The Safety of Cold Versus Hot Snare Polypectomy in Polyps 10-20 mm: A Systematic Review and Meta-Analysis.

Colonoscopy remains the primary method for preventing colorectal cancer. Traditionally, hot snare polypectomy (HSP) was the method of choice for removing polyps larger than 5 mm. Yet, for polyps smaller than 10 mm, cold snare polypectomy (CSP) has become the favored approach. Lately, the use of CSP has expanded to include the removal of sessile polyps that are between 10 and 20 mm in size. Our systematic review and meta-analysis aimed to evaluate the safety of cold snare polypectomy (CSP) compared to hot snare polypectomy (HSP) for resecting polyps measuring 10-20 mm. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Embase, and Cochrane databases up to April 2020 to find studies that directly compared CSP to HSP for polyps larger than 10 mm. Our main focus was on assessing the risk of delayed bleeding after polypectomy; a secondary focus was the incidence of any adverse events that required medical intervention post procedure. Our search yielded three comparative studies, two observational studies, and one randomized controlled trial (RCT), together encompassing 1,193 polypectomy procedures. Of these, 485 were performed using CSP and 708 with HSP. The pooled odds ratio (OR) for post-polypectomy bleeding (PPB) was 0.36 (95% confidence interval {CI}: 0.02, 7.13), with a Cochran Q test P-value of 0.11 and an I2 of 53%. For the risk of any adverse events necessitating medical care, the pooled OR was 0.15 (95% CI: 0.01, 2.29), with a Cochran Q test P-value of 0.21 and an I2 of 35%. The quality of the two observational studies was deemed moderate, and the RCT was only available in abstract form, preventing quality assessment. Our analysis suggests that there is no significant difference in the incidence of delayed post-polypectomy bleeding or other adverse events requiring medical attention between CSP and HSP for polyps measuring 10-20 mm.

Evaluating the Efficacy of Resect-and-Discard and Resect-and-Retrieve Strategies for Diminutive Colonic Polyps.

BACKGROUND AND OBJECTIVES: Diminutive polyps present a unique challenge in colorectal cancer (CRC) prevention strategies. This study aims to assess the characteristics and variables of diminutive polyps in a Romanian cohort, intending to develop a combined resect-and-retrieve or resect-and-discard strategy that reduces the need for an optical diagnosis. MATERIALS AND METHODS: A prospective cohort study was conducted at two endoscopy centers in Romania from July to December 2021. Adult patients undergoing colonoscopies where polyps were identified and resected were included. Endoscopic procedures employed advanced diagnostic features, including blue-light imaging (BLI) and narrow-band imaging (NBI). Logistic regression analysis was utilized to determine factors impacting the probability of adenomatous polyps with high-grade dysplasia (HGD). RESULTS: A total of 427 patients were included, with a mean age of 59.42 years (±11.19), predominantly male (60.2%). The most common indication for a colonoscopy was lower gastrointestinal symptoms (42.6%), followed by screening (28.8%). Adequate bowel preparation was achieved in 87.8% of cases. The logistic regression analysis revealed significant predictors of HGD in adenomatous polyps: age (OR = 1.05, 95% CI: 1.01-1.08, p = 0.01) and polyp size (>5 mm vs. ≤5 mm, OR = 4.4, 95% CI: 1.94-10.06, p < 0.001). Polyps classified as Paris IIa, Ip, and Isp were significantly more likely to harbor HGD compared to the reference group (Is), with odds ratios of 6.05, 3.68, and 2.7, respectively. CONCLUSIONS: The study elucidates significant associations between the presence of HGD in adenomatous polyps and factors such as age, polyp size, and Paris classification. These findings support the feasibility of a tailored approach in the resect-and-discard and resect-and-retrieve strategies for diminutive polyps, potentially optimizing CRC prevention and intervention practices. Further research is warranted to validate these strategies in broader clinical settings.

A colonial serrated polyp classification model using white-light ordinary endoscopy images with an artificial intelligence model and TensorFlow chart.

