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Background: The diagnostic accuracy of colon capsule endoscopy (CCE) depends on a well-cleansed bowel. Evaluating the cleansing quality can be difficult with a substantial interobserver variation., Objectives: Our primary aim was to establish a standard of agreement for bowel cleansing in CCE based on evaluations by expert readers. Then, we aimed to investigate the interobserver agreement on bowel cleansing., Design: We conducted an interobserver agreement study on bowel cleansing quality., Methods: Readers with different experience levels in CCE and colonoscopy evaluated bowel cleansing quality on the Leighton-Rex scale and Colon Capsule CLEansing Assessment and Report (CC-CLEAR), respectively. All evaluations were reported on an image level. A total of 24 readers rated 500 images on each scale., Results: An expert opinion-based agreement standard could be set for poor and excellent cleansing but not for the spectrum in between, as the experts agreed on only a limited number of images representing fair and good cleansing. The overall interobserver agreement on the Leighton-Rex full scale was good (intraclass correlation coefficient (ICC) 0.84, 95% CI (0.82-0.85)) and remained good when stratified by experience level. On the full CC-CLEAR scale, the overall agreement was moderate (ICC 0.62, 95% CI (0.59-0.65)) and remained so when stratified by experience level., Conclusion: The interobserver agreement was good for the Leighton-Rex scale and moderate for CC-CLEAR, irrespective of the reader's experience level. It was not possible to establish an expert-opinion standard of agreement for cleansing quality in CCE images. Dedicated training in using the scales may improve agreement and enable future algorithm calibration for artificial intelligence supported cleansing evaluation., Trial Registration: All included images were derived from the CAREforCOLON 2015 trial (Registered with The Regional Health Research Ethics Committee (Registration number: S-20190100), the Danish data protection agency (Ref. 19/29858), and ClinicalTrials.gov (registration number: NCT04049357))., Competing Interests: Benedicte Schelde-Olesen has received honoraria and participated in advisory board meetings for Jinshan Ltd. Anastasios Koulaouzidis is shareholder of iCERV Ltd., has received consultancy fees and travel support from Jinshan Ltd., and has participated in advisory board meetings hosted by Dr FalkPharmaUK, Norgine, Jinshan, and ANKON. Emanuele Rondonotti has received honoraria from Fujifilm and consultancy fees from Medtronic. Xavier Dray has received lecture fees from Alfasigma, Bouchara, Recordati, Fujifilm, Medtronic, Norgine and Sandoz, has received consultancy fees from Norgine and Provepharma and is co-founder and shareholder of Augmented Endoscopy. Stefania Piccirelli has received a travel grant from AnX Robotica and honoraria from Malesci. Ulrik Deding, Ervin Toth, Konstantinos John Dabos, Abraham Eliakim, Cristina Carretero, Begoña González-Suárez, Thomas de Lange, Hanneke Beaumont, Uri Kopylov, Pierre Ellul, Enrique Pérez-Cuadrado-Robles, Alexander Robertson, Irene Stenfors, Alejandro Bojorquez, Gitte Grunnet Raabe, Reuma Margalit-Yehuda, Isabel Barba, Giulia Scardino, Salome Ouazana, Thomas Bjørsum-Meyer declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s), 2024.)

