Search Results (17)

Background: Colon capsule endoscopy (CCE) or panenteric capsule endoscopy (PCE) offers a promising, non-invasive diagnostic approach for patients with iron deficiency anaemia (IDA). However, high rates of conversion to conventional colonoscopy (CCC) following capsule procedures reduce cost-effectiveness and patient satisfaction. Optimising the faecal immunochemical test (FIT) threshold may improve patient stratification and reduce unnecessary conversions in future applications within the IDA diagnostic pathway. Methods: The CLEAR IDA study was a multicentre, retrospective observational study conducted across four UK hospitals. Data were collected over a six-month study period and included patients referred via the two-week-wait (2WW) cancer pathway for iron deficiency, with or without anaemia, over a 12-month timeframe. Colonoscopy findings were analysed and extrapolated using NHS England’s CCE-to-colonoscopy referral criteria to assess the predictive value of FIT for colorectal cancer (CRC), polyp burden, and CCC using ROC curve analysis. The optimal FIT threshold was identified through three complementary approaches: threshold-based analysis, decision curve analysis, and cost–benefit modelling. Results: A total of 1531 patients were analysed; only 1.6% underwent small bowel capsule endoscopy. The diagnostic accuracy (AUC) of FIT for predicting CRC, polypoidal lesions, and CCC was 0.78, 0.58, and 0.69, respectively. Threshold-based analysis identified FIT = 15 µg/g as the lowest level at which CCC rates significantly increased (p = 0.02; OR = 1.87; 95% CI: 1.07–3.14). Decision curve analysis showed a maximum net benefit at FIT = 17.6 µg/g, while cost–benefit modelling identified 9 µg/g as the most cost-effective. Raising the threshold to 10 µg/g resulted in a net loss of GBP –294.4 per patient. An optimal cost-effective FIT threshold range was identified between 10 and 17.6 µg/g. The threshold selection should be tailored to local service capacity and resource availability. Conclusions: While FIT alone is an imperfect triage tool, optimising thresholds between 10 and 17 µg/g may enhance cost-effectiveness and guide appropriate PCE use in IDA. Full article

The fifth annual REFLECT (The futuRE oF MinimalLy InvasivE GI and Capsule diagnosTics) symposium, held in October 2024 in Nyborg, Denmark, focused on advancements in minimally invasive gastrointestinal (GI) diagnostics, particularly capsule endoscopy (CE) technologies. Key discussions included clinical updates, innovations in hardware and software, and the growing role of colon CE (CCE) in colorectal cancer screening. The event provided a platform for clinicians, engineers, industry representatives, and scientists to exchange knowledge and present the latest advancements in the field. Discussions covered clinical studies, future research protocols, and technological innovations, with also a notable focus on commercial solutions and expansion of the implementation of capsule endoscopy. The symposium also highlighted the significance of predictive models for patient selection and developments in panenteric CE. Innovative technologies presented included robotics for drug delivery and magnetic endoscopic guidance systems. AI advancements were discussed for their potential to reduce diagnostic fatigue and standardize image interpretation, but ethical concerns and the need for transparent algorithms remain. The importance of multidisciplinary collaboration was emphasized to bridge innovation and clinical practice. Home-based CCE delivery emerged as a promising model, despite mixed results from environmental impact assessments. Overall, REFLECT 2024 reinforced the clinical utility and challenges of capsule-based diagnostics, advocating for ongoing interdisciplinary research to support safe and effective integration into healthcare systems. Full article

Background/Objectives: Colon capsule endoscopy (CCE) is a non-invasive method for visualising the colon, but its clinical adoption has been slow. Although the COVID-19 pandemic reignited interest in CCE, its role in conventional gastrointestinal investigations remains unclear, leading to varied practices across Europe. This highlights the need for a comprehensive understanding of diverse approaches to CCE in clinical practice. Method: A web-based survey was conducted from January to July 2024, targeting European gastroenterologists and colorectal surgeons interested in capsule endoscopy through the International Capsule Endoscopy Research (iCARE) Group. The survey aimed to understand CCE application across Europe and investigate factors influencing its uptake. Results: Thirty-eight (n = 38) valid responses were received from 19 European countries. While 88% reported access to CCE, only 45% had local services readily available, and just 7% included CCE in national guidelines. The most common indication for CCE was for patients who declined or could not tolerate colonoscopy (30%), with 77% of CE specialists preferring its use in fit patients. Ease of access was significantly associated with service availability (p = 0.0358). Barriers to uptake included lack of reimbursement, insufficient knowledge, and limited use in research settings. Only 27% of specialists viewed CCE positively, while 57% had a negative perception. Conclusions: This study reveals the wide variation in CCE practices and critical factors influencing its uptake. Understanding common indications and patient groups is the key to guiding its future development, particularly as AI and telemedicine enhance its potential for rapid full digestive tract visualisation. Full article

