PURPOSE: To assess the ability of 18F-FDG PET/CT alone or combined with CA19-9 to diagnose pancreatic cancer and to analyze the correlation between maximal standardized uptake value (SUVmax) and clinical characteristics. METHODS: Ninety-one patients diagnosed with pancreatic cancer using 18F-FDG PET/CT before treatment were analyzed. Definite diagnosis was by histology or cytology. The SUVmax of the primary tumor was used for the statistical analysis and, using the best cutoff value, the patients were divided into 2 groups: a high SUVmax group (SUV- max-5.49) and a low SUVmax group (SUVmax≤5.49). Logistic regression analysis and receiver operating characteristic (ROC) analysis were applied to analyze the effects of SUVmax and/or CA19-9 on the diagnosis of pancreatic cancer. RESULTS: Of 91 patients, 80 had pancreatic cancer and 11 had benign conditions. The ROC curve analysis of the SUVmax yielded a best cutoff value of 5.49. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of ¹⁸F-FDG PET/CT alone in the diagnosis of pancreatic cancer were 67.5, 72.73, 94.74, 23.53, and 68.13%, respectively, while these indices for ¹⁸F-FDG PET/CT combined with CA19-9 increased to 96.25, 63.64, 95.06, 70, and 92.31%, respectively. The area under the curve (AUC) of the SUVmax combined with CA19-9 was 0.94, which was significantly higher than that of the SUVmax or CA19-9 alone (p<0.05). The SUVmax value and CA19-9 levels in pancreatic cancer patients were significantly higher than those with benign conditions (p<0.05). Only the SUVmax in the pancreatic cancer patient group was associated with tumor size (p<0.05). CONCLUSIONS: 18F-FDG PET/CT is a common examination for diagnosing pancreatic cancer, and the SUVmax combined with the CA19-9 level can significantly improve the sensitivity and accuracy in the diagnosis of pancreatic cancer. SUVmax is merely indicative of the volume of pancreatic cancer.
PURPOSE: To assess the ability of 18F-FDG PET/CT alone or combined with CA19-9 to diagnose pancreatic cancer and to analyze the correlation between maximal standardized uptake value (SUVmax) and clinical characteristics. METHODS: Ninety-one patients diagnosed with pancreatic cancer using 18F-FDG PET/CT before treatment were analyzed. Definite diagnosis was by histology or cytology. The SUVmax of the primary tumor was used for the statistical analysis and, using the best cutoff value, the patients were divided into 2 groups: a high SUVmax group (SUV- max-5.49) and a low SUVmax group (SUVmax≤5.49). Logistic regression analysis and receiver operating characteristic (ROC) analysis were applied to analyze the effects of SUVmax and/or CA19-9 on the diagnosis of pancreatic cancer. RESULTS: Of 91 patients, 80 had pancreatic cancer and 11 had benign conditions. The ROC curve analysis of the SUVmax yielded a best cutoff value of 5.49. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of ¹⁸F-FDG PET/CT alone in the diagnosis of pancreatic cancer were 67.5, 72.73, 94.74, 23.53, and 68.13%, respectively, while these indices for ¹⁸F-FDG PET/CT combined with CA19-9 increased to 96.25, 63.64, 95.06, 70, and 92.31%, respectively. The area under the curve (AUC) of the SUVmax combined with CA19-9 was 0.94, which was significantly higher than that of the SUVmax or CA19-9 alone (p<0.05). The SUVmax value and CA19-9 levels in pancreatic cancerpatients were significantly higher than those with benign conditions (p<0.05). Only the SUVmax in the pancreatic cancerpatient group was associated with tumor size (p<0.05). CONCLUSIONS:18F-FDG PET/CT is a common examination for diagnosing pancreatic cancer, and the SUVmax combined with the CA19-9 level can significantly improve the sensitivity and accuracy in the diagnosis of pancreatic cancer. SUVmax is merely indicative of the volume of pancreatic cancer.
Authors: Jing Huang; Jianzhou Liu; Kevin Chen-Xiao; Xuemei Zhang; W N Paul Lee; Vay Liang W Go; Gary Guishan Xiao Journal: Biomark Res Date: 2016-10-22
Authors: Hwaida M Mokhtar; Amira Youssef; Tamer M Naguib; Amr A Magdy; Samir A Salama; Ahmed M Kabel; Nesreen M Sabry Journal: Medicina (Kaunas) Date: 2022-08-01 Impact factor: 2.948
Authors: Yongzhu Pu; Chun Wang; Sheng Zhao; Ran Xie; Lei Zhao; Kun Li; Conghui Yang; Rui Zhang; Yadong Tian; Lixian Tan; Jindan Li; Shujuan Li; Long Chen; Hua Sun Journal: Transl Cancer Res Date: 2021-07 Impact factor: 1.241