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Clinical significance and influencing factors of linked color imaging technique in real-time diagnosis of active Helicobacter pylori infection.

Wang L1, Lin XC1, Li HL1, Yang XS1, Zhang L1, Li X1, Bai P1, Wang Y1, Fan X1, Ding YM1.

Chin Med J (Engl). 2019 Oct 22. doi: 10.1097/CM9.0000000000000486. [Epub ahead of print]

Background: Determining the Helicobacter pylori (H. pylori) infection state during the gastroscopic process is important but still challenging. The linked color imaging (LCI) technique might emphasize the mucosal color change after H. pylori infection, which might help the diagnosis. In the present study, we aimed to compare the LCI technique with traditional white light imaging (WLI) endoscopy for diagnosing active H. pylori infection.

Methods: We collected and analyzed gastroscopic images from 103 patients in our hospital from November 2017 to March 2018, including both LCI and WLI modes. All images were randomly disordered and independently evaluated by four endoscopists who were blinded to the H. pylori status of patients. In addition, the H. pylori state was determined by both rapid urease test and pathology staining. The sensitivity, specificity, positive prediction value (PPV), and negative prediction value (NPV) were calculated for the detection of H. pylori infection. Moreover, the kappa value and interclass correlation coefficient (ICC) were used to evaluate the inter-observer variety by SPSS 24.0 software.

Results: Of the 103 enrolled patients, 27 of them were positive for H. pylori infection, while the 76 patients were negative. In total, 388 endoscopic images were selected, including 197 WLI and 191 LCI. The accuracy rate for H. pylori evaluation in the corpus LCI group was significantly higher than other groups (81.2% vs. 64.3%-76.5%, χ = 34.852, P < 0.001). Moreover, the corpus LCI group had the optimal diagnostic power with the sensitivity of 85.41% (95% confidence interval [CI]: 76.40%-91.51%), the specificity of 79.71% (95% CI: 74.38%-84.19%), the PPV of 59.42% (95% CI: 50.72%-67.59%), and the NPV of 94.02% (95% CI: 89.95%-96.56%), respectively. The kappa values between different endoscopists were higher with LCI than with WLI (0.433-0.554 vs. 0.331-0.554). Consistently, the ICC value was also higher with LCI than with WLI (0.501 [95% CI: 0.429-0.574] vs. 0.397 [95% CI: 0.323-0.474]). We further analyzed the factors that might lead to misjudgment, revealing that active inflammation might disturb WLI judgment (accuracy rate: 58.70% vs. 76.16%, χ = 21.373, P < 0.001). Atrophy and intestinal metaplasia might affect the accuracy of the LCI results (accuracy rate: 66.96% vs. 73.47%, χ = 2.027; 68.42% vs. 73.53%, χ = 1.594, respectively); however, without statistical significance (P = 0.154 and 0.207, respectively).

Conclusions: The application of LCI at the corpus to identify H. pylori infection is reliable and superior to WLI. The inter-observer variability is lower with LCI than with WLI.

1 Department of Gastroenterology, Peking University International Hospital, Beijing 102206, China.

Evaluation of the impact of linked color imaging for improving the visibility of colonic polyp.

Tanaka Y1, Inoue T1,2, Kakimoto K1, Nakazawa K1, Tawa H1, Hirata Y1, Okada T1, Nouda S1, Kawakami K1, Takeuchi T1, Egashira Y3, Higuchi K1.

Oncol Lett. 2019 Nov;18(5):5555-5560. doi: 10.3892/ol.2019.10917. Epub 2019 Sep 24.

Linked color imaging (LCI) is a novel endoscopic system used to increase color contrast. As LCI does not decrease luminal brightness, it may improve the detection of colonic neoplasms. However, the extent to which LCI improves the visibility of colonic polyps has not yet been determined. Between December 2016 and May 2017, patients who received total colonoscopy were consecutively recruited into this retrospective, single-center study. For each polyp identified, images obtained from white light (WL) imaging, blue laser imaging (BLI), and LCI of the same lesion and its surrounding mucosa were evaluated. The color differences (ΔE) between each lesion and its surrounding mucosa in non-magnified images were computed quantitatively using the CIELAB color space, which defines color perception according to colorimetric values, and compared among WL, BLI, LCI, and chromoendoscopy. The ΔE between the vessel and non-vessel areas in magnified images was also assessed. Of the 64 patients who were incorporated into this study, non-magnified and magnified (×80) images from 113 and 95 polyps, respectively, were assessed. The ΔE was intensified by LCI and chromoendoscopy compared with WL and BLI. The ΔE of neoplastic lesions was also intensified by LCI. In magnified images, BLI and LCI significantly increased the ΔE between the vessel and non-vessel areas compared with WL. Luminal brightness, indicated by L*, was not impaired by LCI; however, was reduced by BLI compared with WL and LCI. These results suggest that LCI enhanced the detection of colonic neoplasms without impairing luminal brightness. We propose the routine use of LCI for colonic polyp detection and BLI for magnifying observations of colonic polyps detected by LCI.