Background: Colon capsule endoscopy (CCE) is becoming more widely available across Europe, but its uptake is slow due to the need for follow-up colonoscopy for therapeutic procedures and biopsies, which impacts its cost-effectiveness. One of the major factors driving the conversion to colonoscopy is the detection of excess polyps in CCE that cannot be matched during subsequent colonoscopy. The capsule’s rocking motion, which can lead to duplicate reporting of the same polyp when viewed from different angles, is likely a key contributor. Objectives: This review aims to explore the types of polyp matching reported in the literature, assess matching techniques and matching accuracy, and evaluate the development of machine learning models to improve polyp matching in CCE and subsequent colonoscopy. Methods: A systematic literature search was conducted in EMBASE, MEDLINE, and PubMed. Due to the scarcity of research in this area, the search encompassed clinical trials, observational studies, reviews, case series, and editorial letters. Three directly related studies were included, and ten indirectly related studies were included for review. Results: Polyp matching in colon capsule endoscopy still needs to be developed, with only one study focused on creating criteria to match polyps within the same CCE video. Another study established that experienced CCE readers have greater accuracy, reducing interobserver variability. A machine learning algorithm was developed in one study to match polyps between initial CCE and subsequent colonoscopy. Only around 50% of polyps were successfully matched, requiring further optimisation. As Artificial Intelligence (AI) algorithms advance in CCE polyp detection, the risk of duplicate reporting may increase when clinicians are presented with polyp images or timestamps, potentially complicating the transition to AI-assisted CCE reading in the future. Conclusions: Polyp matching in CCE is a developing field with considerable challenges, especially in matching polyps within the same video. Although AI shows potential for decent accuracy, more research is needed to refine these techniques and make CCE a more reliable, non-invasive alternative to complement conventional colonoscopy for lower GI investigations. Full article

Colon capsule endoscopy (CCE) enables a comprehensive, non-invasive, and painless evaluation of the colon, although it still has limited indications. The lengthy reading times hinder its wider implementation, a drawback that could potentially be overcome through the integration of artificial intelligence (AI) models. Studies employing AI, particularly convolutional neural networks (CNNs), demonstrate great promise in using CCE as a viable option for detecting certain diseases and alterations in the colon, compared to other methods like colonoscopy. Additionally, employing AI models in CCE could pave the way for a minimally invasive panenteric or even panendoscopic solution. This review aims to provide a comprehensive summary of the current state-of-the-art of AI in CCE while also addressing the challenges, both technical and ethical, associated with broadening indications for AI-powered CCE. Additionally, it also gives a brief reflection of the potential environmental advantages of using this method compared to alternative ones. Full article

Colon capsule endoscopy (CCE) has regained popularity for lower gastrointestinal investigations since the COVID-19 pandemic. While there have been systematic reviews and meta-analyses on colonic polyp detection using CCE, there is a lack of comprehensive evidence concerning colonic inflammation. Therefore, this systematic review and meta-analysis aimed to assess the diagnostic accuracy of CCE for colonic inflammation, predominantly ulcerative colitis (UC) and Crohn’s disease (CD). Methods: We systematically searched electronic databases (EMBASE, MEDLINE, PubMed Central, and Cochrane Library) for studies comparing the diagnostic accuracy between CCE and optical endoscopy as the standard reference. A bivariate random effect model was used for the meta-analysis. Results: From 3797 publications, 23 studies involving 1353 patients were included. Nine studies focused on UC, and ten focused on CD. For UC, CCE showed a pooled sensitivity of 92% (95% CI, 88–95%), a specificity of 71% (95% CI, 35–92%), and an AUC of 0.93 (95% CI, 0.89–0.97). For CD, the pooled sensitivity was 92% (95% CI, 89–95%), and the specificity was 88% (95% CI, 84–92%), with an AUC of 0.87 (95% CI, 0.76–0.98). Overall, for inflammatory bowel disease, the pooled sensitivity, specificity, and AUC were 90% (95% CI, 85–93%), 76% (95% CI, 56–90%), and 0.92 (95% CI, 0.94–0.97), respectively. Conclusions: Despite the challenges around standardised disease scoring and the lack of histological confirmation, CCE performs well in diagnosing inflammatory bowel disease. It demonstrates high sensitivity in both UC and Crohn’s terminal ileitis and colitis and high specificity in Crohn’s disease. Further studies are needed to evaluate the diagnostic accuracy of other colonic inflammatory conditions. Full article

