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find Keyword "imaging omics" 1 results
  • Predictive value of CT for neoadjuvant chemotherapy in advanced gastric cancer

    Objective To explore the value of multi-slice spiral CT (MSCT) 3D imaging in evaluating the efficacy of neoadjuvant chemotherapy for advanced gastric cancer. MethodsSixty-one patients with gastric cancer diagnosed by gastroscopy and pathological examination at the First Hospital of Lanzhou University from January 2019 to March 2022 were divided into chemotherapy effective group (n=39) and ineffective group (n=22) according to postoperative pathological regression grade (tumor regression grade, TRG) standards. MSCT was performed before neoadjuvant chemotherapy and before undergoing surgical treatment after neoadjuvant chemotherapy. The independent predictors related to the efficacy of chemotherapy were screened by binary logistics regression analysis of CT conventional observation indexes (including maximum tumor thickness, gastric wall motility, enhancement mode, lymph node metastasis, distant metastasis, peritoneal thickening or peritoneal nodules). Tumor volume and maximum tumor thickness were measured with the imaging histology software ITK-snap, and the diagnostic efficacy of tumor volume and CT conventional observation indexes was analyzed. Results In the evaluation of chemotherapy efficacy, tumor volume reduction rate and tumor maximum thickness reduction rate can evaluate the efficacy of chemotherapy to a certain extent (P< 0.01). The statistically significant indicators (tumor maximum thickness reduction rate, gastric wall motility, lesion intensification mode and peritoneal thickening and nodules) were analyzed by univariate analysis and binary logistic regression. The results showed that gastric wall motility [OR=0.294, 95%CI (0.093, 0.928), P=0.037] and maximum tumor thickness reduction rate [OR=0.282, 95%CI (0.083, 0.957), P=0.042] were independent predictors of the efficacy of neoadjuvant chemotherapy for progressive gastric cancer. Receiver operating characteristic (ROC) curve were plotted based on the predicted probability variable obtained from both and the results showed that the area under curve (AUC=0.900) , sensitivity (83.3%), and specificity (99.8%) of the tumor volume reduction rate were all higher than those of CT clinical index prediction probability variables (AUC=0.802, sensitivity was 58.3%, specificity was 85.7%). ConclusionThe measurement of tumor volume by MSCT combined with the imaging omics software ITK-snap provides an objective basis for the prediction of the efficacy of neoadjuvant chemotherapy, and its diagnostic efficacy is better.

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