Background: Sedation increases colonoscopy risks and prolongs recovery time. We examined whether virtual reality (VR) can substitute for sedation. The primary outcome was the overall satisfaction of patients who underwent colonoscopy with VR headset compared with patients who underwent standard sedation. Pain during the procedure, polyp detection rate (PDR), colonoscopy duration, post-colonoscopy adverse events, post-colonoscopy recovery, time-to-return to daily functions, and turnaround time at the endoscopy unit were secondary outcomes., Methods: The study was approved by Sheba Medical Center's ethics committee IRB number 21-8177-SMC. Sixty patients were sequentially enrolled in a 1:1 ratio to either standard sedated colonoscopy or VR-unsedated procedure, and all patients signed a written informed consent. 28/30 patients successfully completed the colonoscopy using VR headset. Overall satisfaction score was comparable between the groups., Results: There was no difference between VR and controls in colonoscopy duration, or PDR. VR patients had numerically lower rate of post-colonoscopy adverse events than controls. The proportion of VR patients who reported resuming daily activities on the day of the procedure was significantly higher than in the control group. The VR group patients spent significantly less time in the hospital compared to the control group., Conclusions: VR technology can provide adequate substitution for sedation for most patients undergoing colonoscopy and offers comparable patient satisfaction and faster return to daily activities., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background and Aims: Small-bowel (SB) capsule endoscopy (CE) is a first-line procedure for exploring the SB. Endoscopic GI PlacemenT (EGIPT) of SB CE is sometimes necessary. Although experience with EGIPT is considerable in pediatric populations, we aimed to describe the safety, efficacy, and outcomes of EGIPT of SB CE in adult patients., Methods: The international CApsule endoscopy REsearch (iCARE) group set up a retrospective multicenter study. Patients over age 18 years who underwent EGIPT of SB CE before May 2022 were included. Data were collected from medical records and capsule recordings. The primary endpoint was the technical success rate of the EGIPT procedures., Results: Of 39,565 patients from 29 centers, 630 (1.6%) were included (mean age, 62.5 years; 55.9% women). The technical success of EGIPT was achieved in 610 procedures (96.8%). Anesthesia (moderate to deep sedation or general anesthesia) and centers with intermediate or high procedure loads were independent factors of technical success. Severe adverse events occurred in 3 patients (.5%). When technically successful, EGIPT was associated with a high SB CE completion rate (84.4%) and with a substantial diagnostic yield (61.1%). The completion rate was significantly higher when the capsule was delivered in the SB compared with when it was delivered in the stomach., Conclusions: EGIPT of SB CE is highly feasible and safe, with a high completion rate and diagnostic yield. When indicated, it should be performed with patients under anesthesia, and the capsule should be delivered in the duodenum rather than the stomach for better SB examination outcomes., Competing Interests: Disclosure The following authors disclosed financial relationships: S. Ouazana: Speaker for Medtronic. P. Baltes: Speaker for Medtronic; research support from AnX Robotics. E. Toth: Consultant for AnX Robotics, Jinshan, Medtronic, and Norgine; speaker for Jinshan, Medtronic, and Tillotts Pharma; research support from AnX Robotics, Jinshan, and Norgine. H. Beaumont: Speaker for Medtronic. C. Spada: Advisor for AnX Robotics and Medtronic; speaker for AnX Robotics, Boston Scientific, and Olympus; research support from Pentax. A. Mussetto: Consultant for Boston Europe and Olympus Italia. R. Sidhu: Consultant for AnXRobotics. D. McNamara: Speaker for Medtronic and Takeda. B. González-Suárez: Research support from Medtronic; speaker for Norgine and Olympus. C. Carretero: Advisor for Medtronic. E. Despott: Research support from Fujifilm, Aquilant Endoscopy, Pentax Medical, Olympus, Boston Scientific, GI Supply, Cook Medical, Diagmed Healthcare, Norgine, Takeda, Abbvie, Cantel Medical, Ardmore Medical, Apollo Endosurgery, Erbe, APR Medical, AnX Robotics, and Medtronic; consultant for Fujifilm, Norgine, and Ambu; speaker for Fujifilm, Aquilant Endoscopy, Olympus, Boston Scientific, GI Supply, Ambu, and Aquilant Endoscopy. E. Rondonotti: Speaker and consultant for Fujifilm; consultant for Medtronic. J. Kirchgesner: Consultant for Janssen, Celltrion, Roche, Pfizer, and Gilead; speaker for Janssen and Lilly. X. Dray: Speaker for Alfasigma, Bouchara Recordati, Fujifilm, Medtronic, Norgine, and Sandoz; co-founder of and shareholder in Augmented Endoscopy; consultant for Norgine and Provepharma. All other authors disclosed no financial relationships., (Copyright © 2024 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

