The diagnostic performance of an [18F]FDG PET/CT algorithm for preoperative evaluation of extrahepatic cholangiocarcinoma: a retrospective study.

Abstract

In this retrospective study, we evaluated the diagnostic value of [¹⁸F]FDG PET/CT in preoperative assessment of extrahepatic cholangiocarcinoma (ECC) and to develop a PET-based diagnostic algorithm for ECC.Patients with suspected ECC with biliary obstruction were included. Patients received [¹⁸F]FDG PET/CT scan and image analysis. FDG uptake was semi-quantified using the SUV_max of the suspected primary tumor, lymph nodes and metastatic lesions. Sex, age, tumor location, enhancement patterns and tumor size were analyzed using binary logistic regression for prediction of ECC on PET images.The study included 238 ECC patients and 42 patients with benign diseases. The lesion was located in the common bile duct in 67.50% patients and in the hilar region in 31.79% patients. [¹⁸F]FDG PET/CT scan showed a sensitivity of 70.6% and a specificity of 76.2% for the diagnosis of cholangiocarcinoma in patients with extrahepatic lesions, with a positive predictive value of 94.4% and a negative predictive value of 31.4% and an accuracy of 71.4%. Forced entry logistic regression analysis showed that age (OR 1.07, 95%CI, 1.03 to 1.10) and detection of ECC by [¹⁸F]FDG PET/CT scan (OR 6.15, 95% CI, 2.00 to 19.10) were predictors of ECC. A PET-based scoring algorithm had an AUC of 0.81 (95% CI, 0.75 to 0.88) and had a sensitivity of 61.3% and a specificity of 88.1% for ECC. The algorithm had a significantly better diagnostic performance than [¹⁸F]FDG PET/CT scan (Chi square test, P <0.001).The PET-based algorithm shows improved diagnostic performance for the detection of ECC and could facilitate early diagnosis and staging of ECC.