Abstract
BACKGROUND AND OBJECTIVES: The most accurate technology to detect and diagnose subepithelial tumors (SETs) is the endoscopic ultrasonography (EUS) combined with puncture techniques, such as the endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) or the endoscopic ultrasonography-guided fine-needle biopsy. Going further in the improvement of the results of tumor samples obtained endoscopically to diagnose the SETs, the canalization technique guided by miniprobes (MPs) to obtain biopsies of SET could be an alternative to EUS-FNA. The objective of this study is to analyze the results of samples obtained by this procedure. MATERIALS AND METHODS: A multicenter, retrospective study of a review of a database of 32 consecutive patients with a SET in the digestive tract, from 2000 to 2015 was conducted. All patients underwent EUS-performed by MP, to define the size, internal echostructure, and layer of origin of tumor. Once the echostructure was defined, it proceeded to the canalization technique to arrive to the tumor tissue. RESULTS: The average diameter of SETs in this series (32 patients) was about 21.6±11 mm (range: 5-41 mm). The diagnostic accuracy was 28/32, 87.50% (Confidence interval 95%: 76.04%-98.99%), and there were no major complications. All procedures were performed on outpatients, none of which required additional hospitalization. The 50% of patients were operated or endoscopically resected and in all cases, the previous pathological diagnosis was confirmed. CONCLUSIONS: This is a feasible, safe, and effective procedure that allows to access to inside of SET to obtain deep biopsies. Tumor samples obtained by deep biopsy, with prior performing of the canalization technique guided by MP, were sufficient for histopathological and immunohistochemical diagnosis and similar to those obtained with other known methods (FNA Trucut, ProCore(®), etc.). However, more prospective comparative studies with a larger number of patients and different specialists carrying out the procedure to reach a higher statistical significance are necessary.