Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer
文献类型:期刊论文
作者 | Zhou, Hai-Feng1; Han, Yu-Qi2,3; Lu, Jian1; Wei, Jing-Wei3,4; Guo, Jin-He1; Zhu, Hai-Dong1; Huang, Ming5; Ji, Jian-Song6; Lv, Wei-Fu7; Chen, Li1 |
刊名 | FRONTIERS IN ONCOLOGY |
出版日期 | 2019-09-27 |
卷号 | 9页码:11 |
ISSN号 | 2234-943X |
关键词 | radiomics pancreatic cancer malignant biliary obstruction irradiation stent survival |
DOI | 10.3389/fonc.2019.00973 |
通讯作者 | Tian, Jie(tian@ieee.org) ; Teng, Gao-Jun(gjteng@vip.sina.com) |
英文摘要 | Purpose: To develop a model to select appropriate candidates for irradiation stent placement among patients with unresectable pancreatic cancer with malignant biliary obstruction (UPC-MBO). Methods: This retrospective study included 106 patients treated with an irradiation stent for UPC-MBO. These patients were randomly divided into a training group (74 patients) and a validation group (32 patients). A clinical model for predicting restenosis-free survival (RFS) was developed with clinical predictors selected by univariate and multivariate analyses. After integrating the radiomics signature, a combined model was constructed to predict RFS. The predictive performance was evaluated with the concordance index (C-index) in both the training and validation groups. The median risk score of progression in the training group was used to divide patients into high- and low-risk subgroups. Results: Radiomics features were integrated with clinical predictors to develop a combined model. The predictive performance was better in the combined model (C-index, 0.791 and 0.779 in the training and validation groups, respectively) than in the clinical model (C-index, 0.673 and 0.667 in the training and validation groups, respectively). According to the median risk score of 1.264, the RFS was significantly different between the high- and low-risk groups (p < 0.001 for the training group, and p = 0.016 for the validation group). Conclusions: The radiomics-based model had good performance for RFS prediction in patients with UPC-MBO who received an irradiation stent. Patients with slow progression should consider undergoing irradiation stent placement for a longer RFS. |
WOS关键词 | MALIGNANT BILIARY OBSTRUCTION ; DUCTAL ADENOCARCINOMA ; I-125 SEEDS ; CONSENSUS STATEMENT ; IMAGING BIOMARKERS ; TUMOR BURDEN ; PREDICTS ; CA125 ; MULTICENTER ; SURVIVAL |
资助项目 | National Key Scientific Instrument and Equipment Development Projects of China[81827805] ; Innovation Platform of Jiangsu Provincial Medical Center[YXZXA2016005] ; National Natural Science Foundation of China[81520108015] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81771924] ; National Key Research and Development Program of China[2017YFC1308700] ; National Key Research and Development Program of China[2017YFC1309100] ; National Key Research and Development Program of China[2017YFA0205200] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] |
WOS研究方向 | Oncology |
语种 | 英语 |
出版者 | FRONTIERS MEDIA SA |
WOS记录号 | WOS:000488003500001 |
资助机构 | National Key Scientific Instrument and Equipment Development Projects of China ; Innovation Platform of Jiangsu Provincial Medical Center ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; Chinese Academy of Sciences |
源URL | [http://ir.ia.ac.cn/handle/173211/26976] |
专题 | 自动化研究所_中国科学院分子影像重点实验室 |
通讯作者 | Tian, Jie; Teng, Gao-Jun |
作者单位 | 1.Southeast Univ, Ctr Intervent Radiol & Vasc Surg, Dept Radiol, Zhongda Hosp,Med Sch, Nanjing, Jiangsu, Peoples R China 2.Xidian Univ, Sch Life Sci & Technol, Xian, Shaanxi, Peoples R China 3.Chinese Acad Sci, Key Lab Mol Imaging, Inst Automat, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Kunming Med Univ, Affiliated Hosp 3, Yunnan Tumor Hosp, Dept Minimally Invas Intervent Radiol, Kunming, Yunnan, Peoples R China 6.Wenzhou Med Univ, Lishui Cent Hosp, Dept Radiol, Lishui, Peoples R China 7.Univ Sci & Technol China, Affiliated Hosp 1, Anhui Prov Hosp, Dept Intervent Radiol, Hefei, Anhui, Peoples R China 8.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med, Beijing, Peoples R China 9.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Zhou, Hai-Feng,Han, Yu-Qi,Lu, Jian,et al. Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer[J]. FRONTIERS IN ONCOLOGY,2019,9:11. |
APA | Zhou, Hai-Feng.,Han, Yu-Qi.,Lu, Jian.,Wei, Jing-Wei.,Guo, Jin-He.,...&Teng, Gao-Jun.(2019).Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer.FRONTIERS IN ONCOLOGY,9,11. |
MLA | Zhou, Hai-Feng,et al."Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer".FRONTIERS IN ONCOLOGY 9(2019):11. |
入库方式: OAI收割
来源:自动化研究所
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