1 Second Department of Internal Medicine, Osaka Medical College, Takatsuki, Osaka 569-8686;
2 Department of Gastroenterology, Inoue Gastroenterology and Endoscopy Clinic, Osaka 595-0072;
3 Department of Pathology, Osaka Medical College, Takatsuki, Osaka 569-8686, Japan

A prospective randomized study of colonoscopy using blue laser imaging and white light imaging in detection and differentiation of colonic polyps.

Ang TL1, Li JW1, Wong YJ1, Tan YJ1, Fock KM1, Tan MTK1, Kwek ABE1, Teo EK1, Ang DS1, Wang LM2.

Endosc Int Open. 2019 Oct;7(10):E1207-E1213. doi: 10.1055/a-0982-3111. Epub 2019 Oct 1.

Background and study aims: Published data on blue laser imaging (BLI) for detection and differentiation of colonic polyps are limited compared to narrow band imaging (NBI). This study investigated whether BLI can increase the detection rate of colonic polyps and adenomas when compared to white light imaging (WLI), and examined use of NICE (NBI International Colorectal Endoscopic) and JNET (Japan NBI Expert Team) classifications with BLI.

Patients and methods: Patients aged 50 years and above referred for colonoscopy were randomized to BLI or WLI on withdrawal. Detected polyps were characterized using NICE and JNET classifications under BLI mode and correlated with histology. Primary outcome was adenoma detection rate. Secondary outcomes were utility of NICE and JNET classifications to predict histology using BLI.

Results: A total of 182 patients were randomized to BLI (92) or WLI (90). Comparing BLI with WLI, the polyp detection rate was 59.8 % vs 40.0 %, P  = 0.008, and the adenoma detection rate was 46.2 % vs 27.8 %, P  = 0.010. NICE 1 and JNET 1 diagnosed hyperplastic polyps with sensitivity of 87.18 % and specificity of 84.35 %. NICE 2 diagnosed low- (LGD) or high-grade dysplasia (HGD) with sensitivity of 92.31 % and specificity of 77.45 %. JNET 2A diagnosed LGD with sensitivity of 91.95 %, and specificity of 74.53 %. Four cases of focal HGD all had JNET 2A morphology.

Conclusion: BLI increased adenoma detection rate compared to WLI. NICE and JNET classifications can be applied when using BLI for endoscopic diagnosis of HP and LGD but histological confirmation remains crucial.

1 Department of Gastroenterology and Hepatology, Changi General Hospital
2 Department of Laboratory Medicine, Changi General Hospital

Development and validation of the international blue-light imaging for Barrett’s neoplasia classification.

Subramaniam S1, Kandiah K1, Schoon E2, Aepli P3, Hayee B4, Pischel A5, Stefanovic M6, Alkandari A7, Coron E8, Omae M9, Baldaque-Silva F9, Maselli R10, Bisschops R11, Sharma P12, Repici A10, Bhandari P1.

Gastrointest Endosc. 2019 Oct 3. pii: S0016-5107(19)32302-8. doi: 10.1016/j.gie.2019.09.035. [Epub ahead of print]

Background and aims: Detecting subtle Barrett’s neoplasia during surveillance endoscopy can be challenging. Blue-light imaging (BLI) is a novel advanced endoscopic technology with high intensity contrast imaging which may improve the identification of Barrett’s neoplasia. The aim of this study was to develop and validate the first classification to enable characterisation of neoplastic and non-neoplastic Barrett’s using BLI.

Methods: In phase 1, descriptors pertaining to neoplastic and non-neoplastic Barrett’s were identified to form the classification (BLINC). Phase 2 involved validation of these component criteria by 10 expert endoscopists assessing 50 BLI images. In phase 3, a web-based training module was developed to enable 15 general (nonexpert) endoscopists to use BLINC. They then validated the classification with an image assessment exercise in phase 4 and their pre- and post-training results were compared.

Results: In Phase 1, the descriptors were grouped into color, pit, and vessel pattern categories to form the classification. In Phase 2, the sensitivity of neoplasia identification was 96.0% with a very good level of agreement among the experts (K=0.83). In Phase 3, 15 general endoscopists completed the training module. In Phase 4, their pretraining sensitivity (85.3%) improved significantly to 95.7% post-training with a good level of agreement (K=0.67).

Conclusion: We developed and validated a new classification system (BLINC) for the optical diagnosis of Barrett’s neoplasia using BLI. Despite the limitations of this image-based study with a high prevalence of neoplasia, we believe it has the potential to improve the optical diagnosis of Barrett’s neoplasia given the high degree of sensitivity (96%) noted. It is also a promising tool for training in Barrett’s optical diagnosis using BLI.

