The Significance Of Preoperative Computed Tomography Features In The Prediction Of Overall Survival In Gastric Cancer: A Retrospective Analysis.
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Erturk, Sukru Mehmet
Vatansever, Sezai
Dogan, Izzet
Kızıldağ Yırgın, İnci
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Title: The Significance OfPreoperativeComputed Tomography Features In The Prediction Of Overall Survival In Gastric Cancer: A Retrospective Analysis.Purpose: The objective of this study was to evaluate the role of preoperative computed tomography (CT) findings in predicting overall survival (OS) in patients operated for gastric cancer.Material and Methods: The cases of 101 patients with gastric cancer (68 men, 33 women; age range, 29-82 years; median, 61 years) who underwent CT before surgery were retrospectively evaluated. Two radiologists reviewed multiplanar reconstruction images to measure invasion depth of the tumor (T stage), the number of pathological lymph nodes (N stage), the long diameter of the lesion, the localization of the tumor and the attenuation values of tumor in the arterial and venous phases (HUs). Post operative pathology findings, resection status (R0,R1), pathologic T stage, N stage, grade, histopathological subtype were recorded. All CT-derived parameters and clinicopathologicalvariables associated with OS were analysed by univariateanalysis, followed by multivariate and receiver operatorcharacteristics (ROC) analysis.Results:Multivariate cox regression analysis showed that non of the preoperative CT findings correlated with the OS. The survival rate after resection was worse for the R1 group and high grade group than for the R0 group and low grade group (p:0.001,p:0.005 respectively).N stage and long diameter of the lesion on CT imaging correctly predicted R1 resection ( AUC,0.697; sensitivity,63%; specificity, 88%, AUC,0.734; sensitivity,18%; specificity, 76% respectively).Limitation:This is a retrospective studyand number of participants were small.Conclusion:R1 resection is correlated with lower OS in operated gastric cancer. CT findings including the long diameter of the tumor and the number of pathological lymph nodes, can predict R1 resection.
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