First report from the International Evaluation of Endoscopic classification Japan NBI Expert Team: International multicenter web trial.

OBJECTIVES: Narrow-band imaging (NBI) contributes to real-time optical diagnosis and classification of colorectal lesions. The Japan NBI Expert Team (JNET) was introduced in 2011. The aim of this study was to explore the diagnostic accuracy of JNET when applied by European and Japanese endoscopists not familiar with this classification. METHODS: This study was conducted by 36 European Society of Gastrointestinal Endoscopy (ESGE) and 49 Japan Gastroenterological Endoscopy Society (JGES) non-JNET endoscopists using still images of 150 lesions. For each lesion, nonmagnified white-light, nonmagnified NBI, and magnified NBI images were presented. In the magnified NBI, the evaluation area was designated by region of interest (ROI). The endoscopists scored histological prediction for each lesion. RESULTS: In ESGE members, the sensitivity, specificity, and accuracy were respectively 73.3%, 94.7%, and 93.0% for JNET Type 1; 53.0%, 64.9%, and 62.1% for Type 2A; 43.9%, 67.7%, and 55.1% for Type 2B; and 38.1%, 93.7%, and 85.1% for Type 3. When Type 2B and 3 were considered as one category of cancer, the sensitivity, specificity, and accuracy for differentiating high-grade dysplasia and cancer from the others were 59.9%, 72.5%, and 63.8%, respectively. These trends were the same for JGES endoscopists. CONCLUSION: The diagnostic accuracy of the JNET classification was similar between ESGE and JGES and considered to be sufficient for JNET Type 1. On the other hand, the accuracy for Types 2 and 3 is not sufficient; however, JNET 2B lesions should be resected en bloc due to the risk of cancers and JNET 3 can be treated by surgery due to its high specificity.

Novel endoscopic ultrasonography classification for assured vertical resection margin (≥500 µm) in colorectal endoscopic submucosal dissection.

BACKGROUND AND AIM: The risk of local recurrence might be low in pT1 colorectal carcinoma with a tumor vertical margin (VM) ≥500 µm. We investigated the relationship between endoscopic ultrasonography (EUS) findings and VM in cases with colorectal endoscopic submucosal dissection (ESD) categorized as Type 2B according to the Japan NBI Expert Team (JNET) classification. METHODS: We analyzed 179 JNET Type 2B colorectal tumors resected by ESD at Hiroshima University Hospital from January 2010 to May 2021. The distance from the tumor invasive front to the muscle layer on EUS was defined as the tumor-free distance (EUS-TFD) and classified as Type I (EUS-TFD ≥1 mm) and II (<1 mm). We investigated the relationship between EUS-TFD and VM and analyzed the predictive factors for VM ≥500 µm. RESULTS: EUS-TFD Type I was diagnosed in 133 (74.3%) lesions: VM ≥500 µm (114, 85.7%); VM <500 µm (19, 14.3%); and VM positive (VM1) (0, 0%). Type II was diagnosed in 46 (25.7%) lesions: VM ≥500 µm (14, 30.5%); VM <500 µm (22, 47.8%); and VM1 (10, 21.7%). In the EUS-TFD Type I cases, 84.5% and 87.8% were protruded and superficial types; whereas for Type II cases, these were 38.9% and 25%, respectively. EUS-TFD classification (Type I), scope operability (good), submucosal invasion depth (<2000 µm), histology at the deepest invasive portion (favorable), and degree of fibrosis (F0/F1) were significant predictors of VM ≥500 µm. CONCLUSIONS: In JNET Type 2B lesions, EUS-TFD classification is a novel diagnostic indicator to predict VM ≥500 µm in ESD preoperatively.

Texture and color enhancement imaging in magnifying endoscopic evaluation of colorectal adenomas.