1 Department of Gastroenterology, Queen Alexandra Hospital, Portsmouth, UK
2 Department of Gastroenterology, Catharina Hospital, Eindhoven, Netherlands
3 Department of Gastroenterology & Hepatology, Luzerner Kantonsspital, Luzerne, Switzerland
4 Department of Gastroenterology, King’s College Hospital NHS Foundation Trust, London, UK
5 Department of Gastroenterology, Sahlgrenska University Hospital, Gothenburg, Sweden
6 Department of Gastroenterology, DC Bled, Ljubljana, Slovenia
7 Department of Gastroenterology & Hepatology, Aljahra Hospital, Kuwait
8 Centre Hospitalier Universitaire & Faculté de Médecine de Nantes, Institut des Maladies de l’Appareil Digestif, France
9 Centre for Digestive Diseases, Karolinska University Hospital, Stockholm, Sweden
10 Digestive Endoscopy Unit, Humanitas Research Hospital, Milan, Italy
11 Department of Gastroenterology & Hepatology, Universitaire Ziekenhuizen Leuven, Belgium
12 Department of Gastroenterology & Hepatology, Kansas University Medical Center, Kansas, USA

Predictive rules for optical diagnosis of < 10-mm colorectal polyps based on a dedicated software.

Hassan C1, Bisschops R2, Bhandari P3, Coron E4, Neumann H5, Pech O6, Correale L1, Repici A7.

Endoscopy. 2019 Sep 13. doi: 10.1055/a-0995-0084. [Epub ahead of print]

Background: The BASIC classification for predicting in vivo colorectal polyp histology incorporates both surface and pit/vessel descriptor domains. This study aimed to define new BASIC classes for adenomatous and hyperplastic polyps.

Methods: A video library (102 still images/videos of < 10-mm polyps using white-light [WLI] and blue-light imaging [BLI]) was reviewed by seven expert endoscopists. Polyps were rated according to the individual descriptors of the three BASIC domains (surface/pit/vessel). A model to predict polyp histology (adenomatous or hyperplastic) was developed using multivariable logistic regression and subsequent “leave-one-out” cross-validation. New BASIC rules were then defined by Delphi agreement. The overall accuracy of these rules when used by experts was evaluated according to the level of confidence and light type.

Results: The strength of prediction for adenomatous histology from 2175 observations assessed by area under the curve (AUC; 95 % confidence interval) was poor-to-fair for the surface descriptors (0.50 [0.33 - 0.69] for mucus; 0.68 [0.57 - 0.79] for irregular surface), but stronger for pits (0.87 [0.80 - 0.96] for featureless/round/not round) and vessels (0.80 [0.65 - 0.87] for not present/lacy/pericryptal). By combining the domains, a good-to-excellent prediction was shown (AUC 0.89 [0.81 - 0.96]). After the definition of new BASIC rules for adenomatous and hyperplastic polyps, accuracy for high confidence BLI predictions was 90.3 % (86.3 % - 93.2 %), which was superior to high confidence WLI (83.7 % [77.3 % - 87.7 %]) and low confidence BLI predictions (77.7 % [61.1 % - 88.6 %]).

Conclusions: Based on the strength of prediction, the new BASIC classes for adenomatous and hyperplastic histology show favorable results for accuracy and confidence levels.

1 Department of Gastroenterology, Nuovo Regina Margherita Hospital, Rome, Italy
2 Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospitals Leuven, Leuven, Belgium
3 Solent Centre for Digestive Diseases, Portsmouth Hospital, Portsmouth, United Kingdom
4 Department of Hepatogastroenterology, Centre Hospitalier Universitaire Hotel Dieu, Nantes, France
5 First Medical Department, University Medical Center Mainz, Mainz, Germany
6 Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
7 Digestive Endoscopy Unit, Humanitas University, Milan, Italy

New Diagnostic Approach for Esophageal Squamous Cell Neoplasms Using Linked Color Imaging and Blue Laser Imaging Combined with Iodine Staining.

Tsunoda M1, Miura Y1, Osawa H1, Khurelbaatar T1, Sakaguchi M2, Fukuda H1, Lefor AK3, Yamamoto H1.

Clin Endosc. 2019 Apr 16. doi: 10.5946/ce.2018.195. [Epub ahead of print]

62-year-old man with a flat early esophageal cancer was referred for endoscopic treatment. White light imaging revealed a pale red lesion, whereas linked color imaging (LCI) and blue laser imaging (BLI) yielded purple and brown images, respectively. Iodine staining demonstrated a large unstained area with a homogenous but very weak pink-color sign. This area appeared more clearly as purple and green on LCI and BLI, respectively; however, a different colored portion was observed at the 4 o’clock position inside the iodineunstained area. Histopathology findings of the resected specimen revealed squamous intraepithelial neoplasia at the 4 o’clock position and an esophageal squamous cell carcinoma in the remaining iodine-unstained area. LCI and BLI combined with iodine staining produce characteristic images that overcomes the pink-color sign, reflecting the histological features of a flat esophageal neoplasm. This new method is useful for detailed evaluation of early flat squamous cell neoplasms.

1 Division of Gastroenterology, Department of Medicine
2 Department of Diagnostic Pathology
3 Department of Surgery, Jichi Medical University, Shimotsuke, Japan