Endocytoscopic microvasculature evaluation is a reliable new diagnostic method for colorectal lesions (with video)

Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review

This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of patients with ulcerative colitis. The use of artificial intelligence (AI) has increased substantially across several medical fields, including gastrointestinal endoscopy. Evidence suggests that it may be helpful to predict histologic remission and relapse, which would be beneficial because current histological diagnosis is limited by the inconvenience of obtaining biopsies and the high cost and time-intensiveness of pathological diagnosis. MEDLINE and the Cochrane Central Register of Controlled Trials were searched for studies published between January 1, 2000, and October 31, 2023. Nine studies fulfilled the selection criteria and were included; five evaluated the prediction of histologic remission, two assessed the prediction of clinical outcomes, and two evaluated both. Seven were prospective observational or cohort studies, while two were retrospective observational studies. No randomized controlled trials were identified. AI-assisted colonoscopy demonstrated sensitivity between 65 %-98 % and specificity values of 80 %-97 % for identifying histologic remission. Furthermore, it was able to predict future relapse in patients with ulcerative colitis. However, several challenges and barriers still exist to its routine clinical application, which should be overcome before the true potential of AI-assisted colonoscopy can be fully realized.

Endoscopic characterization of neoplastic and non-neoplastic lesions in inflammatory bowel disease: systematic review in the era of advanced endoscopic imaging

Background

Current guidelines strongly recommend the use of validated classifications to support optical diagnosis of lesions with advanced endoscopic imaging in the lower gastrointestinal tract. However, the optimal strategy in inflammatory bowel disease (IBD) is still a matter of debate.

Objectives

To analyze the accuracy of endoscopic classifications or single predictors for in vivo lesion characterization during endoscopic surveillance of IBD with advanced endoscopic imaging.

Design

Systematic review.

Data sources and methods

Medline and PubMed were used to extract all studies which focused on lesion characterization of neoplastic and non-neoplastic lesions in IBD. The diagnostic accuracy of endoscopic classifications and single endoscopic predictors for lesion characterization were analyzed according to type of patients, lesions, and technology used. When available, the rates of true and false positives or negatives for neoplasia were pooled and the sensitivity (SE), specificity (SP), positive predictive value, and negative predictive value (NPV) were calculated.

Results

We included 35 studies (2789 patients; 5925 lesions - 1149 neoplastic). Advanced endoscopic imaging included dye-based chromoendoscopy, virtual chromoendoscopy (VCE), magnification and high-definition endoscopy, confocal laser endomicroscopy (CLE), endocytoscopy, and autofluorescence imaging. The Kudo classification of pit patterns was most frequently used, with pooled SE 83%, SP 83%, and NPV 95%. The endoscopic criteria with the highest accuracy, with minimum SE ⩾ 90%, SP ⩾ 80%, and NPV ⩾ 90% were: the Kudo-IBD classification used with VCE (Fuji Intelligent Color Enhancement and i-SCAN); combined irregular surface and vascular patterns used with narrow band imaging; the Mainz classification used with CLE. Multiple clinical and technical factors were found to influence the accuracy of optical diagnosis in IBD.

Conclusion

No single endoscopic factor has yet shown sufficient accuracy for lesion characterization in IBD surveillance. Conventional classifications developed in the non-IBD setting have lower accuracy in IBD. The use of new classifications adapted for IBD (Kudo-IBD), and new technologies based on in vivo microscopic analysis show promise.

A Review of Colonoscopy in Intestinal Diseases

Since the development of the fiberoptic colonoscope in the late 1960s, colonoscopy has been a useful tool to diagnose and treat various intestinal diseases. This article reviews the clinical use of colonoscopy for various intestinal diseases based on present and future perspectives. Intestinal diseases include infectious diseases, inflammatory bowel disease (IBD), neoplasms, functional bowel disorders, and others. In cases of infectious diseases, colonoscopy is helpful in making the differential diagnosis, revealing endoscopic gross findings, and obtaining the specimens for pathology. Additionally, colonoscopy provides clues for distinguishing between infectious disease and IBD, and aids in the post-treatment monitoring of IBD. Colonoscopy is essential for the diagnosis of neoplasms that are diagnosed through only pathological confirmation. At present, malignant tumors are commonly being treated using endoscopy because of the advancement of endoscopic resection procedures. Moreover, the characteristics of tumors can be described in more detail by image-enhanced endoscopy and magnifying endoscopy. Colonoscopy can be helpful for the endoscopic decompression of colonic volvulus in large bowel obstruction, balloon dilatation as a treatment for benign stricture, and colon stenting as a treatment for malignant obstruction. In the diagnosis of functional bowel disorder, colonoscopy is used to investigate other organic causes of the symptom.

Real-World Experience of AI-Assisted Endocytoscopy Using EndoBRAIN—An Observational Study from a Tertiary Care Center

Background and Aims Precise optical diagnosis of colorectal polyps could improve the cost-effectiveness of colonoscopy and reduce polypectomy-related complications. We conducted this study to estimate the diagnostic performance of visual inspection alone (WLI + NBI) and of EndoBRAIN (endocytoscopy-computer-aided diagnosis [EC-CAD]) in identifying a lesion as neoplastic or nonneoplastic using EC in real-world scenario.