In this study, we implemented a combination of data augmentation and artificial intelligence (AI) model-Convolutional Neural Network (CNN)-to help physicians classify colonic polyps into traditional adenoma (TA), sessile serrated adenoma (SSA), and hyperplastic polyp (HP). We collected ordinary endoscopy images under both white and NBI lights. Under white light, we collected 257 images of HP, 423 images of SSA, and 60 images of TA. Under NBI light, were collected 238 images of HP, 284 images of SSA, and 71 images of TA. We implemented the CNN-based artificial intelligence model, Inception V4, to build a classification model for the types of colon polyps. Our final AI classification model with data augmentation process is constructed only with white light images. Our classification prediction accuracy of colon polyp type is 94%, and the discriminability of the model (area under the curve) was 98%. Thus, we can conclude that our model can help physicians distinguish between TA, SSA, and HPs and correctly identify precancerous lesions such as TA and SSA.

Tri-branch feature pyramid network based on federated particle swarm optimization for polyp segmentation.

Deep learning technology has shown considerable potential in various domains. However, due to privacy issues associated with medical data, legal and ethical constraints often result in smaller datasets. The limitations of smaller datasets hinder the applicability of deep learning technology in the field of medical image processing. To address this challenge, we proposed the Federated Particle Swarm Optimization algorithm, which is designed to increase the efficiency of decentralized data utilization in federated learning and to protect privacy in model training. To stabilize the federated learning process, we introduced Tri-branch feature pyramid network (TFPNet), a multi-branch structure model. TFPNet mitigates instability during the aggregation model deployment and ensures fast convergence through its multi-branch structure. We conducted experiments on four different public datasets：CVC-ClinicDB, Kvasir, CVC-ColonDB and ETIS-LaribPolypDB. The experimental results show that the Federated Particle Swarm Optimization algorithm outperforms single dataset training and the Federated Averaging algorithm when using independent scattered data, and TFPNet converges faster and achieves superior segmentation accuracy compared to other models.

Predictive factors and model validation of post-colon polyp surgery Helicobacter pylori infection.

BACKGROUND: Recently, research has linked Helicobacter pylori (H. pylori) stomach infection to colonic inflammation, mediated by toxin production, potentially impacting colorectal cancer occurrence. AIM: To investigate the risk factors for post-colon polyp surgery, H. pylori infection, and its correlation with pathologic type. METHODS: Eighty patients who underwent colon polypectomy in our hospital between January 2019 and January 2023 were retrospectively chosen. They were then randomly split into modeling (n = 56) and model validation (n = 24) sets using R. The modeling cohort was divided into an H. pylori-infected group (n = 37) and an H. pylori-uninfected group (n = 19). Binary logistic regression analysis was used to analyze the factors influencing the occurrence of H. pylori infection after colon polyp surgery. A roadmap prediction model was established and validated. Finally, the correlation between the different pathological types of colon polyps and the occurrence of H. pylori infection was analyzed after colon polyp surgery. RESULTS: Univariate results showed that age, body mass index (BMI), literacy, alcohol consumption, polyp pathology type, high-risk adenomas, and heavy diet were all influential factors in the development of H. pylori infection after intestinal polypectomy. Binary multifactorial logistic regression analysis showed that age, BMI, and type of polyp pathology were independent predictors of the occurrence of H. pylori infection after intestinal polypectomy. The area under the receiver operating characteristic curve was 0.969 [95% confidence interval (95%CI): 0.928-1.000] and 0.898 (95%CI: 0.773-1.000) in the modeling and validation sets, respectively. The slope of the calibration curve of the graph was close to 1, and the goodness-of-fit test was P > 0.05 in the two sets. The decision analysis curve showed a high rate of return in both sets. The results of the correlation analysis between different pathological types and the occurrence of H. pylori infection after colon polyp surgery showed that hyperplastic polyps, inflammatory polyps, and the occurrence of H. pylori infection were not significantly correlated. In contrast, adenomatous polyps showed a significant positive correlation with the occurrence of H. pylori infection. CONCLUSION: Age, BMI, and polyps of the adenomatous type were independent predictors of H. pylori infection after intestinal polypectomy. Moreover, the further constructed column-line graph prediction model of H. pylori infection after intestinal polypectomy showed good predictive ability.

Colonoscopic-assisted laparoscopic wedge resection versus segmental colon resection for benign colonic polyps: a comparative cost analysis.