Fecal incontinence (FI) is often underreported and underestimated in men. Our aims were to clarify the causes and the physiological characteristics of FI in men and to underline the differences between etiological and physiological factors in men and women diagnosed with FI. The study cohort encompassed 200 men and 200 women who underwent anatomical and physiological evaluation for FI in a tertiary referral center specializing in pelvic floor disorders. All patients underwent endoanal ultrasound and anorectal manometry. Evacuation proctography was performed in some patients. Demographic, medical, anatomical, and physiological parameters were compared between the two study groups. Urge incontinence was the most frequent type of FI in both genders. In men, anal fistula, history of anal surgeries, rectal tumors, and pelvic radiotherapy were common etiologic factors, whereas history of pelvic surgeries was more common in women. Associated urinary incontinence was reported more frequently by women. External anal sphincter defects, usually anterior, were more common in women (M: 1.5%, F: 24%, P < 0.0001), whereas internal anal sphincter defect prevalence was similar in men and women (M: 6%, F: 12%, P = 0.19). Decreased resting and squeeze pressures were less common in men (M: 29%, F: 46%, P < 0.0001: M: 44%, F: 66%, P < 0.0001). The incidence of rectal hyposensitivity was higher in men (M: 11.1%, F: 2.8%, P < 0.0001), whereas rectal hypersensitivity was higher in women (M: 5.8%, F: 10.8%, P < 0.0001). Anorectal dyssynergia was more common in men (M: 66%, F: 37%, P < 0.0001). Significantly different etiological factors and physiological characteristics for FI were found in men. Acknowledging these differences is significant and may yield better treatment options. NEW & NOTEWORTHY Fecal incontinence (FI) in men has different etiological factors when compared with women. The prevalence of internal anal sphincter defect among men with FI was similar to women. Different manometric measurements were found among men with FI: decreased anal pressures were less common among men, whereas rectal hyposensitivity and anorectal dyssynergia were more common among men.

Introduction: The investigation of small bowel (SB) intussusception is variable, reflecting the lack of existing standards. The aim of this study was to understand the role of small bowel capsule endoscopy (SBCE) to investigate this pathology., Methodology: This was a retrospective multi-centre study. Patients with intussusception on SBCE and those where SBCE was carried out due to findings of intussusception on radiological investigations were included. Relevant information was collected., Results: Ninety-five patients (median age 39+/-SD19.1 years, IQR 30) were included. Radiological investigations were carried out in 71 patients (74.7%) prior to SBCE with intussusception being present in 60 patients on radiological investigations (84.5%). Thirty patients (42.2%) had intussusception on radiological investigations followed by a normal SBCE. Ten patients (14.1%) had findings of intussusception on radiological investigations, a normal SBCE and repeat radiological investigations that were also normal. Abnormal findings were noted on SBCE that could explain intussusception on imaging in (16 patients) 22.5% of patients. Five patients (5.3%) underwent radiological investigations and SBCE to investigate coeliac disease and intussusception. None had associated malignancy. Four patients (4.2%) underwent SBCE to investigate familial polyposis syndromes and went on to SB enteroscopy and surgery accordingly. Most patients (n = 14; 14.8%) with intussusception on initial SBCE (without prior radiological imaging) had suspected SB bleeding (n = 10, 10.5%). Four patients (4.2%) had additional findings of a mass on CT scan and went on to have surgery., Conclusion: SBCE should be used to complement radiology when investigating intussusception. It is a safe non-invasive test that will minimise unnecessary surgery. Additional radiological investigations following a negative SBCE in cases of intussusception noted on initial radiological investigations are unlikely to yield positive findings. Radiological investigations following intussusception noted on SBCE in case of patients presenting with obscure gastrointestinal bleeding, may yield additional findings., Competing Interests: Conflict of interest None., (Copyright © 2023 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.)