Methods In this observational, prospective, pilot study, a total of 55 polyps were studied in the patients aged more than or equal to 18 years. EndoBRAIN is an artificial intelligence (AI)-based system that analyzes cell nuclei, crypt structure, and vessel pattern in differentiating neoplastic and nonneoplastic lesion in real-time. Endoscopist assessed polyps using white light imaging (WLI), narrow band imaging (NBI) initially followed by assessment using EC with NBI and EC with methylene blue staining. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of endoscopist and EndoBRAIN in identifying the neoplastic from nonneoplastic polyp was compared using histopathology as gold-standard.

Results A total of 55 polyps were studied, in which most of them were diminutive (36/55) and located in rectum (21/55). The image acquisition rate was 78% (43/55) and histopathology of the majority was identified to be hyperplastic (20/43) and low-grade adenoma (16/43). EndoBRAIN identified colonic polyps with 100% sensitivity, 81.82% specificity (95% confidence interval [CI], 59.7–94.8%), 90.7% accuracy (95% CI, 77.86–97.41%), 84% positive predictive value (95% CI, 68.4–92.72%), and 100% negative predictive value. The sensitivity and negative predictive value were significantly greater than visual inspection of endoscopist. The diagnostic accuracy seems to be superior; however, it did not reach statistical significance. Specificity and positive predictive value were similar in both groups.

Conclusion Optical diagnosis using EC and EC-CAD has a potential role in predicting the histopathological diagnosis. The diagnostic performance of CAD seems to be better than endoscopist using EC for predicting neoplastic lesions.

Beyond complete endoscopic healing: Goblet appearance using an endocytoscope to predict future sustained clinical remission in ulcerative colitis

OBJECTIVES

Complete endoscopic healing, defined as Mayo endoscopic score (MES) = 0, is an optimal target in the treatment of ulcerative colitis (UC). However, some patients with MES = 0 show clinical relapse within 12 months. Histologic goblet mucin depletion has emerged as a predictor of clinical relapse in patients with MES = 0. We observed goblet depletion in vivo using an endocytoscope, and analyzed the association between goblet appearance and future prognosis in UC patients.

METHODS

In this retrospective cohort study, all enrolled UC patients had MES = 0 and confirmed clinical remission between October 2016 and March 2020. We classified the patients into two groups according to the goblet appearance status: preserved-goblet and depleted-goblet groups. We followed the patients until March 2021 and evaluated the difference in cumulative clinical relapse rates between the two groups.

RESULTS

We identified 125 patients with MES = 0 as the study subjects. Five patients were subsequently excluded. Thus, we analyzed the data for 120 patients, of whom 39 were classified as the preserved-goblet group and 81 as the depleted-goblet group. The patients were followed-up for a median of 549 days. During follow-up, the depleted-goblet group had a significantly higher cumulative clinical relapse rate than the preserved-goblet group (19% [15/81] vs. 5% [2/39], respectively; P = 0.02).

CONCLUSIONS

Observing goblet appearance in vivo allowed us to better predict the future prognosis of UC patients with MES = 0. This approach may assist clinicians with onsite decision-making regarding treatment interventions without a biopsy.

Brown slits for colorectal adenoma crypts on conventional magnifying endoscopy with narrow band imaging using the X1 system

BACKGROUND

Accurate diagnosis of colorectal premalignant polyps, including adenomas, is vital in clinical practice.

AIM

To investigate the diagnostic yields of novel findings of brown slits for adenomas.

METHODS

Patients who underwent colonoscopy at the Toyoshima Endoscopy Clinic were enrolled. Polyps sized ≥ 5 mm suspected of adenomas or clinically significant serrated polyps were included in the study. We defined the surface structures of colorectal polyps, which were brown curves inside and along the tubular glands identified using a combination of a new X1 system (Olympus Corporation) and a conventional magnifying colonoscope with non-staining narrow band imaging (NBI), as brown slits. The brown slits corresponded to slit-like lumens on endocytoscopy and histological crypt openings of an adenoma. We evaluated the diagnostic performance of brown slits for adenoma.

RESULTS

A total of 108 Lesions from 62 patients were eligible. The average age was 60.4 years and 41.9% were male. The mean polyp size was 7.45 ± 2.83 mm. Fifty-seven lesions were positive for brown slits. Histopathological diagnosis comprised 59 low-grade tubular adenomas, 16 sessile serrated lesions, and 33 hyperplastic polyps. Among 59 adenomas, 56 (94.9%) were positive for brown slits. Among 16 sessile serrated lesions, 0 (0%) was positive for brown slits. Among 33 hyperplastic polyps, 1 (3.0%) was positive for brown slits. The sensitivity, specificity, and accuracy of brown slits for adenoma were 94.9%, 98.0%, and 96.3%, respectively. The positive predictive value and negative predictive value of brown slits for adenoma were also excellent for 98.2%, and 94.1%, respectively.

CONCLUSION

Brown slits on conventional magnifying endoscopy with non-staining NBI using the X1 system were useful for diagnosing colorectal adenoma. The new endoscopy system could be examined using new standards.

Evaluation in real-time use of artificial intelligence during colonoscopy to predict relapse of ulcerative colitis: a prospective study

BACKGROUND AND AIMS

The use of artificial intelligence (AI) during colonoscopy is attracting attention as an endoscopist-independent tool to predict histologic disease activity of ulcerative colitis (UC). However, no study has evaluated the real-time use of AI to directly predict clinical relapse of UC. Hence, it is unclear whether the real-time use of AI during colonoscopy helps clinicians make real-time decisions regarding treatment interventions for patients with UC. This study aimed to establish the role of real-time AI in stratifying the relapse risk of patients with UC in clinical remission.

