Japan NBI Expert Team Classification Research Articles

Evaluation of the extended Japan NBI expert team classification of subtype 2B in laterally spreading colorectal tumors based on blue laser imaging.

The Japan NBI Expert Team (JNET) classification has good diagnostic potential for colorectal diseases. We aimed to explore the diagnostic value of the JNET classification type 2B (JNET2B) criteria for colorectal laterally spreading tumors (LSTs) based on magnifying endoscopy with blue laser imaging (ME-BLI) examination. Between January 2017 and June 2023, 218 patients who were diagnosed as having JNET2B-type LSTs using ME-BLI were included retrospectively. Endoscopic images were reinterpreted to categorize the LSTs as JNET2B-low (n = 178) and JNET2B-high (n = 53) LSTs. The JNET2B-low and JNET2B-high LSTs were compared based on their histopathological and morphological classifications. Among the 178 JNET2B-low LSTs, 86 (48.3%) were histopathologically classified as low-grade intraepithelial neoplasia, 54 (30.3%) as high-grade intraepithelial neoplasia (HGIN), 37 (20.8%) as intramucosal carcinoma (IMC), and one (0.6%) as superficial invasive submucosal carcinoma (SMC1). Among the 53 JNET2B-high LSTs, five (9.4%) were classified as HGIN, 28 (52.9%) as IMC, 15 (28.3%) as SMC1, and 5 (9.4%) as deep invasive submucosal carcinoma. There were significant differences in this histopathological classification between the two groups (P < 0.001). However, there was no significant difference between JNET2B-low and JNET2B-high LSTs based on their morphological classification (granularvs nongranular) or size (<20 mm vs ≥20 mm). Besides, the κ value for JNET2B subtyping was 0.698 (95% confidence interval 0.592-0.804) between the two endoscopists who reassessed the endoscopic images. The JNET2B subtyping of LSTs has a diagnostic potential in the preoperative setting, and may be valuable for treatment decision-making.

Endoscopic submucosal dissection and JNET classification for colorectal neoplasia: A North American academic center experience.

Endoscopic submucosal dissection (ESD) enables minimally invasive resection of superficial gastrointestinal neoplasms en bloc regardless of size. The Japan narrow band imaging expert team (JNET) classification utilizes optical magnification and narrow band imaging (NBI) to predict pathology. In North America, ESD is far from ubiquitous, and regional outcomes are not widely described. To date there are no North American studies describing the application and yield of the JNET classification as applied in the practice of ESD. A retrospective, single-center, cohort analysis was performed on a prospectively maintained database of ESD procedures. Between July 2016 and February 2023, all consecutive patients treated with ESD for colorectal lesions were identified and stratified by lesion location, JNET, NBI International Colorectal Endoscopic, lateral spreading tumors, and Paris classifications. Univariate analysis was used for clinicopathological data. p<0.05 was considered statistically significant. A total of 112 patients were identified. One lesion, a lipoma, was excluded. Overall, 49.5% (55/111) of lesions were colonic and 50.5% (56/111) rectal. Most lesions were lateral spreading tumors (60.4%, 67/111). Overall, 96.4% (107/111) ESDs were successfully completed, 98.1% (105/107) en bloc, and 87.9% (94/107) R0. Adverse events occurred in 1.8% (2/111) of procedures. The median diameter was 4.0cm and resected in a median time of 62.0min. Overall, 70.1% (47/67) lesions were upstaged from pre-ESD biopsy. JNET 2B showed 80.2% (95% CI 71.5-87.1) accuracy for high-grade dysplasia or sm1. All JNET type 3 were ≥sm2 (p<0.001). ESD permits safe and effective resection of superficial colorectal neoplasms. JNET classification was more accurate than pre-resection biopsy at predicting histology in this series.

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

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. 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. 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. 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.