Background: Deep learning techniques can accurately detect and grade inflammatory findings on images from capsule endoscopy (CE) in Crohn's disease (CD). However, the predictive utility of deep learning of CE in CD for disease outcomes has not been examined., Objectives: We aimed to develop a deep learning model that can predict the need for biological therapy based on complete CE videos of newly-diagnosed CD patients., Design: This was a retrospective cohort study. The study cohort included treatment-naïve CD patients that have performed CE (SB3, Medtronic) within 6 months of diagnosis. Complete small bowel videos were extracted using the RAPID Reader software., Methods: CE videos were scored using the Lewis score (LS). Clinical, endoscopic, and laboratory data were extracted from electronic medical records. Machine learning analysis was performed using the TimeSformer computer vision algorithm developed to capture spatiotemporal characteristics for video analysis., Results: The patient cohort included 101 patients. The median duration of follow-up was 902 (354-1626) days. Biological therapy was initiated by 37 (36.6%) out of 101 patients. TimeSformer algorithm achieved training and testing accuracy of 82% and 81%, respectively, with an Area under the ROC Curve (AUC) of 0.86 to predict the need for biological therapy. In comparison, the AUC for LS was 0.70 and for fecal calprotectin 0.74., Conclusion: Spatiotemporal analysis of complete CE videos of newly-diagnosed CD patients achieved accurate prediction of the need for biological therapy. The accuracy was superior to that of the human reader index or fecal calprotectin. Following future validation studies, this approach will allow for fast and accurate personalization of treatment decisions in CD., Competing Interests: UK: research support – Medtronic, Janssen, Takeda. Speaker/advisory fees – AbbVie, BMS, Janssen, Pfizer, Takeda, MSD, Rafa. RE: Speaker for Takeda, Janssen, and Medtronic. SBH: received consulting and advisory board fees and/or research support from AbbVie, MSD, Janssen, Takeda, Pfizer, GSK, and CellTrion. EK, SheS, RMY, OB, and EZ: no competing interests. RK, AB, EA, and ShiS: employees of Intel Inc., (© The Author(s), 2023.)

Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with the incorporation of AI in endoscopy are being addressed in recent consensus documents., Objectives: In the current paper, we aimed to map future challenges and areas of research for the incorporation of AI in capsule endoscopy (CE) practice., Design: Modified three-round Delphi consensus online survey., Methods: The study design was based on a modified three-round Delphi consensus online survey distributed to a group of CE and AI experts. Round one aimed to map out key research statements and challenges for the implementation of AI in CE. All queries addressing the same questions were merged into a single issue. The second round aimed to rank all generated questions during round one and to identify the top-ranked statements with the highest total score. Finally, the third round aimed to redistribute and rescore the top-ranked statements., Results: Twenty-one (16 gastroenterologists and 5 data scientists) experts participated in the survey. In the first round, 48 statements divided into seven themes were generated. After scoring all statements and rescoring the top 12, the question of AI use for identification and grading of small bowel pathologies was scored the highest (mean score 9.15), correlation of AI and human expert reading-second (9.05), and real-life feasibility-third (9.0)., Conclusion: In summary, our current study points out a roadmap for future challenges and research areas on our way to fully incorporating AI in CE reading., Competing Interests: Uri Kopylov: research support – Medtronic, Jannsen, Takeda. Speaker/advisory fees – Abbvie, BMS, Jannsen, Pfizer, Takeda, MSD, Rafa. Xavier Dray, Romain Leenhardt, and Aymeric Histace are cofounders and shareholders of Augmented Endoscopy. Xavier Dray has acted as a consultant for Boston Scientific and Norgine and has given lectures for Fujifilm, Medtronic, MSD, and Pentax. Romain Leenhardt has given a lecture for Abbvie. Martin Keuchel has acted as a consultant for Medtronic and has given lectures for Medtronic and received study support from AnXRobotic’s and Olympus. Arnaud Bourreille received honoraria or grant research from Abbvie, Celgene, Galapagos, Gilead, Mauna Kea Technologies, Medtronic, MSD, Hoffman la Roche, Ferring, Janssen, MSD, Pfizer, Takeda, Tillotts, and OSE immunotherapeutics. Pia Smedsrud employed and shareholder in Augere Medical a start-up company for AI in endoscopy. Medical Augere of shareholder and cofounder is Lange de Thomas. Rami Eliakim has received research support and consultant fee from Medtronic, consultant fee from jannsen and Takeda, (© The Author(s), 2022.)