AIM: The colonoscopic-assisted laparoscopic wedge resection (CAL-WR) is proven to be an effective and safe alternative to a segmental colon resection (SCR) for large or complex benign colonic polyps that are not eligible for endoscopic removal. This analysis aimed to evaluate the costs of CAL-WR and compare them to the costs of an SCR. METHOD: A single-centre 90-day 'in-hospital' comparative cost analysis was performed on patients undergoing CAL-WR or SCR for complex benign polyps between 2016 and 2020. The CAL-WR group consisted of 44 patients who participated in a prospective multicentre study (LIMERIC study). Inclusion criteria were (1) endoscopically unresectable benign polyps; (2) residual or recurrence after previous polypectomy; or (3) irradically resected low risk pT1 colon carcinoma. The comparison group, which was retrospectively identified, included 32 patients who underwent an elective SCR in the same period. RESULTS: Colonoscopic-assisted laparoscopic wedge resection was associated with significantly fewer complications (7% in the CAL-WR group vs. 45% in the SCR group, P < 0.001), shorter operation time (50 min in the CAL-WR group vs. 119 min in the SCR group, P < 0.001), shorter length of hospital stay (median length of stay 2 days in the CAL-WR group vs. 4 days in the SCR group, P < 0.001) and less use of surgical resources (reduction in costs of 32% per patient), resulting in a cost savings of €2372 (£2099 GBP) per patient (P < 0.001). CONCLUSION: Given the clinical and financial benefits, CAL-WR should be recommended for complex benign polyps that are not eligible for endoscopic resection before major surgery is considered.

AGA Clinical Practice Update on the Role of Artificial Intelligence in Colon Polyp Diagnosis and Management: Commentary.

DESCRIPTION: The purpose of this American Gastroenterological Association (AGA) Institute Clinical Practice Update (CPU) is to review the available evidence and provide expert commentary on the current landscape of artificial intelligence in the evaluation and management of colorectal polyps. METHODS: This CPU was commissioned and approved by the AGA Institute Clinical Practice Updates Committee (CPUC) and the AGA Governing Board to provide timely guidance on a topic of high clinical importance to the AGA membership and underwent internal peer review by the CPUC and external peer review through standard procedures of Gastroenterology. This Expert Commentary incorporates important as well as recently published studies in this field, and it reflects the experiences of the authors who are experienced endoscopists with expertise in the field of artificial intelligence and colorectal polyps.

Prognostic roles and survival benefits of endoscopic resection versus surgical resection in the management of malignant colon polyps

Background: Due to few sufficient data regarding the comparison between endoscopic and surgical resection of malignant colorectal polyps regarding outcomes and survival benefits, there are no clear guidelines of management strategies of malignant colorectal polyps. The aims of the present study were to compare endoscopic resection alone and surgical resection in patients with malignant polyps in the colon (T1N0M0) readings advantages, disadvantages, recurrence risks, survival benefits, and long-term prognosis to detect how management strategy affects outcome. Patients and methods: we included 350 patients. All included patients were divided into 2 groups; the first group included 100 patients who underwent only endoscopic polypectomy and the second group included 250 patients who underwent endoscopic polypectomy followed by definitive surgical resection after histopathological diagnosis. We followed all patients for about 5 years, ranging from 18 to 55 months. The primarily evaluated parameters are surgical consequences and patients' morbidity. The secondary evaluated parameters are recurrence risks, recurrence free survival, and overall survival rates. Results: The age of patients who underwent polypectomy is usually younger than the surgical group, males have more liability to polypectomy in comparison with females. Patients with tumors in the left colon have more liability to polypectomy in comparison with the right colon (p< 0.0001). Tumor factors associated with more liability to surgical resection are presence of lymphovascular invasion, high grade, and poor tumor differentiation (p< 0.0001). The management strategy was the most significant predictor of overall and recurrence free survival rates in patients with malignant colon polyps (p< 0.001). Conclusions: We found that survival benefits and lower incidence of recurrence are detected in the surgical resection group more than in the polypectomy group. (AU)

Unusual Instance of Mucosa-Associated Lymphoid Tissue (MALT) Lymphoma Confined to a Colonic Polyp.

Extranodal marginal zone lymphoma (EMZL) of mucosa-associated lymphoid tissue (MALT) commonly affects the gastrointestinal (GI) tract but rarely occurs within the colon. Colonic EMZL is a rare diagnosis accounting for 2.5% of EMZL and less than 0.5% of colon cancers. We present a unique case of asymptomatic colonic EMZL diagnosed on a routine surveillance colonoscopy. The lymphoma was confined to a single colonic polyp presenting endoscopically as a sessile polypoid lesion at the recto-sigmoid junction. The patient was successfully treated with polypectomy with no recurrence of the disease.