Expression of Cyclooxygenase-2 in Patients With Snow-White Sign of Advanced Colorectal Adenomas

Objective To analyze the expression of cyclooxygenase-2 (COX-2) in the patients with snow-white sign of advanced colorectal adenoma (ACA) and explore its clinical significance.Method Western blotting was employed to determine the expression of COX-2 in the adenoma tissue and the normal tissue adjacent to the adenoma tissue (>5 cm away from the distal end of the adenoma tissue) of 40 ACA patients with snow-white sign and 40 ACA patients without snow-white sign.Results The appearance of snow-white sign in ACA patients was associated with patient age (P=0.001) and not associated with sex,smoking history,drinking history,ethnic groups,family history of colorectal cancer,abdominal pain,diarrhea,constipation,fecal occult blood,or tumor markers (all P>0.05).Snow-white sign mainly appeared in the ACA patients with multiple adenomas (P=0.004),large adenomas (P=0.006),adenomas in distal colon (P=0.015),protruding polyps (P=0.044),and late-stage pathology (P=0.010).The occurrence of snow-white sign showed no difference in the ACA patients with different results of Japan NBI Expert Team classification (P=0.502).The expression of COX-2 in the adenoma tissue was higher than that in the adjacent normal tissue in the patients with and without snow-white sign (P<0.001,P=0.004).The patients with snow-white sign had higher expression of COX-2 protein in the adenoma tissue than the patients without snow-white sign (P=0.001).The expression of COX-2 protein in the adjacent healthy tissue had no significant difference between the patients with and without snow-white sign (P=0.603).Conclusions Snow-white sign is more like to appear in the ACA patients with young age,multiple and large adenomas,adenomas in distal colon,protruding polyps,and late-stage pathology.Moreover,the expression of COX-2 in the ACA patients with snow-white sign is significantly higher than that in the ACA patients without snow-white sign.The adults with snow-white sign are prone to cancerization than those without snow-white sign.

Comparison of blue laser imaging and light-emitting diode-blue light imaging for the characterization of colorectal polyps using the Japan narrow-band imaging expert team classification: The LASEREO and ELUXEO COLonoscopic study.

Although the laser light is optically ideal for producing narrow-band light, it has not been used in some areas of the world. Endoscopic light sources using light-emitting diodes (LEDs) are used worldwide. The purpose of this study was to compare blue laser imaging (laser-BLI) and LED-blue light imaging (LED-BLI) for the characterization of colorectal polyps using the Japan narrow band imaging expert team (JNET) classification. Colorectal lesions were prospectively examined using magnifying narrow-band light generated by a laser (laser-BLI) or LEDs (LED-BLI). Twelve endoscopists (six non-experts and six experts from three institutions) evaluated each still-magnified image of lesions using the JNET classification. Seven hundred and fifty-six images from 63 lesions were reviewed. The mean polyp size was 24.5 ± 13.4mm. Histopathology included 13 serrated lesions and 50 neoplasms. The rate of agreement between laser-BLI and LED-BLI using the JNET classification was 92.5% (699/756). The weighted κ-statistic was 0.99. The percentages of "almost similar" comparing scores of surface patterns, vessel patterns, and brightness among all endoscopists were 95.4%, 95.9%, and 95.0%, respectively. This multicenter study demonstrates that the rate of agreement between laser-BLI and LED-BLI using the JNET Classification is very high. The surface patterns, vessel patterns, and brightness are almost similar.

Diagnostic Value of Adding Magnifying Chromoendoscopy to Magnifying Narrow-Band Imaging Endoscopy for Colorectal Polyps