Lower gastrointestinal endoscopy is considered the gold standard for the diagnosis and removal of colonic polyps. Delays in colonoscopy following a positive fecal immunochemical test increase the likelihood of advanced adenomas and colorectal cancer (CRC) occurrence. However, patients may refuse to undergo conventional colonoscopy (CC) due to fear of possible risks and pain or discomfort. In this regard, patients undergoing CC frequently require sedation to better tolerate the procedure, increasing the risk of deep sedation or other complications related to sedation. Accordingly, the use of CC as a first-line screening strategy for CRC is hampered by patients’ reluctance due to its invasiveness and anxiety about possible discomfort. To overcome the limitations of CC and improve patients’ compliance, several studies have investigated the use of robotic colonoscopy (RC) both in experimental models and in vivo. Self-propelling robotic colonoscopes have proven to be promising thanks to their peculiar dexterity and adaptability to the shape of the lower gastrointestinal tract, allowing a virtually painless examination of the colon. In some instances, when alternatives to CC and RC are required, barium enema (BE), computed tomographic colonography (CTC), and colon capsule endoscopy (CCE) may be options. However, BE and CTC are limited by the need for subsequent investigations whenever suspicious lesions are found. In this narrative review, we discussed the current clinical applications of RC, CTC, and CCE, as well as the advantages and disadvantages of different endoscopic procedures, with a particular focus on RC. Full article

Artificial intelligence (AI) applications have become widely popular across the healthcare ecosystem. Colon capsule endoscopy (CCE) was adopted in the NHS England pilot project following the recent COVID pandemic’s impact. It demonstrated its capability to relieve the national backlog in endoscopy. As a result, AI-assisted colon capsule video analysis has become gastroenterology’s most active research area. However, with rapid AI advances, mastering these complex machine learning concepts remains challenging for healthcare professionals. This forms a barrier for clinicians to take on this new technology and embrace the new era of big data. This paper aims to bridge the knowledge gap between the current CCE system and the future, fully integrated AI system. The primary focus is on simplifying the technical terms and concepts in machine learning. This will hopefully address the general “fear of the unknown in AI” by helping healthcare professionals understand the basic principle of machine learning in capsule endoscopy and apply this knowledge in their future interactions and adaptation to AI technology. It also summarises the evidence of AI in CCE and its impact on diagnostic pathways. Finally, it discusses the unintended consequences of using AI, ethical challenges, potential flaws, and bias within clinical settings. Full article

Background: CCE is a diagnostic tool lacking clinical data on false negative rates. We aimed to assess this rate and the reader/technical error breakdown. Methods: False negative CCEs were identified after comparing to a colonoscopy database. Missed pathology characteristics and study indications/quality were collated. Cases were re-read by experts and newly identified lesions/pathologies were verified by an expert panel and categorised as reader/technical errors. Results: Of 532 CCEs, 203 had an adequately reported comparative colonoscopy, 45 (22.2%) had missed polyps, and 26/45 (57.8%) reached the colonic section with missed pathology. Of the cases, 22 (84.6%) had adequate bowel preparation. Indications included 13 (50%) polyp surveillance, 12 (46%) GI symptoms, 1 (4%) polyp screening. CCE missed 18 (69.2%) diminutive polyps and 8 (30.8%) polyps ≥ 6 mm, 18/26 (69.2%) of these were adenomas. Excluding incomplete CCE correlates, colonoscopy total and significant polyp yield were 97/184 (52.7%) and 50/97 (51.5%), respectively. CCE total polyp and significant polyp false negative rate was 26.8% (26/97) and 16% (8/50), respectively. Following re-reading, reader and technical error was 20/26 (76.9%) and 6/26 (23.1%). Total and significant missed polyp rates were 20.6% (20/97) and 14% (7/50) for reader error, 6.2% (6/97) and 2% (1/50) for technical error. Conclusions: False negative CCE rate is not insubstantial and should be factored into clinical decision making. Full article

Colon capsule endoscopy (CCE) is a promising modality for colonic investigations, but completion rates (CR) and adequate cleansing rates (ACR) must be improved to meet established standards for optical colonoscopy. Improvements should be made with patient acceptability in mind. We aimed to compare a very low-volume polyethylene glycol (PEG) laxative to a conventional high-volume laxative. We carried out a single-center retrospective comparative cohort study including patients referred for CCE. One hundred and sixty-six patients were included in the final analysis, with eighty-three patients in each group. We found a CR and ACR of 77% and 67% in the high-volume group and 72% and 75% in the very low-volume group, respectively. In the high-volume group, 54% had complete transit and adequate cleansing, whereas this was the case for 63% in the very low-volume group. No statistically significant difference in CR, ACR, or a combination of the two was found. A very low-volume bowel preparation regimen was non-inferior to a high-volume regimen before CCE in terms of CR and ACR. Full article