Through the Looking Glass: Surveillance Following Colonoscopic Polypectomy of Malignant Polyps.

Introduction Colonoscopic polypectomy is a well-established screening and surveillance modality for malignant colorectal polyps. Following the detection of a malignant polyp, patients are either put on endoscopic surveillance or planned for a surgical procedure. We studied the outcome of colonoscopic excision of malignant polyps and their recurrence rates. Methods We performed a retrospective analysis over a period of five years (2015-2019) of patients who underwent colonoscopy and resection of malignant polyps. Size of polyp, follow-up with tumour markers, CT scan, and biopsy were considered individually for pedunculate and sessile polyps. We analysed the percentage of patients who underwent surgical resection, the percentage of patients who were managed conservatively, and the percentage of recurrence post-excision of malignant polyps. Results A total of 44 patients were included in the study. Of the 44 malignant polyps, most were present in the sigmoid colon at 43% (n=19), with the rectum containing 41% (n=18). The ascending colon accounted for 4.5% (n=2), transverse colonic polyps were 7% (n=3), and the descending colon polyps were 4.5% (n=2). Pedunculated polyps made up 55% (n=24). These were Level 1-3 based on Haggits classification; 14 were Haggits Level 1, eight were Haggits Level 2, and two were Haggits Level 3. The rest were sessile polyps making up 45% (n=20). Based on the Kikuchi classification, these were predominantly SM1 (n=12) and SM2 (n=8). Out of 44 cases, 11% (n=5) underwent surgical resection on follow-up in the form of bowel resection. This included three right hemicolectomies, one sigmoid colectomy, and one low anterior resection. Seven per cent (n=3) underwent endoscopic resection as trans-anal endoscopic mucosal resection (TEMS) and 82% (n=36) of the remaining cases were managed with regular follow-up and surveillance. Conclusions Colonoscopic polypectomy offers excellent benefits in detecting colorectal cancer and treating pre-malignant polyps. Colonoscopic polypectomy provides excellent benefits in colorectal cancer (CRC) detection and treatment of malignant polyps. However, it remains to be seen if post-polypectomy surveillance for low-risk polyp cancers would require a change in surveillance.

Hybrid Argon Plasma Coagulation for Barrett's Esophagus and for Colonic Mucosal Resection-A Systematic Review and Meta-Analysis.

Hybrid argon plasma coagulation (hAPC) is a novel technique that combines conventional argon plasma coagulation and waterjet submucosal expansion. The aims of this metanalysis were to evaluate the efficacy and safety of hAPC in the setting of Barret's esophagus (BE) ablation and as an adjunct to colonic endoscopic mucosal resection (EMR). Four electronic databases were searched, and the results were analyzed by two independent authors. Random-effects meta-analyses of the proportions of endoscopic and histologic remission (for BE), recurrence, and post-procedure adverse events were performed using R. Studies' reporting quality was also assessed. From the 979 identified records, 13 studies were included (10 regarding BE and three colonic EMR). The pooled percentages of endoscopic and histologic remission after hAPC for BE were 95% (95% confidence interval [CI] 91-99, I2 = 34) and 90% (95%CI 84-95, I2 = 46), respectively, while major adverse events and recurrence were registered in 2% (95%CI 0-5, I2 = 41) and 11% (95%CI 2-27, I2 = 11), respectively. Concerning hAPC-assisted EMR, the pooled percentages of major adverse events and recurrence were 5% (95%CI 2-10, I2 = 0) and 1% (95%CI 0-3, I2 = 40). Evidence suggests that the main advantages of hAPC are the increase in safety in the setting of BE ablation and the reduction of local recurrence after colonic EMR. Trials comparing hAPC with standard strategies are required to support its use for these indications.

Mastocytic Enterocolitis: An Overlooked Diagnosis for Unexplained Chronic Diarrhea in a Patient With Colon Polyps and a Family History of Colon Cancer.

Chronic intractable diarrhea is a common presenting complaint that is often clinically worked up for a wide variety of diseases including inflammatory bowel disease, celiac disease, and hyperthyroidism. When lab results come back normal, patients are often diagnosed with irritable bowel disease-diarrheal subtype, overlooking the potential diagnosis of mastocytic enterocolitis. Mastocytic enterocolitis is an uncommon diagnosis where patients can benefit from mast cell stabilizers that directly target the underlying pathology. Given the broad differential diagnosis of nonspecific diarrhea presentation, a histopathological examination is warranted for definitive diagnosis. We hope to raise awareness of this potentially treatable disease that can be effectively managed with antihistamines. We describe the case of a 63-year-old male patient with a family history significant for colon cancer who presented with intractable diarrhea and was ultimately diagnosed with mastocytic enterocolitis by histopathology. His symptoms were relieved by antihistamine treatment.

