Endoscopic ultrasound-guided fine-needle aspiration vs fine-needle biopsy for the diagnosis of pancreatic neuroendocrine tumors.
Published on Oct 22, 2019in Endoscopy International Open
· DOI :10.1055/A-0967-4684
Background and study aims Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) as a method of obtaining preoperative diagnosis of pancreatic neuroendocrine tumors (PanNETs) has been reported in several series. Fine-needle biopsies (FNB) are increasingly employed to obtain core specimens during EUS. However, the differences in efficacy between these sampling methods in the diagnosis of PanNETs still needs to be defined. Patients and methods Over a 13-year period, all patients who underwent EUS-guided tissue sampling of suspicious pancreatic lesions with clinical, endoscopic and pathologic details were entered into an electronic database. Lesions underwent EUS-FNA or FNB sampling, or a combination of the two. The accuracy and safety of different EUS-guided sampling methods for confirmed PanNETs were investigated. Results A total of 91 patients (M/F: 42/49, median age: 57 years), who underwent 102 EUS procedures had a final diagnosis of PanNET. Both EUS-guided sampling modalities were used in 28 procedures, EUS-FNA alone was used in 61 cases, while EUS-FNB alone in 13 cases. Diagnostic yield of EUS-FNA and EUS-FNB alone, including the inadequate specimens, was 77.5 % (95 %CI: 68.9 – 86.2 %) and 85.4 % (95 %CI: 74.6 – 96.2 %), respectively. The combination of both sampling modalities established the diagnosis in 96.4 % of cases (27/28) (95 %CI: 89.6 – 100 %), significantly superior to EUS-FNA alone (P = 0.023). Diagnostic sensitivity among the adequate samples for EUS-FNA, EUS-FNB and for the combination of the two methods was 88.4 % (95 %CI: 80.9 – 96.0 %), 94.3 % (95 %CI: 86.6 – 100 %) and 100 % (95 %CI: 100 – 100 %). There was one reported complication, a post-FNA bleeding, treated conservatively. Conclusions EUS-FNB improves diagnostic sensitivity and confers additional information to cytological assessment of PanNETs.