Introduction

To conduct a back-to-back endoscopy study and to evaluate the contribution of endocuff assisted colonoscopy to the detection of missed adenomas in a mixed population of colorectal cancer (CRC) screening/surveillance and symptomatic patients. To the best of our knowledge, this is the first study on this issue.

Aims & Methods

It is a prospective study conducted from March 2021 to March 2022 in a tertiary endoscopy department. Two consecutive same day, endocuff assisted, colonoscopies were performed in 124 patients.
ClinicalTrials.gov Identifier: NCT04805567.

Results

124 patients were enrolled (58.9% male/ median age 62 years). All examinations were complete (100% cecum intubation, 54% ileal intubation). The indications were CRC screening (77 patients, 62.1%), post-polypectomy surveillance (24 patients, 19.4%) and diagnostic assessment (23 patients, 18.5%). 54.8% of the patients had diverticulosis. 368 polyps were overall found and removed. 321 in the first and 48 in the second examination. Only 4 patients with no adenoma found in the first examination had one adenoma found in the second examination. The overall miss rate for adenomas was 12.01% and 11.32% for adenomas≥10mm.

Conclusion

This back-to-back study has shown that endocuff- assisted colonoscopy has a low adenoma miss rate. These data further strengthen the existing evidence recommending the use of endocuff for decreasing the adenoma miss rate.

Introduction

Accurate determination of withdrawal time (WT) is a critical quality metric within colonoscopy. While application of artificial intelligence (AI) to standardize WT estimation has been investigated, a critical need for further prospective validation exists.

Aims & Methods

We planned a prospective examiner-blinded evaluation to compare a novel AI system’s performance to that of physician assessment in routine colonoscopy from December 2023 to March 2024. Manual frame-by-frame video annotation provided the gold standard. The AI system autonomously generated detailed image reports, which were independently assessed by four endoscopists. (ClinicalTrials.gov NCT06094270).

Results

In the 126 analyzed examinations, our AI demonstrated a lower mean absolute error for WT estimation achieved by the AI system with 2.17 minutes compared to physician assessments with 4.23 minutes, p<0.01. Achieving mean 97% satisfaction with the timeline representation and 81% overall satisfaction, the AI generated comprehensive image reports.

Conclusion

These findings establish the potential of the AI system to improve efficiency and precision in WT calculation in clinical practice. This work represents a critical step towards integrating AI-driven solutions for optimizing clinical workflows and enhancing the quality of colorectal cancer screening.

Introduction

Videocolonoscopy (VCC) remains the gold standard in the diagnosis of colorectal carcinoma (CRC) and premalignant lesions. Around 26% of polyps are missed during conventional colonoscopy due to operator (e.g., expertise, fatigue, etc.), and technical (e.g., suboptimal bowel preparation and withdrawal time) dependent-factors. Artificial intelligence (AI) aids in adenoma and polyp detection, thus increasing adenoma and polyp detection rates (ADR and PDR, respectively).

Aims & Methods

We aim to evaluate the real-world effectiveness of an AI-assisted colonoscopy (AI-VCC) and compare the results among experts and non-experts endoscopists. Consecutive patients ≥45 years old who underwent VCC (Nov/2020-Mar/2021) were invited to participate. Patients with BBPS≤6, history of inflammatory bowel disease, familial polyposis syndrome, colorectal carcinoma, colorectal surgery, or uncontrolled coagulopathy were not considered. The study protocol was conducted according to the declaration of Helsinki and approved by the local Institutional Review Board (IRB). All patients signed an informed written consent. First, a standard HD-VCC was performed. Then, an AI-VCC was performed by a second operator blinded to previous findings. We determined the adenoma detection rate (ADR) as a quality indicator of the procedure. The polyp detection rate (PDR), and the adenoma and polyp miss rates (AMR and PMR, respectively) were also calculated. The results were compared between experts and non-experts endoscopists. Data was analyzed in R v4.0.