This study examined the additional value of magnifying chromoendoscopy (MCE) on magnifying narrow-band imaging endoscopy (M-NBI) in the optical diagnosis of colorectal polyps. A multicenter prospective study was conducted at 9 facilities in Japan and Germany. Patients with colorectal polyps scheduled for resection were included. Optical diagnosis was performed by M-NBI first, followed by MCE. Both diagnoses were made in real time. MCE was performed on all type 2B lesions classified according to the Japan NBI Expert Team classification and other lesions at the discretion of endoscopists. The diagnostic accuracy and confidence of M-NBI and MCE for colorectal cancer (CRC) with deep invasion (≥T1b) were compared on the basis of histologic findings after resection. In total, 1173 lesions were included between February 2018 and December 2020, with 654 (5 hyperplastic polyp/sessile serrated lesion, 162 low-grade dysplasia, 403 high-grade dysplasia, 97 T1 CRCs, and 32 ≥T2 CRCs) examined using MCE after M-NBI. In the diagnostic accuracy for predicting CRC with deep invasion, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for M-NBI were 63.1%, 94.2%, 61.6%, 94.5%, and 90.2%, respectively, and for MCE they were 77.4%, 93.2%, 62.5%, 96.5%, and 91.1%, respectively. The sensitivity was significantly higher in MCE (P < .001). However, these additional values were limited to lesions with low confidence in M-NBI or the ones diagnosed as ≥T1b CRC by M-NBI. In this multicenter prospective study, we demonstrated the additional value of MCE on M-NBI. We suggest that additional MCE be recommended for lesions with low confidence or the ones diagnosed as ≥T1b CRC. Trials registry number: UMIN000031129.

Updates in narrow-band imaging for colorectal polyps: Narrow-band imaging generations, detection, diagnosis, and artificial intelligence.

Narrow-band imaging (NBI) is an optical digital enhancement method that allows the observation of vascular and surface structures of colorectal lesions. Its usefulness in the detection and diagnosis of colorectal polyps has been demonstrated in several clinical trials and the diagnostic algorithms have been simplified after the establishment of endoscopic classifications such as the Japan NBI Expert Team classification. However, there were issues including lack of brightness in the earlier models, poor visibility under insufficient bowel preparation, and the incompatibility of magnifying endoscopes in certain endoscopic platforms, which had impeded NBI from becoming standardized globally. Nonetheless, NBI continued its evolution and the newest endoscopic platform launched in 2020 offers significantly brighter and detailed images. Enhanced visualization is expected to improve the detection of polyps while universal compatibility across all scopes including magnifying endoscopy will promote the global standardization of magnifying diagnosis. Therefore, knowledge related to magnifying colonoscopy will become essential as magnification becomes standardly equipped in future models, although the advent of computer-aided diagnosis and detection may greatly assist endoscopists to ensure quality of practice. Given that most endoscopic departments will be using both old and new models, it is important to understand how each generation of endoscopic platforms differ from each other. We reviewed the advances in the endoscopic platforms, artificial intelligence, and evidence related to NBI essential for the next generation of endoscopic practice.

Diagnostic performance of endoscopic classifications for neoplastic lesions in patients with ulcerative colitis: A retrospective case-control study.

BACKGROUNDIt is unclear whether the Japan Narrow-Band Imaging Expert Team (JNET) classification and pit pattern classification are applicable for diagnosing neoplastic lesions in patients with ulcerative colitis (UC).AIMTo clarify the diagnostic performance of these classifications for neoplastic lesions in patients with UC.METHODSThis study was conducted as a single-center, retrospective case-control study. Twenty-one lesions in 19 patients with UC-associated neoplasms (UCAN) and 23 lesions in 22 UC patients with sporadic neoplasms (SN), evaluated by magnifying image-enhanced endoscopy, were retrospectively and separately assessed by six endoscopists (three experts, three non-experts), using the JNET and pit pattern classifications. The results were compared with the pathological diagnoses to evaluate the diagnostic performance. Inter- and intra-observer agreements were calculated.RESULTSIn this study, JNET type 2A and pit pattern type III/IV were used as indicators of low-grade dysplasia, JNET type 2B and pit pattern type VI low irregularity were used as indicators of high-grade dysplasia to shallow submucosal invasive carcinoma, JNET type 3 and pit pattern type VI high irregularity/VN were used as indicators of deep submucosal invasive carcinoma. In the UCAN group, JNET type 2A and pit pattern type III/IV had a low positive predictive value (PPV; 50.0% and 40.0%, respectively); however, they had a high negative predictive value (NPV; 94.7% and 100%, respectively). Conversely, in the SN group, JNET type 2A and pit pattern type III/IV had a high PPV (100% for both) but a low NPV (63.6% and 77.8%, respectively). In both groups, JNET type 3 and pit pattern type VI-high irregularity/VN showed high specificity. The inter-observer agreement of JNET classification and pit pattern classification for UCAN among experts were 0.401 and 0.364, in the same manner for SN, 0.666 and 0.597, respectively. The intra-observer agreements of JNET classification and pit pattern classification for UCAN among experts were 0.387, 0.454, for SN, 0.803 and 0.567, respectively.CONCLUSIONThe accuracy of endoscopic diagnosis using both classifications was lower for UCAN than for SN. Endoscopic diagnosis of UCAN tended to be underestimated compared with the pathological results.