BACKGROUND: Olympus Corporation has developed texture and color enhancement imaging (TXI) as a novel image-enhancing endoscopic technique. AIM: To investigate the effectiveness of TXI in identifying colorectal adenomas using magnifying observation. METHODS: Colorectal adenomas were observed by magnified endoscopy using white light imaging (WLI), TXI, narrow band imaging (NBI), and chromoendoscopy (CE). This study adopted mode 1 of TXI. Adenomas were confirmed by histological examination. TXI visibility was compared with the visibility of WLI, NBI, and CE for tumor margin, and vessel and surface patterns of the Japan NBI expert team (JNET) classification. Three expert endoscopists and three non-expert endoscopists evaluated the visibility scores, which were classified as 1, 2, 3, and 4. RESULTS: Sixty-one consecutive adenomas were evaluated. The visibility score for tumor margin of TXI (3.47 ± 0.79) was significantly higher than that of WLI (2.86 ± 1.02, P < 0.001), but lower than that of NBI (3.76 ± 0.52, P < 0.001), regardless of the endoscopist's expertise. TXI (3.05 ± 0.79) had a higher visibility score for the vessel pattern of JNET classification than WLI (2.17 ± 0.90, P < 0.001) and CE (2.47 ± 0.87, P < 0.001), but lower visibility score than NBI (3.79 ± 0.47, P < 0.001), regardless of the experience of endoscopists. For the visibility score for the surface pattern of JNET classification, TXI (2.89 ± 0.85) was superior to WLI (1.95 ± 0.79, P < 0.01) and CE (2.75 ± 0.90, P = 0.002), but inferior to NBI (3.67 ± 0.55, P < 0.001). CONCLUSION: TXI provided higher visibility than WLI, lower than NBI, and comparable to or higher than CE in the magnified observation of colorectal adenomas.

Diagnostic efficacy of the Japan NBI Expert Team classification with dual-focus magnification for colorectal tumors.

BACKGROUND AND AIMS: The Japan NBI Expert Team (JNET) classification is the first unified classification criteria for colorectal tumors using magnifying narrow-band imaging (NBI) in Japan. However, the diagnostic stratification ability of the JNET classification with dual-focus magnifying NBI (DF-JNET) has remained obscure. The aim of this study was to validate the diagnostic stratification ability of DF-JNET for colorectal tumors in two Japanese referral centers. METHODS: A multicenter retrospective image evaluation study was conducted by three experienced endoscopists, including an original JNET member who was also involved in establishing the diagnostic criteria. A total of two images, namely, one representative non-magnified white light image and one representative DF-NBI image for each of the 557 consecutive lesions were used in the evaluation study. The diagnostic value of DF-JNET was calculated based on the evaluation data. RESULTS: The sensitivity, specificity, positive and negative predictive values, and accuracy of DF-JNET Type 1 for differentiating between non-neoplastic and neoplastic lesions were 78.1%, 98.6%, 89.1%, 96.8%, and 95.9%, respectively; of Type 2A lesions for differentiating low-grade dysplasia from others were 98.0%, 76.5%, 94.9%, 89.7%, and 94.1%, respectively; of Type 2B lesions for differentiating high-grade dysplasia and shallow submucosal invasive carcinoma from others were 43.5%, 99.1%, 66.7%, 97.6%, and 96.8%, respectively; and of Type 3 lesions for differentiating deep submucosal invasive carcinoma from others were 83.3%, 99.5%, 62.5%, 99.8%, and 99.3%, respectively. CONCLUSIONS: All DF-JNET types had an over 90% diagnostic accuracy for the histological prediction of colorectal tumors. DF-JNET might contribute to appropriate treatment choices, such as endoscopic resection or surgery, not only in Japan but also in Western countries in which the use of optical zoom endoscopy is limited.

Development of multi-class computer-aided diagnostic systems using the NICE/JNET classifications for colorectal lesions.

BACKGROUND AND AIM: Diagnostic support using artificial intelligence may contribute to the equalization of endoscopic diagnosis of colorectal lesions. We developed computer-aided diagnosis (CADx) support system for diagnosing colorectal lesions using the NBI International Colorectal Endoscopic (NICE) classification and the Japan NBI Expert Team (JNET) classification. METHODS: Using Residual Network as the classifier and NBI images as training images, we developed a CADx based on the NICE classification (CADx-N) and a CADx based on the JNET classification (CADx-J). For validation, 480 non-magnifying and magnifying NBI images were used for the CADx-N and 320 magnifying NBI images were used for the CADx-J. The diagnostic performance of the CADx-N was evaluated using the magnification rate. RESULTS: The accuracy of the CADx-N for Types 1, 2, and 3 was 97.5%, 91.2%, and 93.8%, respectively. The diagnostic performance for each magnification level was good (no statistically significant difference). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the CADx-J were 100%, 96.3%, 82.8%, 100%, and 96.9% for Type 1; 80.3%, 93.7%, 94.1%, 79.2%, and 86.3% for Type 2A; 80.4%, 84.7%, 46.8%, 96.3%, and 84.1% for Type 2B; and 62.5%, 99.6%, 96.8%, 93.8%, and 94.1% for Type 3, respectively. CONCLUSIONS: The multi-class CADx systems had good diagnostic performance with both the NICE and JNET classifications and may aid in educating non-expert endoscopists and assist in diagnosing colorectal lesions.

