What Is the Optimal Bowel Preparation for Capsule Colonoscopy and Pan-intestinal Capsule Endoscopy? A Systematic Review and Meta-Analysis

Panenteric capsule endoscopy in gastrointestinal bleeding - time to change old habits?

PURPOSE OF REVIEW

Capsule endoscopy (CE) is an effective tool for small bowel evaluation. Recent technical advancements, including long-lasting batteries and enhanced optics, have enabled featured capsules (panenteric capsules, PCs) to potentially assess the entire gastrointestinal (GI) tract. The PC provides a potential easy-to-use, comprehensive, single-device approach for evaluating GI bleeding patients. This review critically examines the potential role of PC in patients with GI bleeding by highlighting benefits, limitations, open issues, and future challenges.

RECENT FINDINGS

Evidence on PC for GI bleeding patients remains limited. Two retrospective studies and one recent prospective trial consistently show that when used in the workup of GI bleeding patients, PC is safe, feasible, achieves high diagnostic yield (both in the small and large bowel), and potentially reduces the need for unnecessary colonoscopies. Nevertheless, current challenges include the need for extensive bowel preparation, incomplete colon evaluation, and limited access to trained readers.

SUMMARY

The PC holds promise for optimizing the diagnostic workup of GI bleeding patients. However, significant challenges remain. Robust clinical trials comparing standard diagnostic methods to PC-based workup are needed before the adoption of PC in managing bleeding patients in clinical practice.

Quest to optimise capsule endoscopy through observational analysis

OBJECTIVES

To search for parameters susceptible to optimization when performing capsule endoscopy (CE) in a third level hospital with high volume and experience in this test.

PATIENTS AND METHODS

Retrospective observational study, including 1325 CEs performed between 2017 and 2022. Overall diagnostic yield, effective diagnostic yield, by indication, place of request and waiting list, as well as complete examination rate and cleansing degree were analyzed.

RESULTS

The overall diagnostic yield was 70.99%, while the effective diagnostic yield was 72.7%. Diagnostic yields varied between 60.2% and 77.9% depending on the indication and between 64.7% and 74.3% depending on the requesting center. The mean waiting list was 101.15 days, with a tendency to worse results when the waiting list was longer. A total of 77.8% of the examinations were complete. Completion rates were lower in patients >70 years of age (p=0.001), as well as in those with gastric transit >60minutes (p=0.000). A total of 77.3% were clean, with debris that did not impede diagnosis being found in 16.9% and debris that did impede diagnosis in 5.8%. There was a relationship, although not significant, between cleansing degree and age.

CONCLUSIONS

The diagnostic yields of CE in our center are in line with those previously reported. Differences were found according to the place of request. Waiting list could also influence diagnostic yield. Completion rates are lower in >70 years of age and when gastric transit is >60minutes. Cleansing degree achieved is acceptable.

The Application Value of an Artificial Intelligence-Driven Intestinal Image Recognition Model to Evaluate Intestinal Preparation before Colonoscopy

Aims/Background Artificial intelligence (AI), with advantages such as automatic feature extraction and high data processing capacity and being unaffected by fatigue, can accurately analyze images obtained from colonoscopy, assess the quality of bowel preparation, and reduce the subjectivity of the operating physician, which may help to achieve standardization and normalization of colonoscopy. In this study, we aimed to explore the value of using an AI-driven intestinal image recognition model to evaluate intestinal preparation before colonoscopy. Methods In this retrospective analysis, we analyzed the clinical data of 98 patients who underwent colonoscopy in Nantong First People's Hospital from May 2023 to October 2023. Among them, 47 cases were evaluated based on the intestinal preparation map and the last fecal characteristics (Regular group), and 51 cases were evaluated using an AI-driven intestinal image recognition model (AI group). The duration of colonoscopy examination, intestinal cleanliness, incidence of adverse reactions, and satisfaction with intestinal preparation of the two groups were analyzed. Results The time for colonoscopy in the AI group was shorter than that in the Regular group, and the intestinal cleanliness score in the AI group was higher than that in the Regular group (p < 0.05). The incidence of adverse reactions in the AI group (3.92%) was lower than that in the Regular group (10.64%), but the difference was not statistically significant (p > 0.05). The satisfaction rate of intestinal preparation in the AI group (96.08%) was comparable to that of the Regular group (82.98%) (p > 0.05). Conclusion Compared with the assessment based solely on the intestinal preparation map and the last fecal characteristics, the application of AI intestinal image recognition model in intestinal preparation before colonoscopy can shorten the time of colonoscopy and improve intestinal cleanliness, but with comparable patient satisfaction and safety.

Polyp Matching in Colon Capsule Endoscopy: Pioneering CCE-Colonoscopy Integration Towards an AI-Driven Future

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.

Best Approach for Incomplete Colonoscopy: Colon Capsule Endoscopy or Repeat Conventional Colonoscopy?