METHODS

This open-label, prospective, cohort study was conducted in a referral center. The cohort comprised 145 consecutive patients with UC in clinical remission who underwent AI-assisted colonoscopy with a contact-microscopy function. We classified patients into either the Healing group or Active group based on the AI outputs during colonoscopy. The primary outcome measure was clinical relapse of UC (defined as a partial Mayo score >2) during 12 months of follow-up after colonoscopy.

RESULTS

Overall, 135 patients completed the 12-month follow-up after AI-assisted colonoscopy. AI-assisted colonoscopy classified 61 patients as the Healing group and 74 as the Active group. The relapse rate was significantly higher in the AI-Active group (28.4% [21/74]; 95% confidence interval, 18.5%-40.1%) than in the AI-Healing group (4.9% [3/61]; 95% confidence interval, 1.0%-13.7%; P < .001).

CONCLUSIONS

Real-time use of AI predicts the risk of clinical relapse in patients with UC in clinical remission, which helps clinicians make real-time decisions regarding treatment interventions. (Clinical trial registration number: UMIN000036650.).

Evolving roles of magnifying endoscopy and endoscopic resection for neoplasia in inflammatory bowel diseases

Magnifying endoscopy is a useful technique to differentiate neoplasia from non-neoplastic lesions. Data regarding the clinical utility of magnifying endoscopy for neoplasia in patients with inflammatory bowel disease (IBD) has been emerging. While Kudo’s pit pattern types III-V are findings suggestive of neoplasia in non-IBD patients, these pit patterns are predictive of IBD-associated neoplasia as well. However, active chronic inflammatory processes, particularly regenerative changes, can mimic neoplastic pit patterns and may affect a meticulous evaluation of pit pattern diagnosis in patients with IBD. The clinical evidence regarding the utility of magnifying endoscopy with narrow band imaging or endocytoscopy has also been evolving in regard to the diagnosis of IBD-associated neoplasia. These advanced endoscopic techniques are promising for multiple reasons; not only for making an accurate diagnosis of neoplasia, but also in determining if endoscopic resection is appropriate for such lesions in patients with IBD. In this review, we discuss the diagnostic accuracy and limitations of magnifying endoscopy in assessing IBD-associated neoplasia and examine the feasibility and outcomes of endoscopic resection for these lesions.

Evaluation of Microvascular Patterns Alone Using Endocytoscopy with Narrow-Band Imaging for Diagnosing Gastric Cancer

INTRODUCTION

Although endocytoscopy (EC) with narrow-band imaging (NBI) is effective in diagnosing gastric cancer, no diagnostic system has been validated. We explored a specific diagnostic system for gastric cancer using EC with NBI.

METHODS

Equal numbers of images from cancerous and noncancerous areas (114 images each) were assessed by endoscopists with (development group: 33) and without (validation group: 28) specific training in magnifying endoscopy with NBI. Microvascular and microsurface patterns (MS) in each image were evaluated. Lesions were diagnosed as cancerous when patterns were deemed "irregular." The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of a diagnosis according to patterns on EC with NBI (microvascular pattern [MV] alone, MS alone, and both) were evaluated and compared between groups to determine the diagnostic performance.

RESULTS

In the development and validation groups, diagnoses based on the MV alone had significantly higher accuracy (91.7% vs. 76.3%, p < 0.0001 and 92.5% vs. 67.5%, p < 0.0001, respectively) and sensitivity (88.6% vs. 68.3%, p < 0.0001 and 89.5% vs. 38.6%, p < 0.0001, respectively) than those based on the MS alone. In both groups, there were no significant differences in diagnostic accuracy between using the MV alone and both patterns.

DISCUSSION/CONCLUSION

Evaluation of the MV alone is a simple and accurate diagnostic method for gastric cancer. This system could find widespread applications in clinical practice.

Combined endocytoscopy with pit pattern diagnosis in ulcerative colitis-associated neoplasia: Pilot study

OBJECTIVES

Ulcerative colitis-associated neoplasias (UCAN) are often flat with an indistinct boundary from surrounding tissues, which makes differentiating UCAN from non-neoplasias difficult. Pit pattern (PIT) has been reported as one of the most effective indicators to identify UCAN. However, regenerated mucosa is also often diagnosed as a neoplastic PIT. Endocytoscopy (EC) allows visualization of cell nuclei. The aim of this retrospective study was to demonstrate the diagnostic ability of combined EC irregularly-formed nuclei with PIT (EC-IN-PIT) diagnosis to identify UCAN.

METHODS

This study involved patients with ulcerative colitis whose lesions were observed by EC. Each lesion was diagnosed by two independent expert endoscopists, using two types of diagnostic strategies: PIT alone and EC-IN-PIT. We evaluated and compared the diagnostic abilities of PIT alone and EC-IN-PIT. We also examined the difference in the diagnostic abilities of an EC-IN-PIT diagnosis according to endoscopic inflammation severity.

RESULTS

We analyzed 103 lesions from 62 patients; 23 lesions were UCAN and 80 were non-neoplastic. EC-IN-PIT diagnosis had a significantly higher specificity and accuracy compared with PIT alone: 84% versus 58% (P < 0.001), and 88% versus 67% (P < 0.01), respectively. The specificity and accuracy were significantly higher for Mayo endoscopic score (MES) 0-1 than MES 2-3: 93% versus 68% (P < 0.001) and 95% versus 74% (P < 0.001), respectively.

CONCLUSIONS

Our novel EC-IN-PIT strategy had a better diagnostic ability than PIT alone to predict UCAN from suspected and initially detected lesions using conventional colonoscopy. UMIN clinical trial (UMIN000040698).