Effect of educational lecture on the diagnostic accuracy of Japan NBI Expert Team classification for colorectal lesions.

BACKGROUND: An educational and training program is required for generalization of Japan NBI Expert Team (JNET) classification. However, there is no detailed report on the learning curve of the diagnostic accuracy of endoscopists using JNET classification. We examined the effect of an educational lecture on beginners and less experienced endoscopists for improving their diagnostic accuracy of colorectal lesions by JNET classification. METHODS: Seven beginners with no endoscopy experience (NEE group), 7 less experienced endoscopists (LEE group), and 3 highly experienced endoscopists (HEE group) performed diagnosis using JNET classification for randomized NBI images of colorectal lesions from 180 cases (Type 1: 22 cases, Type 2A: 105 cases, Type 2B: 33 cases, and Type 3: 20 cases). Next, the NEE and LEE groups received a lecture on JNET classification, and all 3 groups repeated the diagnostic process. We compared the correct diagnosis rate and interobserver agreement before and after the lecture comprehensively and for each JNET type. RESULTS: In the HEE group, the correct diagnosis rate was more than 90% with good interobserver agreements (kappa value: 0.78-0.85). In the NEE and LEE groups, the correct diagnosis rate (NEE: 60.2 → 68.0%, P < 0.01; LEE: 66.4 → 86.7%, P < 0.01), high-confidence correct diagnosis rate (NEE: 19.6 → 37.2%, P < 0.01; LEE: 43.6 → 61.1%, P < 0.01), and interobserver agreement (kappa value, NEE: 0.32 → 0.43; LEE: 0.39 → 0.75) improved after the lecture. In the examination by each JNET type, the specificity and positive predictive value in the NEE and LEE groups generally improved after the lecture. CONCLUSION: After conducting an appropriate lecture, the diagnostic ability using JNET classification was improved in beginners or endoscopists with less experience in NBI magnifying endoscopy.

Usefulness of the Japan narrow-band imaging expert team classification system for the diagnosis of sessile serrated lesion with dysplasia/carcinoma.

BACKGROUND: Sessile serrated lesion (SSL) is a colorectal polyp that has malignant potential. However, the dysplastic components within an SSL can be difficult to diagnose with conventional endoscopy, because most SSLs with dysplasia/carcinoma have subtle mucosal features. Many studies have indicated that narrow-band imaging (NBI) observations of colorectal polyps are very useful, accurate predictors of histology. We aimed to verify the usefulness of the Japan NBI Expert Team (JNET) classification system for the diagnosis of SSLs with dysplasia/carcinoma. METHODS: We examined 709 endoscopically or surgically resected lesions that were pathologically diagnosed as SSL, including 647 with no dysplasia, 37 with low-grade dysplasia, 15 with high-grade dysplasia, and 10 with submucosal invasive carcinoma. We retrospectively evaluated their clinicopathologic characteristics and conventional endoscopic and magnifying NBI endoscopic findings using the JNET system. RESULTS: Cases in all groups were more frequently located in the proximal colon. Submucosal invasive carcinomas were significantly larger than no dysplasia and low-grade dysplasia lesions. Almost all studied lesions (96.3%) were covered with a mucus cap. Five hundred and eighty (81.8%) lesions exhibited dark spots inside the crypts, which are NBI findings' characteristic of SSL. As for the JNET classification of magnifying NBI endoscopic findings, all 709 lesions showed Type 1. Six hundred and eighteen (95.5%) SSLs with no dysplasia lesions exhibited Type 1 only, whereas 52 (83.9%) SSLs with dysplasia/carcinoma had a combination of Type 1 and Type 2A, 2B, or 3, corresponding to SSL and dysplasia/carcinoma, respectively. The JNET classification had high sensitivity (83.9%), specificity (95.5%), and overall diagnostic accuracy (94.5%) for diagnosing SSLs with dysplasia/carcinoma. CONCLUSIONS: Use of magnifying NBI endoscopy with the JNET classification might be useful for diagnosing SSLs with dysplasia/carcinoma. This increased awareness may also improve the recognition of SSLs with dysplasia/carcinoma.

