Introduction

The prevalence of Helicobacter pylori (H.pylori) positive patients has gradually decreased in Japan due to eradication therapy, and H.pylori-uninfected gastric cancer (HPUGC) is expected to increase relatively. Recently, HPUGC, such as gastric adenocarcinoma of fundic-gland type (GAFG), gastric adenocarcinoma of foveolar-type (GAFV), adenocarcinoma of differentiated type (DGA) and signet ring cell carcinoma (SRCC) has been increasingly reported. Since the detection and endoscopic diagnosis of HPUGC is considered to be difficult [1]. The effective observation methods in screening endoscopy to detect HPUGC. In this context, a new image enhancement technology called Texture and Color Enhancement Imaging (TXI; Olympus Medical Systems Corporation) which optimizes the three elements: structure (texture) enhancement, color tone, and brightness correction was developed in 2020. There have been several reports on the usefulness of TXI for the detection and endoscopic diagnosis of mucosal atrophy or gastric neoplasm [2-6]. However, the usefulness of TXI for the detection of HPUGC has been investigated.

Aims & Methods

The aim of the study is to investigate whether the visibility of HPUGC improved using TXI and NBI compared with WLI as a single-center retrospective clinical study. We enrolled 40 HPUGC lesions endoscopically imaged with WLI, TXI-1, TXI-2, and NBI in our facility between October 2020 and March 2023. In addition, the visibility of HPUGCs was analyzed for each factor, such as histological type, coloration, and macroscopic type. Ten endoscopists (5 experts and 5 non-experts) evaluated the images, and visibility changes were scored by endoscopists as follows: 5, improved; 4, somewhat improved; 3, equivalent; 2, somewhat decreased; and 1, decreased. The total visibility score of ≥40 in all endoscopists and /≥20 in each of the 5 endoscopists was defined as improved visibility, 21-39/11-19 as unchanged visibility, and 20≤/10≤ as decreased visibility. The intraclass correlation coefficients (ICC) were calculated and evaluated for inter-rater agreement.

Results

The histological types were classified as GAFG (n=24), GAFV (n=9), DGA (n=4), and SRCC (n=3). There were 17 reddish lesions and 23 whitish lesions. In the macroscopic type, there were type 0-Ⅰ (n=11), type 0-Ⅱa (n=13), type 0-Ⅱb (n=11), and type 0-Ⅱc (n=5) lesions. The visibility improvement rate for all endoscopists in all HPUGCs was TXI-1: 55%, TXI-2: 29.7%, and NBI: 7.5%. The overall ICCs were TXI-1: 0.86, TXI-2: 0.84, and NBI: 0.90, which were almost perfect. GAFG (all/experts/trainees: 79/54/79%) and SRCC (all/experts/trainees: 67/67/67%) showed improved visibility with TXI-1. In contrast, GAFV and DGA did not improve the visibility. The whitish lesions (all/experts/trainees: 74/52/74%) showed improved the visibility with TXI-1, but the reddish lesions did not improve visibility. Among the macroscopic type , type 0-Ⅱa (overall/experts/trainees: 85/54/85%) and type 0-Ⅱb (overall/experts/trainees: 73/64/73%) showed improved visibility with TXI-1. The all ICCs of each factor were above 0.7, which indicated generally good correlations.

Conclusion

The usefulness of TXI-1 compared with WLI led to the improved visibility of the whitish lesions such as GAFG and SRCC for both experts and trainees when evaluated subjectively and objectively.

References

1. Ishibashi, F., et al., Exploring quality indicators for the detection of Helicobacter pylori-naïve gastric cancer: a cross-sectional nationwide survey. Clinical Endoscopy, 2023. Apr 4. doi: 10.5946/ce.2022.167.
2. Abe, S., et al., Emerging texture and color enhancement imaging in early gastric cancer. Dig Endosc, 2022. 34(4): p. 714-720.
3. Sugimoto, M., et al., Efficacy of high-vision transnasal endoscopy using texture and colour enhancement imaging and narrow-band imaging to evaluate gastritis: a randomized controlled trial. Ann Med, 2022. 54(1): p. 1004-1013.
4. Abe, S., et al., Visibility of early gastric cancer in texture and color enhancement imaging. DEN Open, 2022. 2(1): p. e46.
5. Ishikawa, T., et al., Efficacy of Texture and Color Enhancement Imaging in visualizing gastric mucosal atrophy and gastric neoplasms. Sci Rep, 2021. 11(1): p. 6910.
6. Kawasaki, A., et al., Usefulness of third-generation narrow band imaging and texture and color enhancement imaging in improving visibility of superficial early gastric cancer: A study using color difference. DEN Open, 2022. 3(1): p. e186.