Completing colon capsule endoscopy (CCE) investigations rely on successful transit and acceptable bowel preparation quality. We investigated the effect of adding castor oil to the CCE bowel preparation regimen on the completion rate using a meta-analysis of existing literature. We conducted a systematic literature search in PubMed, Web of Science, and Embase. Included studies underwent quality assessment, and data for meta-analysis were extracted. Pooled estimates for excretion rate and acceptable bowel preparation rate were calculated. We identified 72 studies matching our search criteria, and six were included in the meta-analysis. Three of the studies had control groups, although two used historical cohorts. The pooled excretion rate (92%) was significantly higher in patients who received castor oil than in those who did not (73%). No significant difference in acceptable colonic cleanliness was observed. Castor oil has been used in a few studies as a booster for CCE. This meta-analysis shows the potential for this medication to improve excretion rates, and castor oil could be actively considered in conjunction with other emerging laxative regimens in CCE. Still, prospective randomized trials with appropriate control groups should be conducted before any conclusions can be drawn. Prospero ID: CRD42022338939. Full article

Background: Colon capsule endoscopy (CCE) is an alternative for patients unwilling or with contraindications for conventional colonoscopy. Colorectal cancer screening may benefit greatly from widespread acceptance of a non-invasive tool such as CCE. However, reviewing CCE exams is a time-consuming process, with risk of overlooking important lesions. We aimed to develop an artificial intelligence (AI) algorithm using a convolutional neural network (CNN) architecture for automatic detection of colonic protruding lesions in CCE images. An anonymized database of CCE images collected from a total of 124 patients was used. This database included images of patients with colonic protruding lesions or patients with normal colonic mucosa or with other pathologic findings. A total of 5715 images were extracted for CNN development. Two image datasets were created and used for training and validation of the CNN. The AUROC for detection of protruding lesions was 0.99. The sensitivity, specificity, PPV and NPV were 90.0%, 99.1%, 98.6% and 93.2%, respectively. The overall accuracy of the network was 95.3%. The developed deep learning algorithm accurately detected protruding lesions in CCE images. The introduction of AI technology to CCE may increase its diagnostic accuracy and acceptance for screening of colorectal neoplasia. Full article

Capsule endoscopy (CE) has proven to be a valuable diagnostic modality for small bowel diseases over the past 20 years, particularly Crohn’s disease (CD), which can affect the entire gastrointestinal tract from the mouth to the anus. CE is not only used for the diagnosis of patients with suspected small bowel CD, but can also be used to assess disease activity, treat-to-target, and postoperative recurrence in patients with established small bowel CD. As CE can detect even mildly non-specific small bowel lesions, a high diagnostic yield is not necessarily indicative of high diagnostic accuracy. Moreover, the cost effectiveness of CE as a third diagnostic test employed usually after ileocolonoscopy and MR or CT enterography is an important consideration. Recently, new developments in colon capsule endoscopy (CCE) have increased the utility of CE in patients with ulcerative colitis (UC) and pan-enteric CD. Although deflation of the colon during the examination and the inability to evaluate dysplasia-associated lesion or mass results in an inherent risk of overestimation or underestimation, the convenience of CCE examination and the risk of flare-up after colonoscopy suggest that CCE could be used more actively in patients with UC. Full article

Observing the entire small bowel is difficult due to the presence of complex loops and a long length. Capsule endoscopy (CE) provides a noninvasive and patient-friendly method for visualizing the small bowel and colon. Small bowel capsule endoscopy (SBCE) has a critical role in the diagnosis of small bowel disorders through the direct observation of the entire small bowel mucosa and is becoming the primary diagnostic tool for small bowel diseases. Recently, colon capsule endoscopy (CCE) was also considered safe and feasible for obtaining sufficient colonic images in patients with incomplete colonoscopy, in the absence of bowel obstruction. This review article assesses the current status of CE in terms of the diagnostic yield and the clinical impact of SBCE in patients with obscure gastrointestinal bleeding, who have known or suspected Crohn’s disease, small bowel tumor and inherited polyposis syndrome, celiac disease, and those who have undergone CCE. Full article

In the constantly developing era of minimal diagnostic invasiveness, the role of colon capsule endoscopy in colonic examination is being increasingly recognised, especially in the context of curtailed endoscopy services due to the COVID-19 pandemic. It is a safe diagnostic tool with low adverse event rates. As with other endoscopic modalities, various colon capsule endoscopy scores allow the standardisation of reporting and reproducibility. As bowel cleanliness affects CCE’s diagnostic yield, a few operator-dependent scores (Leighton–Rex and CC-CLEAR scores) and a computer-dependent score (CAC score) have been developed to grade bowel cleanliness objectively. CCE can be used to monitor IBD mucosal disease activity through the UCEIS and the panenteric CECDAIic score for UC and CD, respectively. CCE may also have a role in CRC screening, given similar sensitivity and specificity rates to conventional colonoscopy to detect colonic polyps ≥ 10 mm and CRC. Given CCE’s diagnostic yield and reproducible clinical scores with high inter-observer agreements, CCE is fast becoming a suitable alternative to conventional colonoscopy in specific patient populations. Full article