Blue laser imaging combined with JNET (Japan NBI Expert Team) classification for pathological prediction of colorectal laterally spreading tumors.

BACKGROUND: Blue laser imaging (BLI) can provide useful information on colorectal laterally spreading tumors (LSTs) by visualizing the surface and vessel patterns in detail. The present research aimed to evaluate the diagnostic performance of BLI-combined JNET (Japan NBI Expert Team) classification for identifying LSTs. METHODS: This retrospective, multicenter study included 172 LSTs consisted of 6 hyperplastic polyps/sessile serrated polyps, 94 low-grade dysplasias (LGD), 60 high-grade dysplasias (HGD), 6 superficial submucosal invasive (m-SMs) carcinomas, and 4 deep submucosal invasive carcinomas. The relationship between the JNET classification and the histologic findings of these lesions were then analyzed. RESULTS: For all LSTs, non-experts and experts had a 79.7% and 90.7% accuracy for Type 2A (P = 0.004), a sensitivity of 94.7% and 96.8% (P = 0.718), and a specificity of 61.5% and 83.3% (P = 0.002) for prediction of LGD, respectively. The results also demonstrated 80.8% and 91.3% accuracy for Type 2B (P = 0.005), a sensitivity of 65.2% and 83.3% (P = 0.017), and a specificity of 90.6% and 96.2% (P = 0.097) for predicting HGD or m-SMs. For LST-granular (LST-G) lesions, Type 2A in experts had higher specificity (65.6% vs. 83.6%, P = 0.022) and accuracy (81.8% vs. 91.2%, P = 0.022). Type 2B in experts only had higher accuracy (82.5% vs. 92.0%, P = 0.019). However, no significant differences were noted for any comparisons between non-experts and experts for LST-non-granular (LST-NG) lesions. CONCLUSIONS: BLI combined with JNET classification was an effective method for the precise prediction of pathological diagnosis in patients with LSTs. Diagnostic performance of JNET classification by experts was better than that by non-experts for all examined LST or LST-G lesions when delineating between Type 2A and 2B, but there was no difference for the identification of LST-NG lesions by these two groups.

Endoscopic prediction of advanced histology in colorectal lesions sized <10 mm using the Japan Narrow-band imaging Expert Team classification.

BACKGROUND AND AIM: Endoscopic diagnosis of advanced histology in colorectal lesions sized <10 mm is essential for appropriate selection of resection methods. The Japan Narrow-band imaging Expert Team (JNET) classification has been recently validated for the evaluation of colorectal lesions. Our objective was to investigate the diagnostic value of the JNET classification for advanced histology in colorectal lesions sized <10 mm. METHODS: We enrolled 680 patients with 1472 colorectal lesions sized <10 mm diagnosed according to the JNET classification and who subsequently underwent endoscopic or surgical resection between January and December 2017. We retrospectively examined the relationship between the JNET findings and pathological histology. Multivariate analysis was carried out to assess the predictive power of the JNET findings and clinical characteristics of lesions. RESULTS: Advanced histology was present in 29 (2.0%) lesions. Advanced histology was absent in 68 lesions diagnosed as JNET type 1, whereas 1389 lesions diagnosed as JNET type 2A included 19 lesions of advanced histology (1.4%) with high-grade dysplasia alone. Eleven lesions diagnosed as JNET type 2B comprised eight lesions of advanced histology (72.7%) with four high-grade dysplasia and four submucosal invasive cancer, and two lesions diagnosed as JNET type 3 were submucosal invasive cancer. Multivariate analysis showed that JNET type 2B + 3 was a stronger predictive factor for advanced histology than other clinical risk factors. CONCLUSION: Narrow-band imaging with magnification according to the JNET classification may be a useful modality for identification of advanced histology in colorectal lesions sized <10 mm.