Clinical Efficacy of Endocytoscopy for Gastrointestinal Endoscopy

Endocytoscopy (EC) is a contact-type optical endoscope that allows in vivo cellular observation during gastrointestinal endoscopy and is now commercially available not only in Japan but also in Asian, European Union, and Middle Eastern countries. EC helps conduct a highly accurate pathological prediction without biopsy. Initially, EC was reported to be effective for esophageal diseases. Subsequently, its efficacy for stomach and colorectal diseases has been reported. In this narrative review, we searched for clinical studies that investigated the efficacy of EC. EC seems to accurately diagnose gastrointestinal diseases without biopsy. Most of the studies aimed to clarify the relationship between endocytoscopic findings of gastrointestinal neoplasia and pathological diagnosis. Some studies have investigated non-epithelial lesions or diseases, such as inflammatory bowel disease or infectious diseases. However, there are few high-level pieces of evidence, such as randomized trials; thus, further studies are needed.

Diagnostic performance in gastric cancer is higher using endocytoscopy with narrow-band imaging than using magnifying endoscopy with narrow-band imaging

BACKGROUND

For diagnosing gastric cancer, differences in the diagnostic performance between endocytoscopy with narrow-band imaging and magnifying endoscopy with narrow-band imaging have not been reported. We aimed to clarify these differences by analyzing diagnoses made by endoscopists in Japan.

METHODS

This single-center retrospective cohort study used 106 cancerous and 106 non-cancerous images obtained via both modalities (total, 424 images) for diagnosis. Sixty-one endoscopists with varying experience levels from 45 institutions were included. Diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated to determine the diagnostic performance of each modality and compared using the Mann-Whitney U test.

RESULTS

Among all endoscopists, diagnostic accuracy, sensitivity, positive predictive value, and negative predictive value were higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging (percentage [95% confidence interval]: 78.8% [76.4-83.0%] versus 72.2% [69.3-73.6%], p < 0.0001; 82.1% [78.3-85.9%] versus 64.2% [60.4-69.8%], p < 0.0001; 88.7% [82.6-90.7%] versus 78.5% [75.4-85.1%], p = 0.0023; 79.0% [75.3-80.5%] versus 68.5% [66.4-71.6%], p < 0.0001, respectively). In the magnifying endoscopy with narrow-band imaging-trained group, these values were also higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging (p < 0.0001, p = 0.0001, p = 0.0143, and p < 0.0001, respectively). Diagnostic accuracy, sensitivity, and negative predictive value were higher with endocytoscopy with narrow-band imaging than with magnifying endoscopy with narrow-band imaging in the magnifying endoscopy with narrow-band imaging-untrained group (p = 0.0041, p = 0.0049, and p = 0.0098, respectively).

CONCLUSIONS

Diagnostic performance was higher using endocytoscopy with narrow-band imaging than using magnifying endoscopy with narrow-band imaging. Our results may help change the technique used to diagnose gastric cancer.

Endocytoscopic intramucosal capillary network changes and crypt architecture abnormalities can predict relapse in patients with an ulcerative colitis Mayo endoscopic score of 1

OBJECTIVES

Recent studies have suggested the necessity of therapeutic intervention for patients with ulcerative colitis at high risk of clinical relapse with a Mayo endoscopic score (MES) of 1. The aim of this retrospective cohort study was to demonstrate the impact of intramucosal capillary network changes and crypt architecture abnormalities to stratify the risk of relapse in patients with an MES of 1.

METHODS

All included patients had an MES of ≤1 and confirmed sustained clinical remission between October 2016 and April 2019. We classified patients with an MES of 1 as "intramucosal capillary/crypt (ICC)-active" or "ICC-inactive" using endocytoscopic evaluation. We followed patients until October 2019 or until relapse; the main outcome measure was the difference in clinical relapse-free rates between ICC-active and ICC-inactive patients with an MES of 1.

RESULTS

We included 224 patients and analyzed data for 218 (82 ICC-active and 54 ICC-active with an MES of 1 and 82 with an MES of 0). During follow-up, among the patients with an MES of 1, 30.5% (95% confidence interval 20.8-41.6; 25/82) of the patients relapsed in the ICC-active group and 5.6% (95% confidence interval 1.2-15.4; 3/54) of the patients relapsed in the ICC-inactive group. The ICC-inactive group had a significantly higher clinical relapse-free rate compared with the ICC-active group (P < 0.01).

CONCLUSIONS

In vivo intramucosal capillary network and crypt architecture patterns stratified the risk of clinical relapse in patients with an MES of 1 (UMIN 000032580; UMIN 000036359).

Endocytoscopy: technology and clinical application in the lower GI tract

Endocytoscopy (EC) is now one of the valuable technologies in diagnosing colorectal tumors. Providing ultra-high-resolution white light images (520×), endocytoscopy attains the so called virtual histology or optical biopsy, making it a promising tool to diagnose colorectal lesions. Recent studies about artificial intelligence (AI) or computer aided diagnosis (CAD) are also increasingly reported. We investigate the current application of endocytoscopy, as well as the benefit of AI and CAD. Furthermore, we performed a meta-analysis comparing the diagnostic performance of endocytoscopy and magnified chromoendoscopy. In conclusion, this systematic review and meta-analysis supports the recent finding indicating the higher diagnostic performance of endocytoscope in the depth assessment of colorectal neoplasms.

