Evidence map›Paper›PMID 36276081›Full record

ArticleFrontiers in oncology2022

A quantitative model based on gross tumor volume of gastric adenocarcinoma corresponding to N-stage measured at multidetector computed tomography for preoperative determination of resectability: A case control study.

Zi-Yi Yu, Dan Gao, Zhao Tang, Hai-Ying Zhou, Jing Ou, Ke-Ying Li, Xiao-Qian Chen, Dan Yang, Lin-Li Yan, Rui Li and 2 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Zi-Yi YuMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Dan GaoMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Zhao TangMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Hai-Ying ZhouMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Jing OuMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Ke-Ying LiMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Xiao-Qian ChenMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Dan YangMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Lin-Li YanMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Rui LiMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Xiao-Ming ZhangMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Tian-Wu ChenMedical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop and validate a quantitative model based on gross tumor volume (GTV) of gastric adenocarcinoma (GA) corresponding to N-stage measured at multidetector computed tomography (CT) for preoperative determination of resectability. Materials and methods: 493 consecutive patients with confirmed GA undergoing contrast-enhanced CT two weeks before treatments were randomly enrolled into the training cohort (TC, n = 271), internal validation cohort (IVC, n = 107) and external validation cohort (EVC, n = 115). GTV was measured on CT by multiplying sums of all tumor areas by section thickness. In TC, univariate and multivariate analyses were performed to select factors associated with resectability. Receiver operating characteristic (ROC) analysis was to determine if N-stage based GTV could identify resectability. In IVC and EVC, unweighted Cohen's Kappa tests were to evaluate performances of the ROC models. Results: According to univariate analysis, age, cT stage, cN stage and GTV were related to resectability in TC (all Conclusions: GTV and cN stage can be independent risk factors of unresectable GA, and N-stage based GTV can help determine resectability.

Indexed as

adenocarcinomaROC curvestomach neoplasmstomographyvolumeX-ray computed

Identifiers

PMID36276081
PMCPMC9579338

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