Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection | |
Li, Wuchao1,2,3; Zhang, Liwen2,4; Tian, Chong1,3; Song, Hui1,3; Fang, Mengjie2; Hu, Chaoen2; Zang, Yali2; Cao, Ying3,5; Dai, Shiyuan3,6; Wang, Fang3,7; Dong, Di2,4; Wang, Rongpin1,3; Tian, Jie2,4,8 | |
发表期刊 | EUROPEAN RADIOLOGY |
ISSN | 0938-7994 |
2019-06-01 | |
卷号 | 29期号:6页码:3079-3089 |
摘要 | ObjectivesThe present study aimed to investigate the clinical prognostic significance of radiomics signature (R-signature) in patients with gastric cancer who had undergone radical resection.MethodsA total of 181 patients with gastric cancer who had undergone radical resection were enrolled in this retrospective study. The association between the R-signature and overall survival (OS) was assessed in the primary cohort and verified in the validation cohort. Furthermore, the performance of a radiomics nomogram integrating the R-signature and significant clinicopathological risk factors was evaluated.ResultsThe R-signature, which consisted of six imaging features, stratified patients with gastric cancer who had undergone radical resection into two prognostic risk groups in both cohorts. The radiomics nomogram incorporating R-signature and significant clinicopathological risk factors (T stage, N stage, and differentiation) exhibited significant prognostic superiority over clinical nomogram and R-signature alone (Harrell concordance index, 0.82 vs 0.71 and 0.82 vs 0.74, respectively, p<0.001 in both analyses). All calibration curves showed remarkable consistency between predicted and actual survival, and decision curve analysis verified the usefulness of the radiomics nomogram for clinical practice.ConclusionsThe R-signature could be used to stratify patients with gastric cancer following radical resection into high- and low-risk groups. Furthermore, the radiomics nomogram provided better predictive accuracy than other predictive models and might aid clinicians with therapeutic decision-making and patient counseling.Key Points center dot Radiomics can stratify the gastric cancer patients following radical resection into high- and low-risk groups.center dot Radiomics can improve the prognostic value of TNM staging system.center dot Radiomics may facilitate personalized treatment of gastric cancer patients. |
关键词 | Multidetector computed tomography Stomach neoplasms Survival |
DOI | 10.1007/s00330-018-5861-9 |
关键词[WOS] | INTRATUMOR HETEROGENEITY ; RADIOGENOMICS ; INFORMATION ; SELECTION ; SURVIVAL |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Guizhou Provincial People's Hospital United Foundation[QKHLHZ[2015] 7115] ; Guizhou Science and Technology Department Key Project[QKF[2017] 25] ; Technology and Innovation Foundation for the Returned Overseas Chinese Scholars[QRXMZZ(2016) 03] ; Science and Technology Foundation of Guizhou Province[QKHJC[2016] 1096] ; Guizhou Provincial People's Hospital Doctoral Foundation[GZSYBS[2015] 02] ; Guizhou Provincial Department of Science and Technology ; National Natural Science Foundation of China[61661010] ; National Natural Science Foundation of China[81360565] ; National Key R&D Program of China[2017YFC1309100] ; National Key R&D Program of China[2017YFC1308700] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; National Natural Science Foundation of China[81671851] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81771924] ; National Key R&D Program of China[2017YFA0205200] ; National Natural Science Foundation of China[61231004] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[61231004] ; National Key R&D Program of China[2017YFA0205200] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[81501616] ; National Natural Science Foundation of China[81671851] ; Science and Technology Service Network Initiative of the Chinese Academy of Sciences[KFJ-SW-STS-160] ; Beijing Municipal Science and Technology Commission[Z161100002616022] ; National Key R&D Program of China[2017YFC1308700] ; National Key R&D Program of China[2017YFC1309100] ; National Natural Science Foundation of China[81360565] ; National Natural Science Foundation of China[61661010] ; Guizhou Provincial Department of Science and Technology ; Guizhou Provincial People's Hospital Doctoral Foundation[GZSYBS[2015] 02] ; Science and Technology Foundation of Guizhou Province[QKHJC[2016] 1096] ; Technology and Innovation Foundation for the Returned Overseas Chinese Scholars[QRXMZZ(2016) 03] ; Guizhou Science and Technology Department Key Project[QKF[2017] 25] ; Guizhou Provincial People's Hospital United Foundation[QKHLHZ[2015] 7115] |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000467646300035 |
出版者 | SPRINGER |
七大方向——子方向分类 | 医学影像处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/24584 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Wang, Rongpin; Tian, Jie |
作者单位 | 1.Guizhou Prov Peoples Hosp, Dept Radiol, Guiyang, Guizhou, Peoples R China 2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing, Peoples R China 3.Guizhou Prov Peoples Hosp, Guizhou Prov Key Lab Intelligent Med Image Anal &, Guiyang, Guizhou, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 5.Guizhou Prov Peoples Hosp, Dept Pathol, Guiyang, Guizhou, Peoples R China 6.Guizhou Prov Peoples Hosp, Dept Med Records & Stat, Guiyang, Guizhou, Peoples R China 7.Guizhou Prov Peoples Hosp, Dept Gen Surg, Guiyang, Guizhou, Peoples R China 8.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Li, Wuchao,Zhang, Liwen,Tian, Chong,et al. Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection[J]. EUROPEAN RADIOLOGY,2019,29(6):3079-3089. |
APA | Li, Wuchao.,Zhang, Liwen.,Tian, Chong.,Song, Hui.,Fang, Mengjie.,...&Tian, Jie.(2019).Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection.EUROPEAN RADIOLOGY,29(6),3079-3089. |
MLA | Li, Wuchao,et al."Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection".EUROPEAN RADIOLOGY 29.6(2019):3079-3089. |
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