Diagnostic yield of the Japan NBI Expert Team (JNET) classification for endoscopic diagnosis of superficial colorectal neoplasms in a large-scale clinical practice database.

Background: Magnifying Narrow Band Imaging (NBI) during colonoscopy is a reliable method for differential and depth diagnoses of colorectal lesions. This study examined the diagnostic yield of magnifying NBI based on the Japan NBI Expert Team (JNET) classification in a clinical setting using a large-scale clinical practice database. Types 1, 2A, 2B and 3 correspond to the histopathological classifications of hyperplastic polyp/sessile-serrated polyp, low-grade intramucosal neoplasia, high-grade intramucosal neoplasia/shallow submucosal invasive cancer, and deep submucosal invasive cancer, respectively. Methods: The prospective records of colonoscopy reports and pathological data of 1558 consecutive superficial colorectal lesions removed by colonoscopy were retrospectively analysed. After excluding 156 lesions, the documented JNET classifications of the remaining 1402 colorectal lesions were analysed. Diagnostic yield was analysed and also compared between expert endoscopists and nonexpert endoscopists. Results: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were respectively 75%, 96%, 74%, 96% and 93% for type 1; 91%, 70%, 92%, 67% and 87% for type 2A; 42%, 95%, 26%, 98% and 93% for type 2B; and 35%, 100%, 93%, 98% and 98% for type 3. Nonexpert and expert endoscopists alike had specificity, NPV and accuracy >90% for types 1, 2B and 3, and a sensitivity and PPV >90% for type 2A. Type 2B had a low sensitivity of 42% because it included various histological features. Conclusions: The JNET classification proved useful in a clinical setting both for expert and nonexpert endoscopists, as was expected from the original JNET definition, but type 2B requires further investigation using pit pattern diagnosis.

Additional chromoendoscopy for colorectal lesions initially diagnosed with low confidence by magnifying narrow-band imaging: Can it improve diagnostic accuracy?

BACKGROUND AND AIM: Magnifying chromoendoscopy has been one of the most reliable diagnostic methods for distinguishing neoplastic from non-neoplastic lesions. The aim of this prospective study was to clarify the clinical usefulness of magnifying chromoendoscopy for colorectal polyps initially diagnosed with low confidence (LC) by magnifying narrow-band imaging (NBI). METHODS: Consecutive adult patients who underwent total colonoscopic examination with magnifying NBI between July and December 2016 at Sano Hospital were prospectively recruited. Endoscopists were asked to carry out additional magnifying chromoendoscopy for cases that had been initially diagnosed as Japan NBI Expert Team (JNET) Type 1 or 2A with LC by magnifying NBI. We investigated the diagnostic performance of magnifying NBI for polyps diagnosed as JNET Type 1 or 2A with LC (first phase) and that of subsequent magnifying chromoendoscopy (second phase) in differentiating neoplasia from non-neoplasia. RESULTS: In 50 patients, we analyzed 53 polyps classified as JNET Type 1 or 2A with LC prediction. Accuracy and negative predictive value of magnifying NBI (first phase) were 58.5% (95% CI, 44.1-71.9%) and 66.0% (95% CI, 36.6-77.9%), and those of magnifying chromoendoscopy (second phase) were 66.0% (95% CI, 51.7-78.5%) and 61.1% (95% CI, 43.5-76.9%), respectively. CONCLUSION: Regardless of the findings of additional chromoendoscopy, all polyps should be resected and submitted for histopathological examination when the confidence level in differentiating adenomatous from hyperplastic polyps by magnifying NBI is low.

Validation study for development of the Japan NBI Expert Team classification of colorectal lesions.