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

BACKGROUNDOlympus Corporation has developed texture and color enhancement imaging (TXI) as a novel image-enhancing endoscopic technique.AIMTo investigate the effectiveness of TXI in identifying colorectal adenomas using magnifying observation.METHODSColorectal 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.RESULTSSixty-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).CONCLUSIONTXI provided higher visibility than WLI, lower than NBI, and comparable to or higher than CE in the magnified observation of colorectal adenomas.

History, clinical application, and future perspective of narrow band imaging and blue laser imaging

History, clinical application, and future perspective of narrow band imaging and blue laser imaging

Not So Smart? Artificial Intelligence May Need to Go Deeper to Predict Colorectal Cancer Invasion Depth

Not So Smart? Artificial Intelligence May Need to Go Deeper to Predict Colorectal Cancer Invasion Depth

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

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. 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. 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. 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.

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. 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. 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. 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.

Depth diagnosis of early colorectal cancer: Magnifying chromoendoscopy or image enhanced endoscopy with magnification?

Depth diagnosis is extremely crucial in making a treatment choice between endoscopic resection and surgery in the early stages of cancers. Among several imaging modalities, we use magnifying endoscopy to diagnose lesions by close observation of the findings at mucosal surface layer. In combination with topical staining, magnifying endoscopy enables us to assess the definite pit structure, which referred to as magnifying chromoendoscopy (MCE). The pit pattern classification by MCE was proposed and is now widely accepted as the standard diagnostic criteria for colorectal lesions. Meanwhile, image enhanced endoscopy (IEE) represented by narrow-band imaging was developed to improve the visibility of surface and vascular findings without dyeing. Recent collaborative work performed by endoscopic experts in Japan yielded the unified diagnostic criteria, the Japan NBI Expert Team (JNET) classification, based on the findings of IEE with magnification. In this review, focusing on MCE and IEE with magnification, we aimed to give an outline of the pit pattern classification and the JNET classification, and further discuss their accuracy rate of depth diagnosis of early colorectal lesions by performing a review of the related literature. Both modalities have a high accuracy rate of nearly 90% for depth diagnosis. IEE with magnification is an ideal modality because it helps observe lesions without dye spraying; however, lesions with JNET type 2B have an inadequate diagnostic ability, which should be complemented by MCE. We conclude that accurate diagnosis is possible by examining lesions using both modalities properly to overcome the limitations of each modality.

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

BackgroundAn 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.MethodsSeven 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.ResultsIn 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.ConclusionAfter conducting an appropriate lecture, the diagnostic ability using JNET classification was improved in beginners or endoscopists with less experience in NBI magnifying endoscopy.

Comparative Study of Narrow-Band Imaging and i-scan for Predicting the Histology of Intermediate-to-Large Colorectal Polyps: A Prospective, Randomized Pilot Study.

