BACKGROUND: The role of EUS for detection of pancreatic neuroendocrine tumors (PNETs) is not clearly defined in institutions that use multidetector CT for pancreatic imaging. OBJECTIVE: The aims of this study were to (1) compare the detection rates of EUS and CT by type and size of PNET and calculate the incremental benefit of EUS over CT, (2) evaluate the CT detection rate for PNETs adjusted for improved CT technology over time, and (3) determine the factors associated with CT-negative PNETs. DESIGN: Retrospective single-center cohort study. SETTING: Johns Hopkins Hospital. PATIENTS: Patients with pathologically proven PNETs with preoperative CT. Incidentally found PNETs (resection specimens) and those without Johns Hopkins Hospital CT imaging were excluded. MAIN OUTCOME MEASUREMENT: Detection rates of CT and EUS were compared by using pathology as the reference standard. RESULTS: In 217 patients (with 231 PNETs) studied, CT detected 84% of tumors (54.3% of insulinomas). The sensitivity of CT for the detection of PNETs significantly increased with improvement in CT technology (P = .02; χ(2) for trend). CT was more likely to miss lesions <2 cm (P = .005) and insulinomas (P < .0001). In 56 patients who had both CT and EUS, the sensitivity of EUS was greater than CT (91.7% vs 63.3%; P = .0002), particularly for insulinomas (84.2% vs 31.6%; P = .001). EUS detected 20 of 22 CT-negative tumors (91%). LIMITATIONS: Retrospective nonrandomized design and referral bias. CONCLUSIONS: The detection rate of CT has significantly improved over time. CT-negative tumors are small and more likely to be insulinomas. A sequential approach of CT followed by EUS can detect most PNETs. EUS is a more sensitive initial test for the detection of suspected insulinomas.
BACKGROUND: The role of EUS for detection of pancreatic neuroendocrine tumors (PNETs) is not clearly defined in institutions that use multidetector CT for pancreatic imaging. OBJECTIVE: The aims of this study were to (1) compare the detection rates of EUS and CT by type and size of PNET and calculate the incremental benefit of EUS over CT, (2) evaluate the CT detection rate for PNETs adjusted for improved CT technology over time, and (3) determine the factors associated with CT-negative PNETs. DESIGN: Retrospective single-center cohort study. SETTING: Johns Hopkins Hospital. PATIENTS: Patients with pathologically proven PNETs with preoperative CT. Incidentally found PNETs (resection specimens) and those without Johns Hopkins Hospital CT imaging were excluded. MAIN OUTCOME MEASUREMENT: Detection rates of CT and EUS were compared by using pathology as the reference standard. RESULTS: In 217 patients (with 231 PNETs) studied, CT detected 84% of tumors (54.3% of insulinomas). The sensitivity of CT for the detection of PNETs significantly increased with improvement in CT technology (P = .02; χ(2) for trend). CT was more likely to miss lesions <2 cm (P = .005) and insulinomas (P < .0001). In 56 patients who had both CT and EUS, the sensitivity of EUS was greater than CT (91.7% vs 63.3%; P = .0002), particularly for insulinomas (84.2% vs 31.6%; P = .001). EUS detected 20 of 22 CT-negative tumors (91%). LIMITATIONS: Retrospective nonrandomized design and referral bias. CONCLUSIONS: The detection rate of CT has significantly improved over time. CT-negative tumors are small and more likely to be insulinomas. A sequential approach of CT followed by EUS can detect most PNETs. EUS is a more sensitive initial test for the detection of suspected insulinomas.
Authors: Srinivas R Puli; Nikhil Kalva; Matthew L Bechtold; Smitha R Pamulaparthy; Micheal D Cashman; Norman C Estes; Richard H Pearl; Fritz-Henry Volmar; Sonu Dillon; Michael F Shekleton; David Forcione Journal: World J Gastroenterol Date: 2013-06-21 Impact factor: 5.742
Authors: Ibironke Oduyebo; Joanna K Law; Atif Zaheer; Matthew J Weiss; Christopher Wolfgang; Anne Marie Lennon Journal: Surg Endosc Date: 2014-12-10 Impact factor: 4.584
Authors: James R Eshleman; Alexis L Norris; Yoshihiko Sadakari; Marija Debeljak; Michael Borges; Colleen Harrington; Elaine Lin; Aaron Brant; Thomas Barkley; J Alejandro Almario; Mark Topazian; James Farrell; Sapna Syngal; Jeffrey H Lee; Jun Yu; Ralph H Hruban; Mitsuro Kanda; Marcia Irene Canto; Michael Goggins Journal: Clin Gastroenterol Hepatol Date: 2014-12-04 Impact factor: 11.382