BACKGROUND AND AIM: The Japan narrow-band imaging (NBI) Expert Team (JNET) was organized to unify four previous magnifying NBI classifications (the Sano, Hiroshima, Showa, and Jikei classifications). The JNET working group created criteria (referred to as the NBI scale) for evaluation of vessel pattern (VP) and surface pattern (SP). We conducted a multicenter validation study of the NBI scale to develop the JNET classification of colorectal lesions. METHODS: Twenty-five expert JNET colonoscopists read 100 still NBI images with and without magnification on the web to evaluate the NBI findings and necessity of the each criterion for the final diagnosis. RESULTS: Surface pattern in magnifying NBI images was necessary for diagnosis of polyps in more than 60% of cases, whereas VP was required in around 90%. Univariate/multivariate analysis of candidate findings in the NBI scale identified three for type 2B (variable caliber of vessels, irregular distribution of vessels, and irregular or obscure surface pattern), and three for type 3 (loose vessel area, interruption of thick vessel, and amorphous areas of surface pattern). Evaluation of the diagnostic performance for these three findings in combination showed that the sensitivity for types 2B and 3 was highest (44.9% and 54.7%, respectively), and that the specificity for type 3 was acceptable (97.4%) when any one of the three findings was evident. We found that the macroscopic type (polypoid or non-polypoid) had a minor influence on the key diagnostic performance for types 2B and 3. CONCLUSION: Based on the present data, we reached a consensus for developing the JNET classification.

Magnifying Narrow Band Imaging (NBI) for the Diagnosis of Localized Colorectal Lesions Using the Japan NBI Expert Team (JNET) Classification.

OBJECTIVE: The Japan NBI Expert Team (JNET) proposed a new narrow band imaging (NBI) classification system for colorectal tumors in June 2014. In this classification system, types 1, 2A, 2B, and 3 correspond to hyperplastic polyps (HPs) including sessile serrated polyps (SSPs), low-grade dysplasia (LGD), high-grade dysplasia (HGD) to shallow submucosal invasive (SM-s) carcinomas, and deep submucosal invasive (SM-d) carcinomas, respectively. METHODS: To validate this system, we performed a retrospective image evaluation study, in which 199 colorectal tumors previously assessed by NBI magnifying endoscopy were classified by 3 blinded experienced colonoscopists using the JNET system. The results were compared with the final pathological diagnoses to determine the JNET classification's accuracy. The interobserver agreement was calculated, and the intraobserver agreement was assessed after 6 months. RESULTS: The final pathological diagnoses identified 14 HPs/SSPs, 127 LGDs, 22 HGDs, 19 SM-s carcinomas, and 17 SM-d carcinomas. The respective sensitivities, specificities, positive predictive value, negative predictive value, and accuracies were as follows: Type 1, 85.7, 99.5, 92.3, 98.9, and 98.5%; Type 2A, 96.0, 81.9, 90.3, 92.1, and 90.9%; Type 2B, 75.6%, 90.5, 67.3, 93.4, and 87.4%; and Type 3, 29.4%, 100, 100, 93.8, and 94.0%. The interobserver agreement and the intraobserver agreement were moderate (κ value: 0.52) and excellent (κ value: 0.88), respectively. Lesions presenting as Type 2B during NBI comprised a range of colorectal tumors, including HGDs, SM-s, and SM-d. CONCLUSIONS: The JNET classification was useful for the diagnosis of HPs/SSPs, LGDs, and SM-d, but not SM-s lesions. For low-confidence cases, magnified chromoendoscopy is recommended to ensure correct diagnoses.

Narrow-band imaging (NBI) magnifying endoscopic classification of colorectal tumors proposed by the Japan NBI Expert Team.

Many clinical studies on narrow-band imaging (NBI) magnifying endoscopy classifications advocated so far in Japan (Sano, Hiroshima, Showa, and Jikei classifications) have reported the usefulness of NBI magnifying endoscopy for qualitative and quantitative diagnosis of colorectal lesions. However, discussions at professional meetings have raised issues such as: (i) the presence of multiple terms for the same or similar findings; (ii) the necessity of including surface patterns in magnifying endoscopic classifications; and (iii) differences in the NBI findings in elevated and superficial lesions. To resolve these problems, the Japan NBI Expert Team (JNET) was constituted with the aim of establishing a universal NBI magnifying endoscopic classification for colorectal tumors (JNET classification) in 2011. Consensus was reached on this classification using the modified Delphi method, and this classification was proposed in June 2014. The JNET classification consists of four categories of vessel and surface pattern (i.e. Types 1, 2A, 2B, and 3). Types 1, 2A, 2B, and 3 are correlated with the histopathological findings of hyperplastic polyp/sessile serrated polyp (SSP), low-grade intramucosal neoplasia, high-grade intramucosal neoplasia/shallow submucosal invasive cancer, and deep submucosal invasive cancer, respectively.