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首页> 外文期刊>Acta Radiologica >Gastric cancer: development and validation of a CT-based model to predict peritoneal metastasis
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Gastric cancer: development and validation of a CT-based model to predict peritoneal metastasis

机译：胃癌：基于CT的模型的开发和验证预测腹膜转移

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Background The sensitivity of computed tomography (CT) for the detection of peritoneal metastasis (PM) of advanced gastric cancer (AGC) is relatively low. Purpose To develop a predictive model to improve the sensitivity of PM detection and to externally validate this model. Material and Methods We analyzed data from 78 patients with PM, who had undergone preoperative CT and subsequent surgery between January 2012 and December 2014, and 101 controls to form a derivation set, retrospectively. The following CT findings were evaluated: tumor size; Bormann type 4; enlarged lymph node; indirect findings of PM (peritoneal thickening, fat stranding, plaques or nodules on the peritoneum, and ascites); and definitive findings of PM (omental cake and rectal shelf). A predictive model was created using multivariate logistic regression. Receiver operating characteristic (ROC) analyses were performed to assess the diagnostic performance of the model. The accuracy was externally validated at other hospitals on 31 patients with PM and 48 patients without PM. Results Tumor size >5.2 cm, Bormann type 4, enlarged lymph node, peritoneal plaques or nodules, and ascites were independently associated with PM. It was able to predict PM with a higher area under the ROC curve (AUC) and sensitivity than definitive findings of PM (AUC 0.903 vs. 0.647, sensitivity 92.3% vs. 38.3%). External validation confirmed the predictive power with good inter-observer agreement. Conclusion The CT-driven model shows higher AUC and sensitivity for prediction of PM and may help decision-making with the aim of improving care for patients with AGC.
机译：背景技术进行过晚胃癌（AGC）的腹膜转移（PM）检测的计算机断层扫描（CT）的敏感性相对较低。目的是开发一种预测模型，以提高PM检测的灵敏度和外部验证该模型。我们分析了78例PM患者的数据以及2014年1月至2014年1月至2014年1月至2014年12月之间进行的术前CT和随后的手术的数据和方法，并回顾性地形成推导集的101个控件。评估以下CT结果：肿瘤大小; Bormann类型4;淋巴结扩大; PM的间接结果（腹膜增稠，脂肪链，斑块或结节上的腹膜和腹水）;和PM（Omental Cake和直肠架）的明确结果。使用多变量逻辑回归来创建预测模型。进行接收器操作特征（ROC）分析以评估模型的诊断性能。在31例PM和48名没有PM患者的其他医院外部在其他医院外部验证。结果肿瘤大小> 5.2厘米，肉体4型，扩大淋巴结，腹膜斑块或结节，腹水与PM独立相关。它能够在ROC曲线（AUC）下具有更高面积的PM，比PM的明确发现（AUC 0.903对0.647，灵敏度92.3％对38.3％）的敏感性。外部验证确认了具有良好观察者间协议的预测权力。结论CT驱动模型显示出PM预测的升高和灵敏度，并有助于决策，目的是改善AGC患者的护理。

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