Artificial Intelligence-assisted System Improves Endoscopic Identification of Colorectal Neoplasms

BACKGROUND & AIMS

Precise optical diagnosis of colorectal polyps could improve the cost-effectiveness of colonoscopy and reduce polypectomy-related complications. However, it is difficult for community-based non-experts to obtain sufficient diagnostic performance. Artificial intelligence-based systems have been developed to analyze endoscopic images; they identify neoplasms with high accuracy and low interobserver variation. We performed a multi-center study to determine the diagnostic accuracy of EndoBRAIN, an artificial intelligence-based system that analyzes cell nuclei, crypt structure, and microvessels in endoscopic images, in identification of colon neoplasms.

METHODS

The EndoBRAIN system was initially trained using 69,142 endocytoscopic images, taken at 520-fold magnification, from patients with colorectal polyps who underwent endoscopy at 5 academic centers in Japan from October 2017 through March 2018. We performed a retrospective comparative analysis of the diagnostic performance of EndoBRAIN vs that of 30 endoscopists (20 trainees and 10 experts); the endoscopists assessed images from 100 cases produced via white-light microscopy, endocytoscopy with methylene blue staining, and endocytoscopy with narrow-band imaging. EndoBRAIN was used to assess endocytoscopic, but not white-light, images. The primary outcome was the accuracy of EndoBrain in distinguishing neoplasms from non-neoplasms, compared with that of endoscopists, using findings from pathology analysis as the reference standard.

RESULTS

In analysis of stained endocytoscopic images, EndoBRAIN identified colon lesions with 96.9% sensitivity (95% CI, 95.8%-97.8%), 100% specificity (95% CI, 99.6%-100%), 98% accuracy (95% CI, 97.3%-98.6%), a 100% positive-predictive value (95% CI, 99.8%-100%), and a 94.6% negative-predictive (95% CI, 92.7%-96.1%); these values were all significantly greater than those of the endoscopy trainees and experts. In analysis of narrow-band images, EndoBRAIN distinguished neoplastic from non-neoplastic lesions with 96.9% sensitivity (95% CI, 95.8-97.8), 94.3% specificity (95% CI, 92.3-95.9), 96.0% accuracy (95% CI, 95.1-96.8), a 96.9% positive-predictive value, (95% CI, 95.8-97.8), and a 94.3% negative-predictive value (95% CI, 92.3-95.9); these values were all significantly higher than those of the endoscopy trainees, sensitivity and negative-predictive value were significantly higher but the other values are comparable to those of the experts.

CONCLUSIONS

EndoBRAIN accurately differentiated neoplastic from non-neoplastic lesions in stained endocytoscopic images and endocytoscopic narrow-band images, when pathology findings were used as the standard. This technology has been authorized for clinical use by the Japanese regulatory agency and should be used in endoscopic evaluation of small polyps more widespread clinical settings. UMIN clinical trial no: UMIN000028843.

A detailed comparison between the endoscopic images using blue laser imaging and three-dimensional reconstructed pathological images of colonic lesions

Blue laser/light imaging (BLI) is an image-enhanced endoscopy (IEE) technique that can provide an accurate diagnosis by closely observing the surface structure of various colonic lesions. However, complete correspondence between endoscopic images and pathological images has not been demonstrated. The aim of this study was to accurately compare endoscopic images and the pathological images using a three-dimensionally (3D) reconstructed pathological model. Continuous thin layer sections were prepared from colonic tissue specimens and immunohistochemically stained for CD34 and CAM5.2. Three-dimensional reconstructed images were created by superimposing immunohistochemically stained pathological images. The endoscopic image with magnifying BLI was compared with the top view of the 3D reconstructed image to identify any one-to-one correspondence between the endoscopic images and histopathological images using the gland orifices and microvessels as a guide. Using 3D reconstructed pathological images, we were able to identify the location on the endoscope image in cases of colonic adenocarcinoma, adenoma and normal mucosa. As a result, the horizontal plane of the endoscopic image and the vertical plane of the 2D pathological specimen were able to be compared, and we successfully determined the visible blood vessel depth and performed a detailed evaluation on magnifying BLI. Examples are as follows: (1) The median vasculature depth from the mucosal surface that could be recognized as vasculature on magnifying BLI was 29.4 μm. The median depth of unrecognizable vessels on magnifying BLI was 218.8 μm, which was significantly deeper than recognizable vessels. (2) Some brownish structures were suggested to potentially be not only dense vessels, vessel expansions, corrupted vessels but also bleeding or extravasation of erythrocytes. Overall, we demonstrated a new approach to matching endoscopic images and pathological findings using a 3D-reconstructed pathological model immunohistochemically stained for CD34 and CAM5.2. This approach may increase the overall understanding of endoscopic images and positively contribute to making more accurate endoscopic diagnoses.