Results

A total of 115 patients were included. Median age was 57.0 (51.0 - 67.5) years, 82/115 (71.3%) were females. 58/115 (50.4%) patients had a total of 205 polyps/adenoma, with a PDR and ADR of 132/205 (64.3%) and 73/205 (35.6%) with VCC, respectively: 19/205 (9.3%) NICE II, 7/205 (3.4%) >10 mm. With AI-assistance, the ADR and PDR increased from 16.5% to 18.2% and from 50.4% to 60%, respectively. According to the level of expertise, the ADR increased from 10.8% to 16.2% in the junior group with the AI-VCC, whereas no difference in ADR was observed in the senior cohort (Table 1). The calculated PMR was 43.13% while the AMR was 5.19%. Sensitivity among different colon segments ranged from 56.25% (rectum) to 78.26% (ascending colon). Meanwhile, capability of AI for appropriate polyp and adenoma presence discharging (negative predictive value, NPV) ranged from 61.54% (sigmoid) to 89.09% (cecum). However, lower rates for specificity (8.42-49.49%) and positive predictive value (PPV, 9.89-19.78%) were observed due to high false positives. (Table 2).

Table 1. ADR and PDR during HD-VCC and AI-VCC in senior and junior endoscopists.

Conclusion

The AI-assisted polyp detector is a feasible tool to aid endoscopists during screening colonoscopy. Additionally, with AI-assistance, junior endoscopists can achieve an ADR comparable to that of senior endoscopists. NCT04915833.

References

1. Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, et al. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomized controlled study. Gut. 2019 Oct;68(10):1813-1819.
2. Zhao S, Wang S, Pan P, Xia T, Chang X, et al. Magnitude, Risk Factors, and Factors Associated with Adenoma Miss Rate of Tandem Colonoscopy: A Systematic Review and Meta-analysis. Gastroenterology. 2019;156 (6):1661–1674e11.
3. Mahmud N, Cohen J, Tsourides K, Berzin TM. Computer vision and augmented reality in gastrointestinal endoscopy. Gastroenterol Rep (Oxf). 2015 Aug;3(3):179-84.
4. Kröner PT, Engels MM, Glicksberg BS, Johnson KW, et al. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol 2021; 27(40): 6794-6824.
5. Taghiakbari M, Mori Y, von Renteln D. Artificial intelligence-assisted colonoscopy: A review of current state of practice and research. World J Gastroenterol. 2021 Dec 21;27(47):8103-8122.

Disclosure

Carlos Robles-Medranda is a key opinion leader and consultant for Pentax Medical, Boston Scientific, Steris, Medtronic, Motus, Micro-tech, G-Tech Medical Supply, CREO Medical, EndoSound, and Mdconsgroup. The other authors declare no conflicts of interest.

Introduction

One-fourth of colorectal neoplasia is missed at screening colonoscopy, representing the leading cause of interval colorectal cancer (I-CRC). Colonoscopy assisted by artificial intelligence (AI) with computer-aided polyp detection (CADe) showed higher adenoma detection rate (ADR) and higher adenoma per colonoscopy compared to white light (WL) colonoscopy in randomized clinical trials (RCTs). Despite ADR is a reliable quality indicator and has been associated to the risk of I-CRC and death, an adequate ADR does not eliminate the risk of lesion miss rate since the relationship between ADR and adenoma miss rate (AMR) is only indirect.

Aims & Methods

The aim of this meta-analysis is to summarise the performance of CADe systems on miss rate of colonic lesions. PubMed/Medline, Embase and Cochrane Library were systematically searched through October 2022 by two independent reviewers (M.M. and A.F.) for tandem-design RCTs comparing miss rate of colonic lesions in CAD-first colonoscopy followed by WL colonoscopy (experimental arm) vs WL-first colonoscopy followed by CAD colonoscopy (control arm).
The primary outcomes were pooled AMR and polyp miss rate (PMR). Secondary outcomes were advanced adenoma miss rate (aAMR) and sessile serrated lesion miss rate (SMR). Lesion miss rate was defined as the number of lesions detected at second colonoscopy divided by the total number of same lesions detected at first and second colonoscopy. A random-effect model was applied for pooling results. Heterogeneity was expressed as I².

