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Usefulness of cold polypectomy under linked color imaging
Background and study aims Cold polypectomy is becoming popular for treatment of colon polyps due to its safety and convenience, but there is still the problem of tumor remnants. Because linked color imaging (LCI) improves polyp visibility, cold polypectomy under LCI is anticipated to reduce the tum...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
© Georg Thieme Verlag KG
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949179/ https://www.ncbi.nlm.nih.gov/pubmed/31921990 http://dx.doi.org/10.1055/a-1035-9411 |
Sumario: | Background and study aims Cold polypectomy is becoming popular for treatment of colon polyps due to its safety and convenience, but there is still the problem of tumor remnants. Because linked color imaging (LCI) improves polyp visibility, cold polypectomy under LCI is anticipated to reduce the tumor remnant rate. Therefore, we investigated the usefulness of this procedure. Patients and methods Fifty patients scheduled to undergo cold polypectomy for treatment of colon polyps < 10 mm and assumed to be adenomas were registered prospectively. After performing cold snare polypectomy (CSP) under LCI, biopsy was performed at two resection margin sites for each polyp to determine the tumor remnant rate. Results A total of 145 lesions were treated by CSP. Of the 139 lesions in which polyps were retrievable and diagnosed as adenomas pathologically, one lesion was recognized as a remnant adenoma on biopsy (remnant rate: 0.7 % [95 % CI: 0.0–4.4]). This remnant rate was extremely low. Treatment results were extremely promising given that en bloc resection, post-procedure bleeding, and perforation rates were 100 %, 0 %, and 0 %, respectively. Conclusion Cold snare polypectomy under LCI may be an effective treatment method capable of reducing the tumor remnant rate. This trial was approved by our Institutional Ethics Committee and registered at the University Hospital Medical Information Network (UMIN 000033690). |
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