Background: The most appropriate strategy for completing a previous incomplete colonoscopy (IC) is not standardized. We aimed to compare the efficacy and safety of two strategies for completing a previous IC: colon capsule endoscopy (CCE) versus repeat conventional colonoscopy. Methods: A retrospective cohort study that included consecutive adult patients referred to our center after IC under sedation due to irreducible loop formation or colonic fixed angulation was performed. Patients underwent CCE (PillCam COLON2 Medtronic®) or repetition of conventional colonoscopy under sedation. In this setting, an appropriate CCE progression was defined as the capsule reaching the segment achieved during the previous IC. Repeated conventional colonoscopy was considered complete when cecal intubation was accomplished. We compared the rate of appropriate CCE colon progression with the cecal intubation rate from repeated conventional colonoscopy. Quality of colon preparation, diagnostic yield, and rate of adverse events for CCE and colonoscopy was also analyzed. Results: A total of 192 CCE and 181 colonoscopies were performed for IC, primarily due to fixed angulation of the left colon (69.2%, n = 258). There were no significant differences between the two groups (CCE vs. colonoscopy) concerning age, sex, overweight/obesity status, previous abdominal surgery, and reasons for IC. The rate of appropriate colon progression with CCE was not significantly different from the cecal intubation rate of repeated colonoscopy (95.3% vs. 90.1%, p = 0.073, respectively), even after adjusting for the quality of colon preparation (p = 0.122), which differed significantly between the groups (76.0% vs. 92.8%, p < 0.001, respectively). There were no significant differences in overall colorectal findings identified between the CCE and colonoscopy groups (55.2% vs. 62.4%, p = 0.172, respectively), and no adverse events were reported in either group. Conclusions: Our findings suggest that both CCE and repeat conventional colonoscopy are effective and safe options for completing a previous IC.

A Comprehensive Review of Artificial Intelligence and Colon Capsule Endoscopy: Opportunities and Challenges

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.

Pan-intestinal capsule endoscopy as first-line procedure in patients with suspected mid or lower gastrointestinal bleeding

BACKGROUND

Pan-intestinal capsule endoscopy (PCE) evaluates the small bowel and colon noninvasively. This study evaluated diagnostic accuracy and safety of PCE vs. colonoscopy as first-line examination in suspected mid-lower gastrointestinal bleeding (MLGIB).

METHODS

In this prospective, single-center, single-blinded cohort study, consecutive patients with suspected MLGIB underwent PCE followed by same-day colonoscopy. Diagnostic accuracy for potentially hemorrhagic lesions (PHLs; combined diagnosis by PCE + colonoscopy) and incidence of adverse events were assessed.

RESULTS

100 patients were included (median age 70 [range 18-92] years; 65% female). PHLs were diagnosed in 46 patients, including small-bowel and/or colon angioectasias in 32. PCE correctly identified 54 individuals without PHLs, and 95.7% (44/46) of those with PHLs vs. 50.0% (23/46) for colonoscopy (P<0.01). PHLs were detected by PCE alone in 65.2% (30/46), both examinations in 28.3% (13/46), and colonoscopy alone in 6.5% (3/46). PHLs were diagnosed at the ileocolonic region in 28% of patients, with PCE diagnosing 25/28 cases (89.3%) and colonoscopy diagnosing 23/28 (82.1%; P=0.13). Interventional procedures were performed at colonoscopy in 13/81 patients with iron-deficiency anemia (16.0%) vs. 6/19 patients with overt bleeding (31.6%; P<0.01). No significant adverse events occurred with PCE vs. 2% with colonoscopy.

CONCLUSIONS

In patients with MLGIB, PCE avoided further invasive procedures in >50% of patients. PCE was safe and more effective than colonoscopy in identifying PHL both in the small bowel and colon. These results support the potential use of PCE as first-line examination in patients with suspected MLGIB.

Capsule endoscopy and panendoscopy: A journey to the future of gastrointestinal endoscopy

In 2000, the small bowel capsule revolutionized the management of patients with small bowel disorders. Currently, the technological development achieved by the new models of double-headed endoscopic capsules, as miniaturized devices to evaluate the small bowel and colon [pan-intestinal capsule endoscopy (PCE)], makes this non-invasive procedure a disruptive concept for the management of patients with digestive disorders. This technology is expected to identify which patients will require conventional invasive endoscopic procedures (colonoscopy or balloon-assisted enteroscopy), based on the lesions detected by the capsule, i.e., those with an indication for biopsies or endoscopic treatment. The use of PCE in patients with inflammatory bowel diseases, namely Crohn's disease, as well as in patients with iron deficiency anaemia and/or overt gastrointestinal (GI) bleeding, after a non-diagnostic upper endoscopy (esophagogastroduodenoscopy), enables an effective, safe and comfortable way to identify patients with relevant lesions, who should undergo subsequent invasive endoscopic procedures. The recent development of magnetically controlled capsule endoscopy to evaluate the upper GI tract, is a further step towards the possibility of an entirely non-invasive assessment of all the segments of the digestive tract, from mouth-to-anus, meeting the expectations of the early developers of capsule endoscopy.