Endocytoscopy with NBI has the potential to correctly diagnose diminutive colorectal polyps that are difficult to diagnose using conventional NBI

Background and study aims  Real-time diagnosis of colorectal polyps is needed to prevent unnecessary resection of benign polyps. The vessels in hyperplastic polyps sometimes mimic the characteristic meshed capillary network of neoplastic lesions on non-magnified narrow-band imaging (NBI). Endocytoscopy in conjunction with NBI (EC-NBI) enables more detailed vessel observation. The current study evaluated whether EC-NBI can accurately diagnose small colorectal lesions with visible vessels on non-magnified NBI. Patients and methods  This retrospective study was conducted from January to December 2016. During colonoscopy, lesion images were obtained using NBI and EC-NBI. On EC-NBI, lesions were classified as having "clear," "unclear," or "invisible" blood vessel margins. All specimens were resected and pathologically examined, and the association between vessel margin findings and pathological diagnosis was assessed. The lesion surface to vessel depth was measured in clear, unclear, and invisible lesions. Results  Among 114 adenomas, 108 were clear, while six were unclear. Among 36 hyperplastic polyps, eight were clear, while 28 were unclear. A micro-network (MN) pattern was seen in 106 of 114 adenomas, and four of 36 hyperplastic polyps. The sensitivity, specificity, correct diagnostic rate, and positive and negative predictive values of clear blood vessel margins or a MN pattern as an adenoma index were 98.2 %, 69.4 %, 91.3 %, 91.1 %, and 92.6 %, respectively. EC-NBI correctly diagnosed 69.4 % (25/36) of hyperplastic polyps. The lesion surface-blood vessel distance was greater in unclear versus clear lesions ( P  < 0.001), and invisible versus unclear lesions ( P  < 0.001). Conclusions  EC-NBI may effectively differentiate hyperplastic polyps with visible vessels from adenomas. Blood vessel depth affects visibility.

Advanced Endoscopic Imaging in Colonic Neoplasia

BACKGROUND

Endoscopic imaging is a rapidly evolving field with a constant influx of new concepts and technologies. Since the introduction of video endoscopy and subsequently high-definition imaging as the first revolutions in gastrointestinal endoscopy, several technologies of virtual chromoendoscopy have been developed and brought to the market in the past decade, which have shaped and revolutionized for a second time our approach to endoscopic imaging. In parallel to these developments, microscopic imaging technologies, such as endomicroscopy and endocytoscopy, allow us to examine single cells within the mucosa in real time, thereby enabling histological diagnoses during ongoing endoscopy.

SUMMARY

In this review, we provide an overview on the technical background of different technologies of advanced endoscopic imaging, and then review and discuss their role and applications for the diagnosis and management of colorectal neoplasms as well as limitations and challenges that exist despite all technological improvements.

KEY MESSAGES

Technologies of advanced endoscopic imaging have profound impact not only on our imaging capabilities, they are also about to fundamentally change our approach to managing lesions in the gastrointestinal tract: not every lesion found during colonoscopy has to be excised or sent for histopathologic evaluation. However, before this becomes widespread reality, major obstacles such as patient acceptance, adoption by less trained endoscopists, and also legal aspects need to carefully addressed. The development of computer-aided diagnosis and artificial intelligence algorithms hold the potential to overcome the obstacles associated with the concept of optical biopsy and will most likely fundamentally facilitate, shape, and change decision making in the management of colorectal lesions.

Multicentre prospective evaluation of real-time optical diagnosis of T1 colorectal cancer in large non-pedunculated colorectal polyps using narrow band imaging (the OPTICAL study)

OBJECTIVE

This study evaluated the preresection accuracy of optical diagnosis of T1 colorectal cancer (CRC) in large non-pedunculated colorectal polyps (LNPCPs).

DESIGN

In this multicentre prospective study, endoscopists predicted the histology during colonoscopy in consecutive patients with LNPCPs using a standardised procedure for optical assessment. The presence of morphological features assessed with white light, and vascular and surface pattern with narrow-band imaging (NBI) were recorded, together with the optical diagnosis, the confidence level of prediction and the recommended treatment. A risk score chart was developed and validated using a multivariable mixed effects binary logistic least absolute shrinkage and selection (LASSO) model.

RESULTS

Among 343 LNPCPs, 47 cancers were found (36 T1 CRCs and 11 ≥T2 CRCs), of which 11 T1 CRCs were superficial invasive T1 CRCs (23.4% of all malignant polyps). Sensitivity and specificity for optical diagnosis of T1 CRC were 78.7% (95% CI 64.3 to 89.3) and 94.2% (95% CI 90.9 to 96.6), and 63.3% (95% CI 43.9 to 80.1) and 99.0% (95% CI 97.1 to 100.0) for optical diagnosis of endoscopically unresectable lesions (ie, ≥T1 CRC with deep invasion), respectively. A LASSO-derived model using white light and NBI features discriminated T1 CRCs from non-invasive polyps with a cross-validation area under the curve (AUC) of 0.85 (95% CI 0.80 to 0.90). This model was validated in a temporal validation set of 100 LNPCPs (AUC of 0.81; 95% CI 0.66 to 0.96).

CONCLUSION

Our study provides insights in the preresection accuracy of optical diagnosis of T1 CRC. Sensitivity is still limited, so further studies will show how the risk score chart could be improved and finally used for clinical decision making with regard to the type of endoresection to be used and whether to proceed to surgery instead of endoscopy.

TRIAL REGISTRATION NUMBER

NTR5561.

Fully automated diagnostic system with artificial intelligence using endocytoscopy to identify the presence of histologic inflammation associated with ulcerative colitis (with video)

BACKGROUND AND AIMS

In the treatment of ulcerative colitis (UC), an incremental benefit of achieving histologic healing beyond that of endoscopic mucosal healing has been suggested; persistent histologic inflammation increases the risk of exacerbation and dysplasia. However, identification of persistent histologic inflammation is extremely difficult using conventional endoscopy. Furthermore, the reproducibility of endoscopic disease activity is poor. We developed and evaluated a computer-aided diagnosis (CAD) system to predict persistent histologic inflammation using endocytoscopy (EC; 520-fold ultra-magnifying endoscope).