Colon Cancer Screening Methods: 2023 Update.

Colorectal cancer (CRC) is a significant cause of morbidity and mortality worldwide. National screening guidelines have been implemented to identify and remove precancerous polyps before they become cancer. Routine CRC screening is advised for people with average risk starting at age 45 because it is a common and preventable malignancy. Various screening modalities are currently in use, ranging from stool-based tests (fecal occult blood test (FOBT), fecal immunochemical test (FIT), and FIT-DNA test), radiologic tests (computed tomographic colonography (CTC), double contrast barium enema), and visual endoscopic examinations (flexible sigmoidoscopy (FS), colonoscopy, and colon capsule endoscopy (CCE)) with their varying sensitivity and specificity. Biomarkers also play a vital role in assessing the recurrence of CRC. This review offers a summary of the current screening options, including biomarkers available to detect CRC, highlighting the benefits and challenges encompassing each screening modality.

The relationship between colon polyps and colonic diverticulosis: a retrospective review.

Background: Colonic diverticulosis and colon polyps are common findings on colonoscopy. There is currently no consensus regarding a possible connection between the development of polyps and diverticulosis. Multiple research studies have sought to analyze whether the presence of both conditions is associated with the development of colorectal cancer. Our study aims to add to this body of data and to better assess the relationship between diverticulosis and colon polyps. Methods: A retrospective chart review was performed of all patients who underwent screening and diagnostic colonoscopies between January 2011 and December 2020. Data collection included patient demographics; number, pathology, and location of colon polyps; incidence of colon cancer; and presence and location of colonic diverticulosis. Results: Our study demonstrated that the overall presence of diverticulosis in any location increases the likelihood of having nearby colon polyps, regardless of subtype. The presence of left colonic diverticulosis was particularly associated with adjacent adenomatous and non-adenomatous colon polyps. Conclusions: Colonic diverticulosis in any location may lead to an increased incidence of adenomatous colon polyps. It is important to perform careful examination of the mucosa surrounding colon diverticulosis to avoid missing colon polyps.

Computer-aided automated diminutive colonic polyp detection in colonoscopy by using deep machine learning system; first indigenous algorithm developed in India.

BACKGROUND: Colonic polyps can be detected and resected during a colonoscopy before cancer development. However, about 1/4th of the polyps could be missed due to their small size, location or human errors. An artificial intelligence (AI) system can improve polyp detection and reduce colorectal cancer incidence. We are developing an indigenous AI system to detect diminutive polyps in real-life scenarios that can be compatible with any high-definition colonoscopy and endoscopic video- capture software. METHODS: We trained a masked region-based convolutional neural network model to detect and localize colonic polyps. Three independent datasets of colonoscopy videos comprising 1,039 image frames were used and divided into a training dataset of 688 frames and a testing dataset of 351 frames. Of 1,039 image frames, 231 were from real-life colonoscopy videos from our centre. The rest were from publicly available image frames already modified to be directly utilizable for developing the AI system. The image frames of the testing dataset were also augmented by rotating and zooming the images to replicate real-life distortions of images seen during colonoscopy. The AI system was trained to localize the polyp by creating a 'bounding box'. It was then applied to the testing dataset to test its accuracy in detecting polyps automatically. RESULTS: The AI system achieved a mean average precision (equivalent to specificity) of 88.63% for automatic polyp detection. All polyps in the testing were identified by AI, i.e., no false-negative result in the testing dataset (sensitivity of 100%). The mean polyp size in the study was 5 (± 4) mm. The mean processing time per image frame was 96.4 minutes. CONCLUSIONS: This AI system, when applied to real-life colonoscopy images, having wide variations in bowel preparation and small polyp size, can detect colonic polyps with a high degree of accuracy.

Evaluation of the competence of an artificial intelligence-assisted colonoscopy system in clinical practice: A post hoc analysis.