Background/AimsTo date, no reports have compared the diagnostic efficacy of narrow-band imaging (NBI) and i-scan for the histologic prediction of intermediate-to-large colorectal polyps. We aimed to compare the diagnostic accuracy of NBI and i-scan in predicting histology, and their inter-/intra-observer agreement. MethodsWe performed a prospective, randomized study that included 66 patients (NBI, n=33 vs. i-scan, n=33) with colorectal polyps (size >10 mm but <50 mm) who underwent colonoscopic resection. During the procedure, three endoscopists documented their prediction using the Japan NBI Expert Team (JNET) classification. Two months after study completion, the endoscopists reviewed still images and video clips for analysis. ResultsThe overall diagnostic accuracies in the NBI and i-scan groups were 73.7% (73/99) and 75.8% (75/99), respectively, and there was no statistical significance between the two groups (p=0.744). The JNET classification as applied to NBI and i-scan showed substantial inter-observer agreement (NBI κ-value 0.612, p=0.001 vs. i-scan κ-value 0.662, p=0.002). Additionally, the κ-values of intra-observer agreement were in the range of 0.385–0.660 with NBI and 0.364–0.741 with i-scan. ConclusionsNBI and i-scan have similar diagnostic accuracies for the histologic prediction of intermediate-to-large colorectal polyps. Furthermore, the inter-/intra-observer agreement was acceptable for both modalities when the JNET classification was applied.

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

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. 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. 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. 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.

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

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. 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. 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. 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.

Diagnostic performance for T1 cancer in colorectal lesions ≥10mm by optical characterization using magnifying narrow-band imaging combined with magnifying chromoendoscopy; implications for optimized stratification by Japan Narrow-band Imaging Expert Team classification.

Magnifying narrow-band imaging (M-NBI) and magnifying chromoendoscopy (M-CE) enable accurate diagnosis of T1 colorectal cancer, but the diagnostic yields from combined M-NBI and CE have not been fully analyzed. We aimed to evaluate the diagnostic yield of combining Japan NBI Expert Team (JNET) classification using M-NBI and M-CE. Superficial colorectal lesions ≥10mm removed at a Japanese tertiary cancer center between February 2016 and December 2018 were included. We analyzed the relationship between JNET classification, M-CE findings, and histological results based on prospectively collected endoscopic and pathologic data. A total of 1573 lesions, including 56 superficial submucosal invasive cancers, 160 deep submucosal invasive cancers, and 81 advanced cancers (≥T2) were analyzed. The probability of deeply invasive cancer (95% confidence interval) was 1.8% (1.1-2.8), 30.1% (25.4-35.1), and 96.6% (91.5-99.1) in JNET Types 2A, 2B, and 3, respectively. The probability of deeply invasive cancer in JNET Type 2B lesions with non-V, VL, and VH pit pattern was 4.3%, 16.6%, 76.0%, respectively (P<0.001). Our study showed the stratification by M-NBI using JNET classification and the effect of additional M-CE for JNET Type 2B lesions.

Can Non-expert Physicians Use the Japan Narrow-band Imaging Expert Team Classification to Diagnose Colonic Polyps Effectively?

Objectives: In 2014, the Japan narrow-band imaging expert team (JNET) proposed the first unified colorectal narrow-band imaging magnifying classification system, the JNET classification. The clinical usefulness of this system has been well established in JNET member institutions, but its suitability for use by “non-expert physicians” (physicians with no expertise in the use of JNET classification) remains unclear. This study aimed to examine the clinical usefulness of the JNET classification by “non-expert physicians”. Methods: We retrospectively analyzed 852 consecutive patients who underwent screening colonoscopy following a positive fecal occult blood test between January 2017 and May 2018. Endoscopic results from colon polyp diagnosis by physicians who started using the JNET classification (JNET group) were compared with those of physicians who did not (control group). Mann-Whitney U test and Fisher's exact test were used to compare continuous and categorical variables, respectively. Results: The median patient age was 68 years, and the male-to-female ratio was 1:0.84. When no lesions were found, the median withdrawal time was significantly different between groups (JNET group: 12 min; control group: 15 min; P < 0.01). The number of resected adenomas per colonoscopy was significantly higher in the JNET group (1.7) than in the control group (1.2; P < 0.01). Among the resected lesions, 8.9% in the JNET group and 17% in the control group were non-neoplastic lesions that did not require resection (P < 0.01). Conclusions: Colon polyp diagnosis using the JNET classification can reduce unnecessary resection during magnifying colonoscopy when conducted by “non-expert physicians”.