METHODS

We evaluated the accuracy of the CAD system using test image sets. First, we retrospectively reviewed the data of 187 patients with UC from whom biopsy samples were obtained after endocytoscopic observation. EC images and biopsy samples of each patient were collected from 6 colorectal segments: cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum. All EC images were tagged with reference to the biopsy sample's histologic activity. For validation samples, 525 validation sets of 525 independent segments were collected from 100 patients, and 12,900 EC images from the remaining 87 patients were used for machine learning to construct CAD. The primary outcome measure was the diagnostic ability of CAD to predict persistent histologic inflammation. Its reproducibility for all test images was also assessed.

RESULTS

CAD provided diagnostic sensitivity, specificity, and accuracy as follows: 74% (95% confidence interval, 65%-81%), 97% (95% confidence interval, 95%-99%), and 91% (95% confidence interval, 83%-95%), respectively. Its reproducibility was perfect (κ = 1).

CONCLUSIONS

Our CAD system potentially allows fully automated identification of persistent histologic inflammation associated with UC.

Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy performance. Pooled miss rates for polyps are as high as 22%, and associated interval colorectal cancers after colonoscopy are of concern. Optical biopsy, whereby in-vivo classification of polyps based on enhanced imaging replaces histopathology, has not been incorporated into routine practice because it is limited by interobserver variability and generally only meets accepted standards in expert settings. Real-time decision-support software has been developed to detect and characterise polyps, and also to offer feedback on the technical quality of inspection. Some of the current algorithms, particularly with recent advances in artificial intelligence techniques, match human expert performance for optical biopsy. In this Review, we summarise the evidence for clinical applications of computer-aided diagnosis and artificial intelligence in colonoscopy.

Advanced diagnostic endoscopy in the lower gastrointestinal tract: A review of JGES core sessions

At each of the 89th to the 92nd congresses of the Japan Gastroenterological Endoscopy Society, a series of featured discussion sessions concerning advanced diagnostic endoscopy in the lower gastrointestinal tract were presented. In total, 45 lectures were presented in this subject area. It was shown that, in recent years, several convenient and less invasive colonoscopic modalities have been developed. This review article summarizes these core sessions and the efficacy of the techniques discussed.

Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts

PURPOSE

Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists.

METHODS

We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated.

RESULTS

ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; [Formula: see text]), but similar to experts (87.8 vs 84.2%; [Formula: see text]). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; [Formula: see text]) and comparable to experts (93.5 vs 90.8%; [Formula: see text]).

CONCLUSIONS

ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.

In vivo detection of desmoplastic reaction using endocytoscopy: A new diagnostic marker of submucosal or more extensive invasion in colorectal carcinoma

The pathological determination of desmoplastic reaction (DR) in colorectal carcinoma is useful for predicting extensive submucosal invasion. The aim of the present study was to determine the usefulness of endocytoscopy (EC) in detecting DR. A total of 72 cases of colorectal cancer with submucosal invasion (EC classification, EC3b) were evaluated. The utility of fine granular structure (FGS) observed via EC for the prediction of the presence of DR in the most superficial tumor layers was assessed. Of the 72 lesions, 26 were positive for FGS, and the majority of these lesions (23/26, 88.5%) exhibited a DR, indicating a significant association. The overall accuracy of the identification of FGS via EC that was predictive of a DR was 87.3%. The presence of FGS detected by EC was significantly associated with the presence of a DR, suggesting the clinical usefulness of EC in planning treatment for colon cancer with submucosal invasion.

Narrow Band Imaging, Magnifying Chromoendoscopy, and Gross Morphological Features for the Optical Diagnosis of T1 Colorectal Cancer and Deep Submucosal Invasion: A Systematic Review and Meta-Analysis

OBJECTIVES

Optical diagnosis of T1 colorectal cancer (CRC) and T1 CRC with deep submucosal invasion is important in guiding the treatment strategy. The use of advanced imaging is not standard clinical practice in Western countries. A systematic review and meta-analysis were conducted comparing the accuracy of narrow band imaging (NBI), magnifying chromoendoscopy (MCE), and gross morphological features (GMF) seen with conventional view for the optical diagnosis of T1 CRC and deep submucosal invasion.

METHODS

A literature search identified studies on the optical diagnosis of T1 CRC and deep invasion using NBI, MCE, or GMF. Pooled estimates (PE) of sensitivity and specificity across studies reporting on NBI or MCE were compared using a random effects bivariate meta-regression approach, and a paired analysis focusing on studies that performed both techniques within the same patient was performed.

RESULTS

Thirty-three studies with 31,568 polyps were included. For the optical diagnosis of T1 CRC, both NBI (4 studies; PE 0.85, 95% confidence interval (CI) 0.75-0.91) and MCE (5 studies; PE 0.90, 95% CI 0.83-0.94) yielded higher sensitivity as compared with GMF (3 studies; range 0.21-0.46). No significant preference for NBI or MCE was found (sensitivity relative risk (RR) 0.93, 95% CI 0.79-1.09, P=0.37; specificity RR 0.98, 95% CI 0.86-1.11, P=0.74). Similarly, for the optical diagnosis of deep invasion, both NBI (13 studies; PE 0.77, 95% CI 0.68-0.84) and MCE (17 studies; PE 0.81, 95% 0.75-0.87) yielded higher sensitivity as compared with GMF (6 studies; range 0.18-0.88), and no significant preference for either NBI or MCE was found (sensitivity RR 0.92, 95% CI 0.76-1.11, P=0.36; specificity RR 1.00, 95% CI 0.96-1.04, P=0.92).