Introduction

Fundic gland polyp associated with proton pump inhibitor (PPI-FGP) caused by long-term administration of proton pump inhibitors is known to be larger than normal FGP and have an edematous appearance, however, the endoscopic differentiation from normal FGP is sometimes difficult. Recently, Texture and Color Enhancement Imaging (TXI) has emerged as a novel imaged enhancement technology from Olympus Corporation and is expected to improve the visibility of the lesions by enhancing color tone and structure. The enhancement of color contrast of the mode1 is superior to that of mode2 in accordance with the color enhancement of the mode1 algorithm; however, the naturalness in mode2 is better than that of the mode1¹. Recently, we previously detected the gray color sign as a novel endoscopic finding that was clearly visible by TXI in the edematous appearance of PPI-FGP, and defined that it was gland duct dilatation below the surface containing mucus and other substances in histopathology.

Aims & Methods

The aim of this study was to evaluate the usefulness of TXI compared with white light imaging (WLI) in the visibility of the gray color sign in PPI-FGP. We enrolled 23 PPI-FGP lesions, endoscopically imaged with WLI, TXI-1, TXI-2, and Narrow Band Imaging (NBI) between April 2021 and October 2022. All PPI-FGP lesions were diagnosed by biopsy specimen histopathologically. Ten endoscopists (5 trainees, 5 experts) evaluated the images and scored the visibility of the gray color sign in TXI-1, TXI-2, and NBI compared to WLI. Visibility changes were scored by endoscopists as follows: 5, improved; 4, somewhat improved; 3, equivalent; 2, somewhat decreased; and 1, decreased. For total scores, 40 points or more was considered improved visibility, 21–39 points was comparable to WLI, and a score of less than 20 was considered decreased visibility. Inter-rater reliability was also evaluated using intraclass correlation (ICC). In addition, the color difference (ΔE*) of the gray color sign was calculated using CIELAB (color space system: L* a* b*) defined by Commission internationale de l'éclairage (CIE), and compared between WLI, TXI-1 and TXI-2.

Results

The visibility and ICC scores of TXI-1 and TXI-2 in trainees, experts, and all endoscopists are shown in Table1. TXI-1 and TXI-2 showed improved visibility of the gray color sign in PPI-FGP for all endoscopists. There was no significant difference in the visibility scores between trainees and experts for both TXI-1 and TXI-2. Compared with WLI, TXI showed improved visibility; TXI-1 82.6% (19/23), TXI-2 86.9% (20/23). In contrast, NBI showed decreased visibility; 78.2% (18/23). The intra-rater reliability for TXI-1 and TXI-2 were “almost perfect” for trainees and experts. TheΔE* values were 12.0 for WLI, 22.3 for TXI-1, and 25.9 for TXI-2 (WLI vs. TXI-1: p< 0.01, WLI vs. TXI-2: p< 0.01). In summary, improved visibility of the gray color sign in PPI-FGP was achieved for TXI-1 and TXI-2 compared to WLI for both trainees and experts and inter-rater reliability between trainees and experts was good. The ΔE* values were significantly larger in TXI-1 and TXI-2 compared to WLI.

Gray color sign		All endoscopists　(N:10)	Trainees　(N:5)	Experts　(N:5)	Trainees vs.Experts (P value)
TXI	Mode 1	44.9 ± 4.3	22.7 ± 2.1	22.2 ± 2.3	0.50
	Mode 2	42.9 ± 4.6	21.8 ± 2.4	21.1 ± 2.3	0.32
ICC（2.1）	Mode 1	0.931	0.858	0.864
	Mode 2	0.927	0.889	0.817

Conclusion

The usefulness of TXI compared with WLI led to the improved visibility of the gray color sign in PPI-FGP for both trainees and experts when evaluated subjectively and objectively.

References

1. Sato T et al. Journal of Healthcare Engineering Volume 2021.

Introduction

Linked color imaging (LCI), a unique image-enhanced endoscopy technique, expands the color range to enhance the recognition of subtle mucosal differences, facilitating early lesion detection. Recently, the advantage of LCI in cancer visibility and detection has been reported especially in Helicobacter pylori (H. pylori)-negative gastric cancer including cases post-eradication.¹ However, the correlations between the color of LCI’s visualized mucosa and histological findings have not been thoroughly investigated.

