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基于增强CT静脉期影像组学模型术前预测进展期胃癌神经侵犯的价值

庞志斌 林礼波 周红艳 陈晓丽 贵椿涵

肿瘤预防与治疗2026,Vol.39Issue(7):569-575,7.
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肿瘤预防与治疗2026,Vol.39Issue(7):569-575,7.DOI:10.3969/j.issn.1674-0904.2026.07.006

基于增强CT静脉期影像组学模型术前预测进展期胃癌神经侵犯的价值

Value of a Contrast-Enhanced CT Venous Phase Radiomics Model in Pre-operative Prediction of Perineural Invasion in Advanced Gastric Cancer

庞志斌 1林礼波 1周红艳 1陈晓丽 1贵椿涵1

作者信息

  • 1. 610041 成都,四川省肿瘤临床医学研究中心,四川省肿瘤医院·研究所,四川省癌症防治中心,电子科技大学附属肿瘤医院 影像科
  • 折叠

摘要

Abstract

Objective:To investigate the value of an interpretable radiomics model based on venous phase contrast-en-hanced CT in the preoperative prediction of perineural invasion(PNI)in advanced gastric cancer.Methods:Imaging and clinical data were retrospectively collected from 110 patients with pathologically confirmed advanced gastric cancer admitted to Sichuan Cancer Hospital between January 2024 and December 2024,including 58 PNI-positive cases and 52 PNI-negative cases.A total of 1,223 radiomic features were extracted from venous phase contrast-enhanced CT images after target volume delineation.Patients were divided into a training cohort(77 cases)and a validation cohort(33 cases)at a ratio of 7:3.The least absolute shrinkage and selection operator was used for feature selection.Logistic regression was applied to estab-lish radiomics,clinical and combined models.The predictive performance of each model was evaluated by the area under the curve(AUC).A nomogram was used to visualize the predictive risk probability of the combined model,and decision curve analysis was performed to assess its clinical utility.SHAP(Shapley Additive Explanations)was conducted to evaluate the importance and contribution of clinical and radiomic features in the model.Results:For the prediction of PNI in advanced gastric cancer,the radiomics model achieved an AUC of 0.67(95%CI:0.55~0.80)in the training cohort and 0.72(95%CI:0.54~0.90)in the validation cohort;the clinical model yielded an AUC of 0.74(95%CI:0.63~0.84)and 0.70(95%CI:0.53~0.87),respectively;the combined model showed an AUC of 0.81(95%CI:0.72~0.91)and 0.80(95%CI:0.64~0.95),respectively.Conclusion:The contrast-enhanced CT-based combined model allows effec-tive preoperative prediction of PNI in advanced gastric cancer.

关键词

计算机断层成像/影像组学/胃癌/神经侵犯/夏普利加

Key words

Computed Tomography/Radiomics/Gastric cancer/Perineural invasion/Shapley additive explanations

分类

医药卫生

引用本文复制引用

庞志斌,林礼波,周红艳,陈晓丽,贵椿涵..基于增强CT静脉期影像组学模型术前预测进展期胃癌神经侵犯的价值[J].肿瘤预防与治疗,2026,39(7):569-575,7.

基金项目

This study was supported by grants from Science and Technology Department of Sichuan Province(No.22SYSX0159).四川省科技计划项目(编号:22SYSX0159) (No.22SYSX0159)

肿瘤预防与治疗

1674-0904

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