Background and Aims: The aim of our study was to create an accurate patient-level combined algorithm for the identification of ulcers on CE images from two different capsules., Methods: We retrospectively collected CE images from PillCam-SB3's capsule and PillCam-Crohn's capsule. ML algorithms were trained to classify small bowel CE images into either normal or ulcerated mucosa: a separate model for each capsule type, a cross-domain model (training the model on one capsule type and testing on the other), and a combined model., Results: The dataset included 33,100 CE images: 20,621 PillCam-SB3 images and 12,479 PillCam-Crohn's images, of which 3582 were colonic images. There were 15,684 normal mucosa images and 17,416 ulcerated mucosa images. While the separate model for each capsule type achieved excellent accuracy (average AUC 0.95 and 0.98, respectively), the cross-domain model achieved a wide range of accuracies (0.569-0.88) with an AUC of 0.93. The combined model achieved the best results with an average AUC of 0.99 and average mean patient accuracy of 0.974., Conclusions: A combined model for two different capsules provided high and consistent diagnostic accuracy. Creating a holistic AI model for automated capsule reading is an essential part of the refinement required in ML models on the way to adapting them to clinical practice.

Aims: The primary aim of this study was to assess the reliability, intra- and inter-observer variation of the SPICE, Mucosal protrusion angle (MPA) and SHYUNG scores in differentiating a subepithelial mass (SEM) from a bulge., Methods: This retrospective multicentre study analysed the 3 scores, radiological studies, enteroscopy and/or surgical findings., Results: 100 patients with a potential SEM (mean age 57.6years) were recruited with 75 patients having pathology. In patients with a SEM the mean SPICE score was 2.04 (95% CI 1.82-2.26) as compared to 1.16 (95% CI 0.81-1.51) without any pathology (AUC 0.74, p<0.001), with a fair intra-observer agreement (Kappa 0.3, p<0.001) and slight inter-observer agreement (Kappa 0.14, p<0.05). SPICE had a 37.3% sensitivity and 92.0% specificity in distinguishing between a SEM and bulge, whereas MPA<90˚ had 58.7% and 76.0% respectively, with poor intra-observer(p = 0.05) and interobserver agreement (p = 0.64). The SHYUNG demonstrated a moderate intra-observer (Kappa 0.44, p<0.001) and slight inter-observer reliability (Kappa 0.18, p<0.001). The sensitivity of an elevated SHYUNG score (≥4) in identifying a SEM was 18.7% with a specificity of 92.0% (AUC 0.71, p = 0.002)., Conclusions: Though these scores are easy to use, they have, at best, slight to moderate intra and inter-observer agreement. Their overall diagnostic performances are limited., Competing Interests: Conflict of interest None declared., (Copyright © 2022. Published by Elsevier Ltd.)

Competing Interests: Competing interests The authors declare that they have no conflict of interest.