Aims & Methods

This study aimed to investigate relationships between color values and histological findings visualized by LCI in H. pylori-negative gastric cancer.
Thirty-two patients with H. pylori-negative, differentiated-type intramucosal gastric cancer (≤20 mm) who underwent endoscopic submucosal dissection were retrospectively reviewed. Images captured with LCI and white light imaging (WLI) were analyzed using the CIE1976 (L^*a^*b^*) color space, as defined by the International Commission on Illumination (CIE).² Three regions of interest, each measuring 10 × 10 pixels, were set on the malignant tumor and adjacent mucosa to the border. The values of a^*(red-green) and b^* (yellow-blue) and the color difference (ΔE), which represents the overall difference between the two colors, were calculated. Histopathological evaluation using Hematoxylin-Eosin stained specimens was performed to highlight the demarcation between cancerous and noncancerous mucosa in a width of 1.0 mm inside and outside the lesion. Vascular density, glandular density, mucosal thickness, and the degrees of intestinal metaplasia (IM) were measured. Vascular density was calculated as the percentage of the occupied blood vessels in an area up to 200 μm from the surface. And the proportion of IM relative to the glands was measured and classified as the severe IM (≥60%), moderate IM (≥30% and <60%), or mild IM (<30%) groups.

Results

LCI significantly increased ΔE between the cancer and surrounding mucosa compared with WLI (P < 0.001); however, no significant differences in Δa^* and Δb^* were observed between LCI and WLI. Moderate correlations were observed between LCI a^* values and vascular density (ρ = 0.39, P < 0.001) and between LCI b^* values and the proportion of IM (ρ = −0.49, P < 0.001). Furthermore, the vascular density of cancer in the 0−100 μm depth showed a moderate correlation with the LCI a^* values (ρ = 0.41, P < 0.001). Severe IM significantly decreased the LCI b^* values compared with mild and moderate IM (P = 0.02, P < 0.001).

Conclusion

LCI quantitatively visualizes the superficial vascularity of cancer lesions and the presence of IM of the background mucosa in H. pylori-negative patients. It is a potential noninvasive tool for gastric cancer risk stratification and early detection.

References

1. Kato M, Ono S, Kawada K et al. Diagnostic performance of linked color imaging for gastric cancer by Helicobacter pylori infection status: a subanalysis of the large-scale, multicenter randomized controlled trial LCI-FIND. Helicobacter 2024; 29: e1308.
2. Kuehni RG. Color-tolerance data and the tentative CIE 1976 L a b formula. J Opt Soc Am 1976; 66: 497–500.

Disclosure

Shoko Ono has received lecture and/or consulting fees from Fujifilm.

Introduction

Recently, artificial intelligence (AI)-based diagnostic support tools for early gastric cancer have been developed and reported to be superior to endoscopists (accuracy: 70% and sensitivity: 85%).¹ However, These tools could not guarantee reliable diagnostic accuracy in clinical practice. In previous reports, magnifying endoscopy has been recognized as superior to white-light imaging endoscopy for endoscopic diagnosis of early gastric cancers. Therefore, we developed an AI-based diagnostic support system using magnifying endoscopy with narrow band imaging (M-NBI) for early gastric cancers² and improved its application in clinical practice using nondegraded images obtained from selective depth inspection (SDI) output for real-time diagnosis. This study is the first to create an AI-based diagnostic support system using non-degraded M-NBI images obtained from SDI output, as several previous papers have analyzed damaged M-NBI images that were converted from various recording devices.^3,4

Aims & Methods

We built a new AI system (M-NBI AI) which was assembled using four different image recognition models with non-degraded M-NBI images (normal mucosa:1776 images, gastric cancers: 1947 images, and non-neoplastic lesions: 2451 images). We evaluated the performance of this M-NBI AI for diagnosis of early gastric cancer. The diagnostic performances of M-NBI AI and endoscopists (five specialists and five non-specialists) were compared using non-degraded M-NBI images (three images per lesion) of 50 early gastric cancer and 50 non-cancerous lesions. Early gastric cancers included histopathological types of well, moderately, and poorly differentiated adenocarcinomas and signet-ring cell adenocarcinomas. The primary outcome was the superiority of the M-NBI AI (based on accuracy) over the endoscopists. The secondary outcome was the superiority of the M-NBI AI (based on sensitivity) over the endoscopists.

