Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis

doi:10.3389/fonc.2021.745001

	Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis
	Chen, Hai-Yan 2,3; Deng, Xue-Ying 2,3; Pan, Yao 4; Chen, Jie-Yu 2,3; Liu, Yun-Ying 3,5; Chen, Wu-Jie 2,3; Yang, Hong 2,3; Zheng, Yao 2,3; Yang, Yong-Bo 2,3; Liu, Cheng 6
刊名	FRONTIERS IN ONCOLOGY
	2021-12-23
卷号	11
关键词	pancreatic neoplasms serous cystadenoma mucinous cystadenoma texture analysis tomography
ISSN号	2234-943X
DOI	10.3389/fonc.2021.745001
通讯作者	Shao, Guo-Liang(shaogl@zjcc.org.cn) ; Yu, Ri-Sheng(risheng-yu@zju.edu.cn)
英文摘要	ObjectiveTo establish a diagnostic model by combining imaging features with enhanced CT texture analysis to differentiate pancreatic serous cystadenomas (SCNs) from pancreatic mucinous cystadenomas (MCNs). Materials and MethodsFifty-seven and 43 patients with pathology-confirmed SCNs and MCNs, respectively, from one center were analyzed and divided into a training cohort (n = 72) and an internal validation cohort (n = 28). An external validation cohort (n = 28) from another center was allocated. Demographic and radiological information were collected. The least absolute shrinkage and selection operator (LASSO) and recursive feature elimination linear support vector machine (RFE_LinearSVC) were implemented to select significant features. Multivariable logistic regression algorithms were conducted for model construction. Receiver operating characteristic (ROC) curves for the models were evaluated, and their prediction efficiency was quantified by the area under the curve (AUC), 95% confidence interval (95% CI), sensitivity and specificity. ResultsFollowing multivariable logistic regression analysis, the AUC was 0.932 and 0.887, the sensitivity was 87.5% and 90%, and the specificity was 82.4% and 84.6% with the training and validation cohorts, respectively, for the model combining radiological features and CT texture features. For the model based on radiological features alone, the AUC was 0.84 and 0.91, the sensitivity was 75% and 66.7%, and the specificity was 82.4% and 77% with the training and validation cohorts, respectively. ConclusionThis study showed that a logistic model combining radiological features and CT texture features is more effective in distinguishing SCNs from MCNs of the pancreas than a model based on radiological features alone.
资助项目	National Natural Science Foundation of China[82072032] ; Major Medical and Health Science and Technology Projects in Zhejiang Province[WKJ-ZJ-2002] ; Key R&D Projects in Zhejiang Province[2019C03058] ; Medical Science and Technology Project of the Health Department of Zhejiang Province of China[2019328554] ; Medical Science and Technology Project of the Health Department of Zhejiang Province of China[2021KY091]
WOS关键词	OLIGOCYSTIC ADENOMA ; TUMORS ; CYSTADENOMA ; ASSOCIATION ; GUIDELINES ; MANAGEMENT
WOS研究方向	Oncology
语种	英语
出版者	FRONTIERS MEDIA SA
WOS记录号	WOS:000743506600001
资助机构	National Natural Science Foundation of China ; Major Medical and Health Science and Technology Projects in Zhejiang Province ; Key R&D Projects in Zhejiang Province ; Medical Science and Technology Project of the Health Department of Zhejiang Province of China
内容类型	期刊论文
源URL	[http://ir.hfcas.ac.cn:8080/handle/334002/127115]
专题	中国科学院合肥物质科学研究院
通讯作者	Shao, Guo-Liang; Yu, Ri-Sheng
作者单位	1.Clin Res Ctr Hepatobiliary & Pancreat Dis Zhejian, Hangzhou, Peoples R China 2.Univ Chinese Acad Sci, Canc Hosp, Dept Radiol, Zhejiang Canc Hosp, Hangzhou, Peoples R China 3.Chinese Acad Sci, Inst Canc & Basic Med ICBM, Hangzhou, Peoples R China 4.Zhejiang Univ, Affiliated Hosp 2, Dept Radiol, Sch Med, Hangzhou, Peoples R China 5.Univ Chinese Acad Sci, Canc Hosp, Dept Pathol, Zhejiang Canc Hosp, Hangzhou, Peoples R China 6.Hangzhou YITU Healthcare Technol Co Ltd, Res Inst Artificial Intelligence Healthcare, Hangzhou, Peoples R China
推荐引用方式 GB/T 7714	Chen, Hai-Yan,Deng, Xue-Ying,Pan, Yao,et al. Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis[J]. FRONTIERS IN ONCOLOGY,2021,11.
APA	Chen, Hai-Yan.,Deng, Xue-Ying.,Pan, Yao.,Chen, Jie-Yu.,Liu, Yun-Ying.,...&Yu, Ri-Sheng.(2021).Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis.FRONTIERS IN ONCOLOGY,11.
MLA	Chen, Hai-Yan,et al."Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis".FRONTIERS IN ONCOLOGY 11(2021).