CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer.
Purpose: To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer.Materials and Methods: This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surg...
| Publicado en: | European Radiology Vol. 30; no. 2; pp. 976 - 987 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=141192293&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 141192293 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Feb2020 vid: 30 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 141192293 141192293 NLM31468157 141192293 10.1007/s00330-019-06398-z NLM31468157 141192293 ppf: 976 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: CT radiomics nomogram for the preoperative prediction of lymph node metastasis in gastric cancer. aug: au: Wang, Yue Liu, Wei Yu, Yang Liu, Jing-juan Xue, Hua-dan Qi, Ya-fei Lei, Jing Yu, Jian-chun Jin, Zheng-yu affil: Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 1, Shuaifuyuan, Dongcheng District, 100730, Bejing, People's Republic of China sug: subj: Neoplasm Metastasis Stomach Neoplasms Models, Statistical Algorithms Middle Age Preoperative Care Methods Retrospective Design Stomach Neoplasms Pathology Adult Aged Stomach Neoplasms Surgery Predictive Value of Tests Male Prospective Studies ROC Curve Female Neoplasm Staging Tomography, X-Ray Computed Methods Scales Funding Source Middle Aged: 45-64 years Adult: 19-44 years Aged: 65+ years Male Female ab: Purpose: To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer.Materials and Methods: This retrospective study included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts.Results: The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively.Conclusions: The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer.Key Points: • CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer. • Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer. • The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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