Abstract
ObjectivesTo construct a nomogram model that combines clinical characteristics and radiomics signatures to preoperatively discriminate pancreatic ductal adenocarcinoma (PDAC) in stage I-II and III-IV and predict overall survival.MethodsA total of 135 patients with histopathologically confirmed PDAC who underwent contrast-enhanced CT were included. A total of 384 radiomics features were extracted from arterial phase (AP) or portal venous phase (PVP) images. Four steps were used for feature selection, and multivariable logistic regression analysis were used to build radiomics signatures and combined nomogram model. Performance of the proposed model was assessed by using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Kaplan-Meier analysis was applied to analyze overall survival in the stage I-II and III-IV PDAC groups.ResultsThe AP+PVP radiomics signature showed the best performance among the three radiomics signatures [training cohort: area under the curve (AUC) = 0.919; validation cohort: AUC = 0.831]. The combined nomogram model integrating AP+PVP radiomics signature with clinical characteristics (tumor location, carcinoembryonic antigen level, and tumor maximum diameter) demonstrated the best discrimination performance (training cohort: AUC = 0.940; validation cohort: AUC = 0.912). Calibration curves and DCA verified the clinical usefulness of the combined nomogram model. Kaplan-Meier analysis showed that overall survival of patients in the predicted stage I-II PDAC group was longer than patients in stage III-IV PDAC group (p<0.0001).ConclusionsWe propose a combined model with excellent performance for the preoperative, individualized, noninvasive discrimination of stage I-II and III-IV PDAC and prediction of overall survival.
Highlights
Pancreatic cancer is the fourth most common cause of cancerrelated death in the United States, with a 5-year survival rate of 9.3% [1]
The arterial phase (AP)+portal venous phase (PVP) radiomics signature showed the best performance among the three radiomics signatures [training cohort: area under the curve (AUC) = 0.919; validation cohort: AUC = 0.831]
Kaplan-Meier analysis showed that overall survival of patients in the predicted stage I-II Pancreatic ductal adenocarcinoma (PDAC) group was longer than patients in stage III-IV PDAC group (p
Summary
Pancreatic cancer is the fourth most common cause of cancerrelated death in the United States, with a 5-year survival rate of 9.3% [1]. The number of new pancreatic cancer cases in the United States is expected to reach 56,770, with 45,750 deaths, by the end of 2019 [2]. Complete surgical resection is the only potentially curative treatment for PDAC. Accurate cancer staging plays a critical role in predicting prognosis and choosing a suitable treatment option for patients with PDAC. For most PDAC patients, an accurate cancer stage can be confirmed only by a postoperative histopathologic examination; a preoperative, noninvasive and accurate method is still urgently needed
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