Fujiyoshi T1, Miyahara R1, Funasaka K1, Furukawa K1, Sawada T2, Maeda K2, Yamamura T2, Ishikawa T1, Ohno E1, Nakamura M1, Kawashima H1, Nakaguro M3, Nakatochi M4, Hirooka Y2.
World J Gastroenterol. 2019 Mar 14;25(10):1248-1258. doi: 10.3748/wjg.v25.i10.1248.
Background: Linked color imaging (LCI) is a method of endoscopic imaging that emphasizes slight differences in red mucosal color.
Aim: To evaluate LCI in diagnostic endoscopy of early gastric cancer and to compare LCI and pathological findings.
Methods: Endoscopic images were obtained for 39 patients (43 lesions) with early gastric cancer. Three endoscopists evaluated lesion recognition with white light imaging (WLI) and LCI. Color values in Commission Internationale de l’Eclairage (CIE) 1976 Lab* color space were used to calculate the color difference (ΔE) between cancer lesions and non-cancer areas. After endoscopic submucosal dissection, blood vessel density in the surface layer of the gastric epithelium was evaluated pathologically. The identical region of interest was selected for analyses of endoscopic images (WLI and LCI) and pathological analyses.
Results: LCI was superior for lesion recognition (P < 0.0001), and ΔE between cancer and non-cancer areas was significantly greater with LCI than WLI (29.4 vs 18.6, P < 0.0001). Blood vessel density was significantly higher in cancer lesions (5.96% vs 4.15%, P = 0.0004). An a* cut-off of ≥ 24 in CIE 1976 Lab* color space identified a cancer lesion using LCI with sensitivity of 76.7%, specificity of 93.0%, and accuracy of 84.9%.
Conclusion: LCI is more effective for recognition of early gastric cancer compared to WLI as a result of improved visualization of changes in redness. Surface blood vessel density was significantly higher in cancer lesions, and this result is consistent with LCI image analysis.
1 Department of Gastroenterology Hepatology, Nagoya University Graduate School of Medicine, Nagoya 4668550, Japan
2 Department of Endoscopy, Nagoya University Hospital, Nagoya 4668560, Japan
3 Department of Pathology and Laboratory Medicine, Nagoya University Hospital, Nagoya 4668560, Japan
4 Division of Data Science, Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Nagoya 4668560, Japan