CC BY-NC-ND 4.0 · Endosc Int Open 2024; 12(07): E924-E931
DOI: 10.1055/a-2350-9631
Original article

Value of green sign and chicken skin aspects for detecting malignancy of colorectal neoplasia in a prospective characterization study

1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Jérôme Rivory
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Alexandru Lupu
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Florian Rostain
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Jeremie Jacques
2   Gastroenterology Department, CHU Dupuytren, Limoges, France
,
Thimothee Wallenhorst
3   Gastroenterology Department, CHU Rennes, Rennes, France (Ringgold ID: RIN36684)
,
Adrien Bartoli
4   EnCoV, Institut Pascal, UMR 6602, CNRS/UCA/SIGMA, Clermont-Ferrand, France
5   Department of Clinical Research and Innovation, University Hospital Centre Clermont-Ferrand, Clermont-Ferrand, France (Ringgold ID: RIN55174)
,
Serge Torti
6   Yansys Medical, Vichy, France
,
Tanguy Fenouil
7   Institute of Pathology Est, Hospices Civils de Lyon, Lyon, France
,
Frederic Moll
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Fabien Subtil
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
,
Mathieu Pioche
1   Gastroenterology Department, Edouard Herriot Hospital, Lyon, France (Ringgold ID: RIN36609)
› Author Affiliations

Abstract

Background and study aims Accurate endoscopic characterization of colorectal lesions is essential for predicting histology but is difficult even for experts. Simple criteria could help endoscopists to detect and predict malignancy. The aim of this study was to evaluate the value of the green sign and chicken skin aspects in detection of malignant colorectal neoplasia.

Patients and methods We prospectively characterized and evaluated the histology of all consecutive colorectal lesions detected during screening or referred for endoscopic resection (Pro-CONECCT study). We evaluated the diagnostic accuracy of the green sign and chicken skin aspects for detection of superficial and deep invasive lesions.

Results 461 patients with 803 colorectal lesions were included. The green sign had a negative predictive value of 89.6% (95% confidence interval [CI] 87.1%–91.8%) and 98.1% (95% CI 96.7%-99.0%) for superficial and deep invasive lesions, respectively. In contrast to chicken skin, the green sign showed additional value for detection of both lesion types compared with the CONECCT classification and chicken skin (adjusted odds ratio [OR] for superficial lesions 5.9; 95% CI 3.4–10.2; P <0.001), adjusted OR for deep lesions 9.0; 95% CI 3.9–21.1; P <0.001).

Conclusions The green sign may be associated with malignant colorectal neoplasia. Targeting these areas before precise analysis of the lesion could be a way of improving detection of focal malignancies and prediction of the most severe histology.



Publication History

Received: 01 March 2024

Accepted after revision: 13 June 2024

Accepted Manuscript online:
24 June 2024

Article published online:
25 July 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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  • References

  • 1 Fabritius M, Gonzalez J-M, Becq A. et al. A simplified table using validated diagnostic criteria is effective to improve characterization of colorectal polyps: the CONECCT teaching program. Endosc Int Open 2019; 7: E1197-E1206
  • 2 Bonniaud P, Jacques J, Lambin T. et al. Endoscopic characterization of colorectal neoplasia with different published classifications: comparative study involving CONECCT classification. Endosc Int Open 2022; 10: E145-E153
  • 3 Brule C, Pioche M, Albouys J. et al. The COlorectal NEoplasia Endoscopic Classification to Choose the Treatment classification for identification of large laterally spreading lesions lacking submucosal carcinomas: A prospective study of 663 lesions. United European Gastroenterol J 2022; 10: 80-92
  • 4 Lafeuille P, Fenouil T, Bartoli A. et al. Green-colored areas in laterally spreading tumors on narrow-band imaging: a future target for artificial-intelligence-assisted detection of malignancies?. Endoscopy 2022; 54: E215-E216
  • 5 Shatz BA, Weinstock LB, Thyssen EP. et al. Colonic chicken skin mucosa: an endoscopic and histological abnormality adjacent to colonic neoplasms. Am J Gastroenterol 1998; 93: 623-627
  • 6 Lee YM, Song KH, Koo HS. et al. Colonic chicken skin mucosa surrounding colon polyps is an endoscopic predictive marker for colonic neoplastic polyps. Gut Liver 2022; 16: 754-763
  • 7 Ueno H, Mochizuki H, Hashiguchi Y. et al. Risk factors for an adverse outcome in early invasive colorectal carcinoma. Gastroenterology 2004; 127: 385-394
  • 8 Hashiguchi Y, Muro K, Saito Y. et al. Japanese Society for Cancer of the Colon and Rectum (JSCCR) guidelines 2019 for the treatment of colorectal cancer. Int J Clin Oncol 2020; 25: 1-42
  • 9 Hassan C, Spadaccini M, Iannone A. et al. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc 2021; 93: 77-85.e6
  • 10 Lafeuille P, Lambin T, Yzet C. et al. Flat colorectal sessile serrated polyp: an example of what artificial intelligence does not easily detect. Endoscopy 2022; 54: 520-521
  • 11 Gono K. Narrow band imaging: Technology basis and research and development history. Clin Endosc 2015; 48: 476-480