Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer | |
Wang, Xiaoxiao1; Ding, Yi1; Wang, Siwen2,3![]() ![]() | |
发表期刊 | CANCER IMAGING
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ISSN | 1740-5025 |
2020-11-23 | |
卷号 | 20期号:1页码:1-10 |
摘要 | 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. |
关键词 | Lauren classification Radiomics Peritumoral analysis Gastric cancer Computed tomography |
DOI | 10.1186/s40644-020-00358-3 |
关键词[WOS] | CT ; CARCINOMA ; NOMOGRAM |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Oncology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Oncology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000595717300001 |
出版者 | BMC |
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/173211/41682 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Tian, Jie; Shan, Xiuhong |
作者单位 | 1.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 |
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 | 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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