Results

	M-NBI AI	Endoscopists
		Specialists	Non-specialists
Accuracy, % (95% CI)	87.0 (0.80–0.94)	80.0 (0.72–0.88)	71.0 (0.62–0.79)
Sensitivity, % (95% CI)	86.3 (0.77–0.96)	74.2 (0.63–0.85)	70.6 (0.58–0.83)
Specificity, % (95% CI)	88.0 (0.79–0.97)	89.0 (0.80–0.99)	71.0 (0.59–0.84)
PPV, % (95% CI)	88.0 (0.79–0.97)	92.0 (0.84–0.99)	72.0 (0.60–0.84)
NPV, % (95% CI)	86.0 (0.76–0.96)	68.0 (0.55–0.81)	70.0 (0.57–0.83)
PPV, positive predictive value; NPV, negative predictive value

The M-NBI AI was superior to the non-specialists based on accuracy (87.0%, 95%CI: 0.80–0.94 versus 71.0 %, 95%CI: 0.62–0.79; p<0.01), without being superior to the specialists (87.0%, 95%CI: 0.80–0.94 versus 80.0%, 95%CI: 0.72–0.88; p=0.18). The M-NBI AI was superior to the specialists and non-specialists based on sensitivity (86.3%, 95%CI: 0.77–0.96 versus 74.2%, 95%CI: 0.63–0.85 and 70.6%, 95%CI: 0.58–0.83; p<0.05, respectively).

Conclusion

The M-NBI AI was created as a new AI system that could be implemented for current endoscopy systems as a real-time diagnostic support tool for early gastric cancers. It demonstrated a robust performance and may indicate equalization of diagnostic accuracy and superadded effect over the white-light endoscopy for diagnosis of early gastric cancers in clinical practice.

References

1. Ishioka M et al. Dig Endosc. 2022. doi: 10.1111/den.14455.
2. Ueyama H et al. J Gastroenterol Hepatol. 2021;36(2):482-489.
3. Horiuchi Y et al. Dig. Dis. Sci. 2020;65:1355–1363.
4. He X et al. Gastrointest Endosc. 2022;95(4):671-678.

Introduction

There have been many reports on the usefulness of magnifying endoscopy with image-enhanced endoscopic techniques. In recent years, the magnifying endoscopy simple diagnostic algorithm for early gastric cancer (MESDA-G)^１ has been proposed as a unified diagnostic system. However, it is a “static” diagnostic algorithm that uses still images. We focused on real-time red blood cell flow in subepithelial microvascular visualized by magnifying endoscopy, and clarified that microvascular blood flow rate was significantly lower in early gastric cancer (EGC) than in benign patchy redness in the pilot study².
Moreover, we uniquely developed an automated blood flow rate analysis system (hereinafter “analysis system”) and calculated the cut-off value (1090.9um/sec) for endoscopic diagnosis of EGC using the test dataset. However, comparative studies on diagnostic accuracy between endoscopists and analysis system have not yet been analyzed.

Aims & Methods

The aim of this study was to compare the qualitative diagnostic accuracy of EGC between endoscopists and analysis system. We retrospectively reviewed magnifying endoscopy with blue laser imaging (M-BLI) videos of differentiated-type EGC and patchy redness at our hospital between December 2017 and September 2021. M-BLI videos of 31 differentiated-type EGCs and 40 patchy redness in which red blood cell flow in subepithelial microvascular was visible were included in this study. In the analysis system group, the diagnosis was made according to the above-mentioned cut-off value (1.09 mm/sec) for cancer/non-cancer. In the endoscopist group, 9 endoscopists (5 experts and 4 trainees) reviewed these M-BLI videos and made the diagnosis as cancer/non-cancer according to MESDA-G. We evaluated the diagnostic accuracy in each group, such as sensitivity/specificity/positive predictive value (PPV)/negative predictive value (NPV).

Results

In 31 EGCs, there were more men than women (22/9), the mean age was 72.2±9.5 years, the tumor location was U/M/L=2/8/21, the macroscopic type was elevated/depressed=8/23, the histological type was tub1/tub2/pap=24/6/1, and depth of invasion was M/SM=27/4. In 40 patchy redness, there were more men than women (28/12), the mean age was 69.0±9.7 years, and the location was U/M/L=3/12/25. With regard to diagnostic accuracy, sensitivity/specificity/PPV/NPV was 90.3/89.7/87.2/92.3% in the analysis system group, 85.9/87.2/80.0/85.5% in expert endoscopists, and 70.0/82.7/80.6/71.0% in trainees endoscopists, respectively.

