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Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics
He, Ming1; Liu, Zhenyu2,3,5; Lin, Yusong4; Wan, Jianzhong4; Li, Juan1; Xu, Kai1; Wang, Yun1; Jin, Zhengyu1; Tian, Jie2,3,5,6,7; Xue, Huadan1
发表期刊EUROPEAN JOURNAL OF RADIOLOGY
ISSN0720-048X
2019-08-01
卷号117页码:102-111
通讯作者Tian, Jie(jie.tian@ia.ac.cn) ; Xue, Huadan(bjdanna95@hotmail.com)
摘要Purpose: To develop and validate an effective model to differentiate NF-pNET from PDAC. Materials and methods: Between July 2014 and December 2017, 147 patients (80 patients with PDAC and 67 patients with atypical NF-pNET) with pathology results and enhanced CT were consecutively enrolled and chronologically divided into primary and validation cohorts. Three models were built to differentiate atypical NF-pNET from PDAC, including a model based on radiomic signature alone, one based on clinicoradiological features alone and one that integrated the two. The diagnostic performance of the three models was estimated and compared with the area under the receiver operating characteristic curve (AUC) in the validation cohort. A nomogram was used to represent the model with the best performance, and the associated calibration was also assessed. Results: In the validation cohort, the AUC for differential diagnosis was 0.884 with the integrated model, which was significantly improved over that of the model based on clinicoradiological features (AUC = 0.775, p value = 0.004) and was comparable to that of the model based on the radiomic signature (AUC = 0.873, p value = 0.512). The nomogram representing the integrated model achieved good discrimination performances in both the primary and validation cohorts, with C-indices of 0.960 and 0.884, respectively. Conclusion: The integrated model outperformed the model based on clinicoradiological features alone and was comparable to the model based on the radiomic signature alone with respect to the differential diagnosis of atypical NF-pNET and PDAC. The nomogram achieved an optimal preoperative, noninvasive differential diagnosis between atypical pNET and PDAC, which can better inform therapeutic choice in clinical practice.
关键词Pancreatic ductal carcinoma Neuroendocrine tumor Multidetector computed tomography Radiomics Differential diagnosis
DOI10.1016/j.ejrad.2019.05.024
关键词[WOS]IMAGING MIMICS ; DIAGNOSIS ; PREDICTION ; MANAGEMENT ; GUIDELINES ; CARCINOMA ; SURVIVAL ; MDCT
收录类别SCI
语种英语
WOS研究方向Radiology, Nuclear Medicine & Medical Imaging
WOS类目Radiology, Nuclear Medicine & Medical Imaging
WOS记录号WOS:000475337200014
出版者ELSEVIER IRELAND LTD
七大方向——子方向分类医学影像处理与分析
引用统计
被引频次:25[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/26832
专题中国科学院分子影像重点实验室
通讯作者Tian, Jie; Xue, Huadan
作者单位1.Peking Union Med Coll Hosp Beijing, Dept Radiol, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Zhengzhou Univ, Software Technol Sch, Zhengzhou, Henan, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100080, Peoples R China
6.Beihang Univ, Beijing Adv Innovat Ctr Big Data Precis Med, Sch Med, Beijing 100191, Peoples R China
7.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian 710126, Shaanxi, Peoples R China
通讯作者单位中国科学院自动化研究所
推荐引用方式
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He, Ming,Liu, Zhenyu,Lin, Yusong,et al. Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics[J]. EUROPEAN JOURNAL OF RADIOLOGY,2019,117:102-111.
APA He, Ming.,Liu, Zhenyu.,Lin, Yusong.,Wan, Jianzhong.,Li, Juan.,...&Xue, Huadan.(2019).Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics.EUROPEAN JOURNAL OF RADIOLOGY,117,102-111.
MLA He, Ming,et al."Differentiation of atypical non-functional pancreatic neuroendocrine tumor and pancreatic ductal adenocarcinoma using CT based radiomics".EUROPEAN JOURNAL OF RADIOLOGY 117(2019):102-111.
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