CASIA OpenIR  > 中国科学院分子影像重点实验室
Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer
Wang, Xiaoxiao1; Ding, Yi1; Wang, Siwen2,3; Dong, Di2,3,4; Li, Hailin2,5; Chen, Jian6; Hu, Hui1; Lu, Chao1; Tian, Jie2,4,5,7; Shan, Xiuhong1
Source PublicationCANCER IMAGING
ISSN1740-5025
2020-11-23
Volume20Issue:1Pages:1-10
Abstract

Background: Preoperative prediction of the Lauren classification in gastric cancer (GC) is very important to the choice of therapy, the evaluation of prognosis, and the improvement of quality of life. However, there is not yet radiomics analysis concerning the prediction of Lauren classification straightly. In this study, a radiomic nomogram was developed to preoperatively differentiate Lauren diffuse type from intestinal type in GC.

Methods: A total of 539 GC patients were enrolled in this study and later randomly allocated to two cohorts at a 7:3 ratio for training and validation. Two sets of radiomic features were derived from tumor regions and peritumor regions on venous phase computed tomography (CT) images, respectively. With the least absolute shrinkage and selection operator logistic regression, a combined radiomic signature was constructed. Also, a tumor-based model and a peripheral ring-based model were built for comparison. Afterwards, a radiomic nomogram integrating the combined radiomic signature and clinical characteristics was developed. All the models were evaluated regarding classification ability and clinical usefulness.

Results: The combined radiomic signature achieved an area under receiver operating characteristic curve (AUC) of 0.715 (95% confidence interval [CI], 0.663-0.767) in the training cohort and 0.714 (95% CI, 0.636-0.792) in the validation cohort. The radiomic nomogram incorporating the combined radiomic signature, age, CT T stage, and CT N stage outperformed the other models with a training AUC of 0.745 (95% CI, 0.696-0.795) and a validation AUC of 0.758 (95% CI, 0.685-0.831). The significantly improved sensitivity of radiomic nomogram (0.765 and 0.793) indicated better identification of diffuse type GC patients. Further, calibration curves and decision curves demonstrated its great model fitness and clinical usefulness.

Conclusions: The radiomic nomogram involving the combined radiomic signature and clinical characteristics holds potential in differentiating Lauren diffuse type from intestinal type for reasonable clinical treatment strategy.

KeywordLauren classification Radiomics Peritumoral analysis Gastric cancer Computed tomography
DOI10.1186/s40644-020-00358-3
WOS KeywordCT ; CARCINOMA ; NOMOGRAM
Indexed BySCI
Language英语
WOS Research AreaOncology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectOncology ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000595717300001
PublisherBMC
Sub direction classification医学影像处理与分析
Citation statistics
Cited Times:21[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/41682
Collection中国科学院分子影像重点实验室
Corresponding AuthorTian, Jie; Shan, Xiuhong
Affiliation1.Jiangsu Univ, Affiliated Peoples Hosp, Dept Radiol, Zhenjiang, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing Key Lab Mol Imaging,State Key Lab Managem, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
4.Jinan Univ, Zhuhai Peoples Hosp, Zhuhai Precis Med Ctr, Zhuhai, Peoples R China
5.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing, Peoples R China
6.Jiangsu Univ, Dept Med Imaging, Med Coll, Zhenjiang, Jiangsu, Peoples R China
7.Xidian Univ, Engn Res Ctr Mol & Neuro Imaging, Sch Life Sci & Technol, Minist Educ, Xian, Peoples R China
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Xiaoxiao,Ding, Yi,Wang, Siwen,et al. Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer[J]. CANCER IMAGING,2020,20(1):1-10.
APA Wang, Xiaoxiao.,Ding, Yi.,Wang, Siwen.,Dong, Di.,Li, Hailin.,...&Shan, Xiuhong.(2020).Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer.CANCER IMAGING,20(1),1-10.
MLA Wang, Xiaoxiao,et al."Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer".CANCER IMAGING 20.1(2020):1-10.
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