ArticleBMC gastroenterology2025
Linked color imaging for detection and characterization of gastrointestinal neuroendocrine tumors.
Article in BMC gastroenterology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
BACKGROUND AND
aimsThe endoscopic detection of gastrointestinal neuroendocrine tumors (GI-NETs) remains clinically challenging. Linked color imaging (LCI), which enhances color contrast, may improve the identification of tumorous lesions. This study aims to evaluate the endoscopic characteristics of GI-NETs using LCI in comparison with white light imaging (WLI).
methodsWe retrospectively reviewed two pictures both with WLI and LCI for consecutive patients with GI-NETs who underwent endoscopic resection at our center. The endoscopic features and clinic characteristics were analyzed. The edges of lesions were identified using the Canny operator, and color differences (∆E) between lesions and surrounding mucosa in gastric and rectal NETs were measured using the CIE Lab* color space(CIE: Commission Internationale d'Eclairage). Three expert endoscopists and three non-experts independently assessed LCI and WLI images using a validated visibility scores scale.
resultsSixty patients were included in the analysis. The average ∆E values for LCI were significantly higher than those for WLI in both gastric and rectal NETs (P < 0.05). In rectal NETs, the increased contrast was predominantly driven by enhancement of the yellow-blue component (b*) (P < 0.001). LCI provided superior delineation of lesion edges and more detailed visualization compared to WLI. LCI significantly improves the visibility scores of GI-NETs compared to WLI among non-expert endoscopists (P < 0.001).
conclusionLCI significantly improves the endoscopic visibility of GI-NETs by enhancing color contrast between lesions and surrounding mucosa and optimizing edges visualization. These benefits may allow easy recognition of GI-NETs even for non-experts, suggesting that LCI may be a valuable tool for enhancing the endoscopic detection and characterization of GI-NETs.
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