	Analysis system	Endoscopists
		Experts (n=5)	Trainees (n=4)	All (n=9)
Sensitivity % (95%CI)	90.3 (0.68-0.95)	85.9 (57.0-87.6)	70.0 (54.8-85.8)	77.9 (55.7-86.6)
Specificity % (95%CI)	89.7 (0.79-0.98)	87.2 (65.4-90.8)	82.7 (64.3-92.4)	85.0 (64.8-91.7)
PPV % (95%CI)	87.2 (0.74-0.98)	80.0 (55.5-84.0)	80.6 (59.8-90.8)	80.3 (58.0-87.9)
NPV % (95%CI)	92.3 (0.73-0.96)	85.5 (61.3-85.5)	71.0 (60.0-87.2)	78.3 (60.8-86.4)

Conclusion

The automated blood flow rate analysis system showed higher diagnostic accuracy in the differential diagnosis between differentiated-type EGC and patchy redness compared with endoscopists. It is suggested that the analysis system may be useful as a new diagnostic modality for EGC and could potentially diagnose lesions that are difficult for endoscopists to diagnose.

References

1. Muto M et al. Dig Endosc. 2016. doi: 10.1111/den.12638.
2. Ueyama H et al. J Gastroenterol Hepatol. 2021. doi: 10.1111/jgh.15425.

Introduction

​Endocytoscopy (ECS), an ultrahigh-magnification contact-type endoscopy, enables real-time visualization of gastrointestinal mucosal and neoplastic cells. As a result, ECS enhance diagnostic precision as a form of optical biopsy. However, the reliability of ECS diagnosis is contingent upon adequate staining, which remains a considerable challenge in the stomach due to the abundance of mucus and inflammatory exudates that hinder optimal visualization. Weak vital staining can easily reduce the reliability of ECS diagnosis. Texture and Color Enhancement Imaging (TXI), a digital image enhancement modality developed by Olympus, enhances three key imaging elements—brightness, texture, and color tone—to optimize lesion visualization even under suboptimal staining conditions. Consequently, TXI may augment the diagnostic utility of ECS.

Aims & Methods

The aim of this study was to evaluate whether TXI enhances the diagnostic performance of ECS in early gastric cancer. Twenty-eight patients with 30 gastric cancers scheduled for magnifying endoscopic examination at Nippon Medical School Tama Nagayama Hospital between February 2024 and March 2025 were prospectively enrolled. All ECS procedures were performed with GIF-H290EC (Olympus Co., Tokyo, Japan) and the video processors EVIS X1 (Olympus Co., Tokyo, Japan). For in vivo dyeing, double staining with crystal violet and methylene blue was used. ECS was performed with and without TXI in both cancer and non-cancerous legions. ECS observation is performed by first taking photographs without TXI, and then taking photographs of the same area using the TXI. From each lesion, five ECS images with and without TXI were selected, resulting in a blinded and randomized image catalog (comprising 300 images from 30 gastric cancers and 280 images from 28 non-tumor areas). Two endoscopists independently assessed the images using a numerical rating scale (NRS, 0–10) to evaluate the visibility of nuclear atypia and structural cellular atypia. Diagnostic accuracy was assessed against pathological diagnosis as the gold standard. ECS diagnoses were rendered based on previously established criteria, wherein lesions exhibiting high-grade atypia were classified as cancer (Kaise M, et al. Endoscopy. 2015).

Results

The overall accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for EGC diagnosis by the two endoscopists were 82.5%, 84.3%, 80.7%, 81.3%, and 83.8%, respectively. The rate of interobserver agreement between the two endoscopists was high, with a kappa coefficient of κ = 0.797. Notably, diagnostic accuracy was significantly higher in the TXI images compared to the non-TXI images (85.2% vs. 79.0%, p = 0.0027). While the NRS scores for structural atypia did not differ significantly between the TXI and non-TXI images (4.90 vs. 4.87, p = 0.61), the NRS scores for nuclear atypia were significantly elevated in the TXI images (6.88 vs. 5.88, p < 0.0001).

