, Ning [2 ]
Wang, Bingyan [3 ]
Wang, Yanmei [4 ]
Dai, Zhengjun [5 ]
Zhao, Xia [6 ]
Li, Xiaoli [1 ]
Li, Qiyuan [1 ]
Yang, Guangjie [7 ]
Nie, Pei [1 ]
机构
[1] Qingdao Univ, Affiliated Hosp, Dept Radiol, Qingdao, Shandong, Peoples R China
[2] Shandong First Med Univ, Shandong Prov Hosp, Dept Radiol, Jinan, Shandong, Peoples R China
[3] Qingdao Univ, Dept Ultrasound, Affiliated Hosp, Qingdao, Shandong, Peoples R China
[4] GE Healthcare, Shanghai, Peoples R China
[5] Huiying Med Technol Co Ltd, Sci Res Dept, Beijing, Peoples R China
[6] Shandong Univ Tradit Chinese Med, Affiliated Hosp, Dept Radiol, Jinan, Shandong, Peoples R China
[7] Qingdao Univ, Dept Nucl Med, Affiliated Hosp, Qingdao, Shandong, Peoples R China
关键词
Osteosarcoma; Prognosis; Radiomics; Computerized tomography; METASTATIC OSTEOSARCOMA; SURVIVAL; NOMOGRAM;
D O I
10.1016/j.ejrad.2024.111350
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: To evaluate the performance of CT -based intratumoral, peritumoral and combined radiomics signatures in predicting prognosis in patients with osteosarcoma. Methods: The data of 202 patients (training cohort:102, testing cohort:100) with osteosarcoma admitted to the two hospitals from August 2008 to February 2022 were retrospectively analyzed. Progression free survival (PFS) and overall survival (OS) were used as the end points. The radiomics features were extracted from CT images, three radiomics signatures(RS intratumoral, RS peritumoral, RS combined)were constructed based on intratumoral, peritumoral and combined radiomics features, respectively, and the radiomics score (Rad-score) were calculated. Kaplan -Meier survival analysis was used to evaluate the relationship between the Rad-score with PFS and OS, the Harrell's concordance index (C -index) was used to evaluate the predictive performance of the radiomics signatures. Results: Finally, 8, 6, and 21 features were selected for the establishment of RS intratumoral, RS peritumoral, and RS combined, respectively. Kaplan -Meier survival analysis confirmed that the Rad-scores of the three RSs were significantly correlated with the PFS and OS of patients with osteosarcoma. Among the three radiomics signatures, RS combined had better predictive performance, the C -index of PSF prediction was 0.833 in the training cohort and 0.814 in the testing cohort, the C -index of OS prediction was 0.796 in the training cohort and 0.764 in the testing cohort. Conclusions: CT -based intratumoral, peritumoral and combined radiomics signatures can predict the prognosis of patients with osteosarcoma, which may assist in individualized treatment and improving the prognosis of osteosarcoma patients.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Intratumoral and peritumoral CT radiomics in predicting prognosis in patients with chondrosarcoma: a multicenter study
    Li, Qiyuan
    Wang, Ning
    Wang, Yanmei
    Li, Xiaoli
    Su, Qiushi
    Zhang, Jing
    Zhao, Xia
    Dai, Zhengjun
    Wang, Yao
    Sun, Li
    Xing, Xuxiao
    Yang, Guangjie
    Gao, Chuanping
    Nie, Pei
    [J]. INSIGHTS INTO IMAGING, 2024, 15 (01)
  • [2] Intratumoral and peritumoral CT radiomics in predicting prognosis in patients with chondrosarcoma: a multicenter study
    Qiyuan Li
    Ning Wang
    Yanmei Wang
    Xiaoli Li
    Qiushi Su
    Jing Zhang
    Xia Zhao
    Zhengjun Dai
    Yao Wang
    Li Sun
    Xuxiao Xing
    Guangjie Yang
    Chuanping Gao
    Pei Nie
    [J]. Insights into Imaging, 15
  • [3] Intratumoral and peritumoral CT-based radiomics for predicting the microsatellite instability in gastric cancer
    Chen, Xingchi
    Zhuang, Zijian
    Pen, Lin
    Xue, Jing
    Zhu, Haitao
    Zhang, Lirong
    Wang, Dongqing
    [J]. ABDOMINAL RADIOLOGY, 2024, 49 (05) : 1363 - 1375
  • [4] The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma
    Hang Yuan
    Xiren Xu
    Shiliang Tu
    Bingchen Chen
    Yuguo Wei
    Yanqing Ma
    [J]. BMC Gastroenterology, 22
  • [5] The CT-based intratumoral and peritumoral machine learning radiomics analysis in predicting lymph node metastasis in rectal carcinoma
    Yuan, Hang
    Xu, Xiren
    Tu, Shiliang
    Chen, Bingchen
    Wei, Yuguo
    Ma, Yanqing
    [J]. BMC GASTROENTEROLOGY, 2022, 22 (01)
  • [6] A multicenter study: predicting KRAS mutation and prognosis in colorectal cancer through a CT-based radiomics nomogram
    Li, Manman
    Yuan, Yiwen
    Zhou, Hui
    Feng, Feng
    Xu, Guodong
    [J]. ABDOMINAL RADIOLOGY, 2024, 49 (06) : 1816 - 1828
  • [7] CT-Based Peritumoral and Intratumoral Radiomics as Pretreatment Predictors of Atypical Responses to Immune Checkpoint Inhibitor Across Tumor Types: A Preliminary Multicenter Study
    He, Shuai
    Feng, Yuqing
    Lin, Qi
    Wang, Lihua
    Wei, Lijun
    Tong, Jing
    Zhang, Yuwei
    Liu, Ying
    Ye, Zhaoxiang
    Guo, Yan
    Yu, Tao
    Luo, Yahong
    [J]. FRONTIERS IN ONCOLOGY, 2021, 11
  • [8] The value of CT-based radiomics in predicting the prognosis of acute pancreatitis
    Xue, Ming
    Lin, Shuai
    Xie, Dexuan
    Wang, Hongzhen
    Gao, Qi
    Zou, Lei
    Xiao, Xigang
    Jia, Yulin
    [J]. FRONTIERS IN MEDICINE, 2023, 10
  • [9] MRI-based intratumoral and peritumoral radiomics for preoperative prediction of glioma grade: a multicenter study
    Tan, Rui
    Sui, Chunxiao
    Wang, Chao
    Zhu, Tao
    [J]. FRONTIERS IN ONCOLOGY, 2024, 14
  • [10] Intratumoral and peritumoral CT-based radiomics strategy reveals distinct subtypes of non-small-cell lung cancer
    Tang, Xing
    Huang, Haolin
    Du, Peng
    Wang, Lijuan
    Yin, Hong
    Xu, Xiaopan
    [J]. JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2022, 148 (09) : 2247 - 2260