Background and Aims: Passable intestinal strictures are frequently detected on capsule endoscopy [CE]. Such strictures are a major component of inflammatory scores. Deep neural network technology for CE is emerging. However, the ability of deep neural networks to identify intestinal strictures on CE images of Crohn's disease [CD] patients has not yet been evaluated., Methods: We tested a state-of-the-art deep learning network for detecting CE images of strictures. Images of normal mucosa, mucosal ulcers, and strictures of Crohn's disease patients were retrieved from our previously described CE image bank. Ulcers were classified as per degree of severity. We performed 10 cross-validation experiments. A clear patient-level separation was maintained between training and testing sets., Results: Overall, the entire dataset included 27 892 CE images: 1942 stricture images, 14 266 normal mucosa images, and 11 684 ulcer images [mild: 7075, moderate: 2386, severe: 2223]. For classifying strictures versus non-strictures, the network exhibited an average accuracy of 93.5% [±6.7%]. The network achieved excellent differentiation between strictures and normal mucosa (area under the curve [AUC] 0.989), strictures and all ulcers [AUC 0.942], and between strictures and different grades of ulcers [for mild, moderate, and severe ulcers-AUCs 0.992, 0.975, and 0.889, respectively]., Conclusions: Deep neural networks are highly accurate in the detection of strictures on CE images in Crohn's disease. The network can accurately separate strictures from ulcers across the severity range. The current accuracy for the detection of ulcers and strictures by deep neural networks may allow for automated detection and grading of Crohn's disease-related findings on CE., (© The Author(s) 2020. Published by Oxford University Press on behalf of European Crohn’s and Colitis Organisation. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Takayasu's arteritis (TA) and inflammatory bowel disease (IBD) are chronic inflammatory granulomatous disorders that have rarely been concomitantly reported in case reports and small case series., Objective: We report a series of seven cases of TA and IBD association in two referral centers with a comprehensive review of literature., Methods: We analyzed retrospectively the electronic medical charts of TA-IBD patients at the University Hospital of São Paulo, Brazil, and at the Sheba Medical Center at Tel Aviv University, Israel., Results: Overall, five patients had Crohn's disease (DC) and two had ulcerative colitis (UC), and they were mostly female and non-Asian. All patients developed IBD first and, subsequently, TA. Two underwent colectomy and one ileocecectomy due to IBD activity, while three required cardiovascular surgery due to TA activity. Most patients are currently in clinical remission of both diseases with conventional drug treatment., Conclusion: Although the coexistence of TA and IBD is uncommon, both seem to be strongly associated through pathophysiological pathways., Competing Interests: The authors declare that they have no conflict of interest., (Copyright © 2021 Camilla de Almeida Martins et al.)

Background and Aims: Capsule endoscopy (CE) is an important modality for diagnosis and follow-up of Crohn's disease (CD). The severity of ulcers at endoscopy is significant for predicting the course of CD. Deep learning has been proven accurate in detecting ulcers on CE. However, endoscopic classification of ulcers by deep learning has not been attempted. The aim of our study was to develop a deep learning algorithm for automated grading of CD ulcers on CE., Methods: We retrospectively collected CE images of CD ulcers from our CE database. In experiment 1, the severity of each ulcer was graded by 2 capsule readers based on the PillCam CD classification (grades 1-3 from mild to severe), and the inter-reader variability was evaluated. In experiment 2, a consensus reading by 3 capsule readers was used to train an ordinal convolutional neural network (CNN) to automatically grade images of ulcers, and the resulting algorithm was tested against the consensus reading. A pretraining stage included training the network on images of normal mucosa and ulcerated mucosa., Results: Overall, our dataset included 17,640 CE images from 49 patients; 7391 images with mucosal ulcers and 10,249 normal images. A total of 2598 randomly selected pathologic images were further graded from 1 to 3 according to ulcer severity in the 2 different experiments. In experiment 1, overall inter-reader agreement occurred for 31% of the images (345 of 1108) and 76% (752 of 989) for distinction of grades 1 and 3. In experiment 2, the algorithm was trained on 1242 images. It achieved an overall agreement for consensus reading of 67% (166 of 248) and 91% (158 of 173) for distinction of grades 1 and 3. The classification accuracy of the algorithm was 0.91 (95% confidence interval, 0.867-0.954) for grade 1 versus grade 3 ulcers, 0.78 (95% confidence interval, 0.716-0.844) for grade 2 versus grade 3, and 0.624 (95% confidence interval, 0.547-0.701) for grade 1 versus grade 2., Conclusions: CNN achieved high accuracy in detecting severe CD ulcerations. CNN-assisted CE readings in patients with CD can potentially facilitate and improve diagnosis and monitoring in these patients., (Copyright © 2021 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.)

We report a 27-year-old traveler who returned from Nepal suffering from typhoid fever. His disease was complicated by life-threatening myocarditis and ventricular fibrillation, a rare manifestation in travelers., (© 2013 International Society of Travel Medicine.)