Results

Overall, 4 RCTs (1166 patients), were included in the analysis. Pooled AMR was significantly lower in the CAD-first compared to WL-first arm (131/842, 15.5% vs 300/857, 35.0%; RR, 0.45; 95% CI, 0.35-0.58; P<0.001; I²=49%). PMR was also lower in the CAD-first compared to WL-first arm (192/1198, 16.0% vs 474/1244, 38.1%; RR, 0.43; 95% CI, 0.30-0.61; P<0.001; I²=82%).
No significant difference in aAMR (2/23, 8.7% vs 5/32, 15.6%; RR, 1.28; 95% CI, 0.34-4.83; P=0.71; I²=0%) and in SMR (5/43, 11.6% vs 27/67, 40.3%; RR, 0.44; 95% CI, 0.15-1.28; P=0.13; I²=46%) were observed.

Table 1. Characteristics of the studies included in the meta-analysis.

Conclusion

According to available evidence, the use of colonoscopy assisted by AI with CADe results in a significant lower AMR and PMR, with a potential implication in reducing the incidence of I-CRC. No significant difference in aAMR and SMR has been observed, even if these results should be further confirmed in studies with larger sample sizes.

Introduction

Colon capsule endoscopy (CCE) has been demonstrated to be comparable to colonoscopy and better than CT colonography (CTC) for the detection of colonic pathology. Challenges include poor completion rates and high re-investigation rates.

Aims & Methods

The aim of this study was to assess the role of CCE with faecal immunochemical testing (FIT) as a non-invasive, diagnostic tool in symptomatic and screening populations attending Connolly Hospital.
Prospective participants were identified from both the central endoscopy waiting list at Connolly Hospital and from our national colorectal screening programme, Bowel Screen. All participants were due to attend Connolly Hospital for a symptomatic or surveillance colonoscopy during the time period of the study. Consenting participants underwent CCE the day prior to their scheduled colonoscopy. CCEs were read by two expert readers. Participants were sent FIT kits to complete prior to CCE. Primary outcomes were CCE polyp detection rates (PDR). The potential benefit of using FIT as a triage tool to identify low-risk individuals appropriate for CCE over colonoscopy was explored.

Results

80 back-to-back procedures were completed January 2023-February 2024 (M: F 50:30, mean age 59.6, range 35-78) in a single centre. The most common indications for colonoscopy were surveillance 41.5%, PR bleeding 21% and diarrhoea/ IBD assessment 15%.
CCE detected a total of 108 polyps in 45/80 (56%) participants versus 93 polyps in 39/80 (48%) participants at colonoscopy (p= 0.34). When only complete CCE are included, the polyp detection rate increased to 31/45 (68%), p< 0.05. 79% supplied FITs prior to CCE. CCE PDR for all polyps when FIT < 50 ng/ml was 19/33 (57%) versus (20/27) 74% with FIT > 50 ng/ml (p=0.18). There is trend towards significance. A lower FIT cut-off, closer to limit of detection, not available to this study, may have more significant results.
Only one participant had a cancer diagnosed at colonoscopy. It was located on the ileocaecal valve. The cancer was not detected by CCE despite the capsule passing through this region. This, to our knowledge, is only the second missed cancer by CCE documented.
ESGE 2012 guidelines recommend follow up colonoscopy for one polyp measuring 6mm or more, or if three polyps of any size are detected. 50/80 (62.5%) CCE examinations would have required follow up if they were not part of a study and scheduled for next day colonoscopy. Even when looking at only those CCE examinations that were complete, 17/45 (38%) required further investigation. Reasons for re-investigation included incomplete examination 32/49 (65%), for polypectomy 16/49 (33%) and for biopsy in 1/49 (2%).
False negative CCE rates for polyps greater than 6mm range from 2-15.5% in the literature. In keeping with this, the false negative CCE for all polyps in this study was 8.75%, and 6.25% for polyps greater than 6mm.
There were no adverse events reported. There were technical issues reported in 16% of CCE. These included the capsule not turning on until it was beyond the caecum, participants removing the belt intermittently and one interference which was believed to be secondary to a topical glucose monitor.

Conclusion

The increasing demand on colonoscopy waiting lists raises concerns regarding the ability of health services to deliver traditional endoscopy in a timely fashion. Alternative modalities are necessary and CCE is a viable diagnostic alternative. There is likely a role for FIT testing as a triage tool prior to CCE to reduce re-investigation rates.