Conclusion

​The integration of TXI with ECS significantly enhances the visualization of nuclear atypia and improves diagnostic accuracy in the diagnosis of gastric cancer. This synergistic approach facilitates superior optical biopsy capabilities, enhancing its clinical utility in the endoscopic diagnosis of early gastric cancer.

References

Kaise M, Ohkura Y, Iizuka T, Kimura R, Nomura K, Kuribayashi Y, et al. Endocytoscopy is a promising modality with high diagnostic accuracy for gastric cancer. Endoscopy. 2015;47:19–25.

Introduction

Non-ampullary duodenal epithelial tumors (NADETs) have been reported to exhibit specific endoscopic and clinicopathological features based on mucin phenotypes: the gastric phenotype (GP) and the intestinal phenotype (IP) ¹. However, NADETs with the gastrointestinal mixed phenotype (MP) are often observed in clinical practice. And, the endoscopic and clinicopathological features including subclassification of NADETs with MP have not been well investigated.

Aims & Methods

The aim of this study is to clarify the endoscopic and clinicopathological features of each phenotype group; GP, IP, and MP. NADETs were collected from a database of endoscopic and surgical resections performed between February 2010 and December 2021 at our hospital. All NADETs were classified into three groups immunohistochemically: GP, IP, and MP. In addition, we subclassified MP into the gastric predominant phenotype (GPP) and the intestinal predominant phenotype (IPP) based on the predominance of gastric or intestinal phenotypic expression. The endoscopic and clinicopathological findings were compared between each phenotype group; GP, GPP, IPP, and IP.

Results

A total of 148 NADETs in 142 patients were classified into GP (n=16), GPP (n=16), IPP (n=43), and IP (n=73). As for the tumor location (first/second/third portion), GP (10/6/0) and GPP (9/5/2) were significantly more often located in the first portion compared to IPP (10/30/3) and IP (12/55/6) (p ‹ 0.01). The mean tumor size of GP (14.4 mm) and GPP (19.4 mm) were significantly larger than IPP (11.0 mm) and IP (10.7 mm) (p ‹ 0.01). In Vienna classification (Category 3/4 or 5), the proportion of category 4 or 5 was significantly higher in GP (7/9) and GPP (2/14) than in IPP (35/8) and IP (71/2) (p ‹ 0.01). Regarding the endoscopic findings (Table), the frequency of reddish coloration, 0-I macroscopic type, and lobular/granular pattern in white-light imaging was significantly higher in GP and GPP than in IPP and IP (p ‹ 0.01). The frequency of irregular microsurface pattern, negativity of white opaque substance, positivity of oval-shaped marginal epithelium and dilatation of the intervening part in magnifying endoscopy with narrow-band imaging was significantly higher in GP and GPP than in IPP and IP (p ‹ 0.01). In summary, the endoscopic and clinicopathological features of IPP were similar to those of IP, and GPP were similar to GP. The malignant potential of NADETs was presented in the descending order as follows; GPP › GP › IPP ≒ IP, and GPP demonstrated the highest malignant potential among 4 types.

	GP	GPP	IPP	IP
White-light imaging	n=16	n=16	n=43	n=73
Coloration (red/white)	13/3	11/5	17/26	21/52
Macroscopic type (0-I/0-IIa/0-IIc)	11/1/3	10/4/1	5/21/17	11/38/23
Lobular/granular pattern (%)	62.5%	62.5%	7.0%	11.0%
Magnifying endoscopy with narrow-band imaging	n=12	n=14	n=41	n=70
Microsurface pattern (regular/irregular/absent)	11/1/0	5/9/0	34/7/0	59/11/0
White opaque substance (%)	25.0%	64.3%	90.2%	90.0%
Oval-shaped marginal epithelium (%)	58.3%	64.3%	9.8%	4.3%
Dilatation of the intervening part (%)	75.0%	64.3%	22.0%	12.9%

Conclusion

NADETs exhibited specific features based on mucin phenotypes as previous reports¹, and MP (GPP and IPP) demonstrates the endoscopic and clinicopathological features of its predominant mucin phenotype (GP or IP). The accurate endoscopic diagnosis based on mucin phenotypes is necessary for appropriate treatment approach of NADETs, since the malignant potential of NADETs may differ between each mucin phenotype.

References

1. Akazawa Y. et al. Digestion 2021;102:663–670 DOI: 10.1159/000508040

Disclosure

Nothing.