CONCLUSIONS

This review supports the use of advanced imaging techniques in preference to GMF to reduce the risk of performing piecemeal resection for T1 CRCs or unnecessary surgical referral for lesions amendable to endoscopic resection. A preference for either NBI or MCE could not be observed.

Evaluation of microvascular findings of deeply invasive colorectal cancer by endocytoscopy with narrow-band imaging

Background and study aims: Magnifying narrow-band imaging (NBI) is useful for examination of colorectal lesions, and endocytoscopy (EC) allows diagnostic evaluation of structural atypia, nuclear atypia, and vascular structures of colorectal tumors. The aim of this study was to examine surface microvessels in deep invasive colorectal cancer using EC with a new NBI video processor system. Patients and methods: We retrospectively assessed 132 colorectal neoplastic lesions: 81 adenomas, 18 intramucosal cancers, 4 submucosal slightly invasive cancers, and 29 submucosal deep invasive cancers. Detailed vascular findings commonly seen in submucosal deep invasive carcinomas included > 2-fold vasodilatation seen in adenomas, abnormal tortuosity and branching, loss of the micro-network pattern, caliber change in > 2 places in a single blood vessel, and blood vessels not visible in a line because they appear like a string of beads (beaded sign). Results: Univariate analysis revealed 4 vascular findings that were strongly predictive of submucosal deep invasion: vasodilatation (odds ratio [OR] 9.31; 95 % confidence interval [CI] 3.57 - 24.30), loss of the micro-network pattern (OR 61.60; 95 % CI 17.87 - 212.29), caliber change (OR 35.7; 95 % CI 9.16 - 139.14), and the beaded sign (OR 45.90; 95 % CI 5.50 - 382.73). Conclusions: Detailed assessment of ultra-magnified microvessels could improve the diagnostic performance for submucosal deep invasive cancer.

STUDY REGISTRATION

UMIN-CTR000014033.

Comparison of the endocytoscopic and clinicopathologic features of colorectal neoplasms

BACKGROUND AND AIM

Permeation of a vein or lymphatic vessel by a tumor is a key risk factor for lymph node metastasis. We examined the features of colorectal tumor vessel permeation using endocytoscopy, an ultra-high magnifying endoscopic system combined with a narrow-band imaging capability (EC-NBI).

PATIENTS AND METHODS

We examined 188 colorectal lesions using EC-NBI before treatment was started. We measured the diameters of tumor vessels on EC-NBI images. We used the tumor vessel diameter (the mean diameter of four tumor-associated vessels) and the variation in tumor vessel caliber (the difference between the maximum and minimum diameters of the vessels expressed as a proportion) to judge changes in vessel formation. We examined the relationship between these variables and the extent of venous or lymphatic vessel permeation (vessel invasion) established by immunohistochemical examination of the resected specimen using monoclonal antibodies against the CD34 and D2 - 40 antigens. We also analyzed the relationships between tumor vessel diameter, tumor vessel caliber variation, and depth of tumor invasion.

RESULTS

There were significant differences in tumor vessel diameter and caliber variation between tumors in situ and T1 - T3 carcinomas. In T1 carcinomas, larger tumor vessel diameter and greater tumor vessel caliber variation were significantly associated with venous permeation. In T2 and T3 carcinomas, greater tumor vessel caliber variation was significantly associated with venous permeation.

CONCLUSIONS

The vessel diameter and caliber variation of colorectal tumor microvasculature are associated with depth of invasion and venous permeation, especially in T1 carcinomas.

Role of magnifying colonoscopy for diagnosis of colorectal neoplasms: From the perspective of Japanese colonoscopists

Colorectal cancer is the third leading cause of cancer-related death. As the therapeutic strategy for colorectal cancer depends on the clinical stage of the tumor, precise and accurate staging is necessary prior to treatment decision-making. Colonoscopy is an essential tool for detection and prevention of colorectal cancer, as it also allows for removal of adenomatous lesions. Using conventional endoscopy, however, it is sometimes difficult to differentiate neoplastic lesions from non-neoplastic lesions. Several new endoscopic technologies have been developed to provide a more precise diagnosis. Magnifying chromoendoscopy and narrow-band imaging endoscopy with or without magnification are invaluable not only for distinction of colorectal neoplastic lesions from non-neoplastic lesions, but also for the accurate diagnosis of invasion depth in colorectal cancers. Based on an accumulation of a large number of clinical data, the use of magnifying colonoscopy has become inevitable for the prediction of histology and the diagnosis of invasion depth of colorectal neoplasms in Japan.

Application and Efficacy of Super-Magnifying Endoscopy for the Lower Intestinal Tract

Endoscopy plays a significant role in the diagnosis, management, and surveillance of colorectal cancer (CRC) and inflammatory bowel diseases (IBDs). Moreover, magnifying endoscopy and image-enhanced endoscopy has a crucial role in the clinical setting. Recently, a super-magnifying endoscope has been developed, and two devices, confocal laser endomicroscopy (CLE) and an endocytoscopy system (ECS), which allow in vivo microscopic inspection of the microstructural mucosal features of the gastrointestinal tract, are currently available. Studies on the use of ECS in CRC were reported by a Japanese group. Additionally, a few studies on the use of ECS in IBD have been reported. CLE has been shown to be reliable in assessing the activity of the disease in IBDs in both ulcerative colitis and Crohn’s disease. Various published studies evaluated the use of CLE during colonoscopy to distinguish colorectal polyp pathology and neoplasia. However, these studies are heterogeneous, and further evidence is necessary to confirm the efficacy of CLE.