Accuracy of ultrasound in diagnosing gallbladder polyps at a community hospital

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Abstract

Background and Objectives: Polyps are reported on 1–10% of routine transabdominal ultrasound studies of the gallbladder. Prior studies have reported poor sensitiv-ity and specificity for this diagnostic modality at deter-mining malignant potential of polyps. The aim of this study is to determine the incidence of gallbladder polyps documented on ultrasound at a community hospital, eval-uate the congruency of ultrasound with final histopathol-ogy, and explore factors which may improve ultrasound accuracy at diagnosing true adenomatous polyps. Methods: We conducted a 5-year retrospective cohort study of patients undergoing cholecystectomy at Danbury Hospital between 2014 and 2019, identifying those with a pre-operative ultrasound mention of a “polyp” or “mass.” We assessed the congruency of ultrasound findings with pathology reports. Results: Of the 2,549 cholecystectomies performed, 1,944 (76%) had pre-operative ultrasounds. Of those, 98 (5.0%) reported a polyp, measuring an average of 8.1 mm (SD 7.1 mm). Three (3.1%) specimens were identified as adenomas on final histopathology; the majority were benign pathologies including cholesterol polyp (18), cholesterolosis (20), adenomyoma (4), adenomyo-matosis (7), and chronic or acute cholecystitis (44). Interestingly, only 1 of the 3 adenomas measured > 10 mm on ultrasound, the accepted indication for surgical resection. Conclusions: The accuracy of transabdominal ultrasound in diagnosing true polyps is poor, with only 3% of polyps identified as adenomas based on pathology. Surgeons should use caution when making clinical deci-sions based on polyps identified on ultrasound, and more stringent diagnostic criteria are needed in order to decrease the false positive rate for diagnosis and screening.

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APA

Ostapenko, A., Liechty, S., Kim, M., & Kleiner, D. (2020). Accuracy of ultrasound in diagnosing gallbladder polyps at a community hospital. Journal of the Society of Laparoscopic and Robotic Surgeons, 24(4), 1–5. https://doi.org/10.4293/JSLS.2020.00052

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