Background: Artificial intelligence-assisted colonoscopy (AIAC) has been proposed and validated in recent years, but the effectiveness of clinic application remains unclear since it was only validated in some clinical trials rather than normal conditions. In addition, previous clinical trials were mostly concerned with colorectal polyp identification, while fewer studies are focusing on adenoma identification and polyps size measurement. In this study, we validated the effectiveness of AIAC in the clinical environment and further investigated its capacity for adenoma identification and polyps size measurement. Methods: The information of 174 continued patients who went for coloscopy in Chongqing Rongchang District People's hospital with detected colon polyps was retrospectively collected, and their coloscopy images were divided into three validation datasets, polyps dataset, polyps/adenomas dataset (all containing narrow band image, NBI images), and polyp size measurement dataset (images with biopsy forceps and polyps) to assess the competence of the artificial intelligence system, and compare its diagnostic ability with endoscopists with different experiences. Results: A total of 174 patients were included, and the sensitivity of the colorectal polyp recognition model was 99.40%, the accuracy of the colorectal adenoma diagnostic model was 93.06%, which was higher than that of endoscopists, and the mean absolute error of the polyp size measurement model was 0.62 mm and the mean relative error was 10.89%, which was lower than that of endoscopists. Conclusion: Artificial intelligence-assisted model demonstrated higher competence compared with endoscopists and stable diagnosis ability in clinical use.

FRCNN-AA-CIF: An automatic detection model of colon polyps based on attention awareness and context information fusion.

It is noted that the foreground and background of the polyp images detected under colonoscopy are not highly differentiated, and the feature map extracted by common deep learning object detection models keep getting smaller as the number of networks increases. Therefore, these models tend to ignore the details in pictures, resulting in a high polyp missed detection rate. To reduce the missed detection rate, this paper proposes an automatic detection model of colon polyps based on attention awareness and context information fusion (FRCNN-AA-CIF) based on a two-stage object detection model Faster Region-Convolutional Neural Network (FR-CNN). First, since the addition of attention awareness can make the feature extraction network pay more attention to polyp features, we propose an attention awareness module based on Squeeze-and-Excitation Network (SENet) and Efficient Channel Attention Module (ECA-Net) and add it after each block of the backbone network. Specifically, we first use the 1*1 convolution of ECA-Net to extract local cross-channel information and then use the two fully connected layers of SENet to reduce and increase the dimension, to filter out the channels that are more useful for feature learning. Further, because of the presence of air bubbles, impurities, inflammation, and accumulation of digestive matter around polyps, we used context information around polyps to enhance the focus on polyp features. In particular, after the network extracts the region of interest, we fuse the region of interest with its context information to improve the detection rate of polyps. The proposed model was tested on the colonoscopy dataset provided by Huashan Hospital. Numerical experiments show that FRCNN-AA-CIF has the highest detection accuracy (mAP of 0.817), the lowest missed detection rate of 4.22%, and the best classification effect (AUC of 95.98%). Its mAP increased by 3.3%, MDR decreased by 1.97%, and AUC increased by 1.8%. Compared with other object detection models, FRCNN-AA-CIF has significantly improved recognition accuracy and reduced missed detection rate.

Association of CDH1 Germline Variants and Colon Polyp Phenotypes in Patients with Hereditary Diffuse Gastric Cancer.

Background and Aims: Germline CDH1 variants resulting in E-cadherin loss of function result in an increased risk of diffuse type gastric cancer and lobular type breast cancer. However, the risk of developing other epithelial neoplasms, specifically colorectal cancer, is unknown. Methods: Patients enrolled in a prospective natural history study of hereditary gastric cancer who underwent at least one colonoscopy were evaluated. Results: Out of 300 patients with CDH1 pathogenic or likely pathogenic variants, 85 underwent colonoscopy. More than half of patients (56%, 48/85) had at least one colorectal polyp. Most of those patients (83%, 40/48) had at least one precancerous polyp (adenoma or sessile serrated lesion). More than half (56%) of patients younger than age 45 had a colorectal polyp. Of those with polyps, the most frequent CDH1 variant type was canonical splice site (27%, 13/48) followed by nonsense (21%, 10/48). There was no association between CDH1 variant type and increased likelihood of colorectal polyps. Conclusions: In summary, a majority of CDH1 variant carriers who underwent colonoscopy had colorectal polyps detected, and most subjects were less than 45 years old. This study of colorectal cancer risk based on the prevalence of colorectal polyps in the CDH1 population requires further investigation to appropriately counsel patients on colorectal cancer screening. Clinical trial registry website: https://clinicaltrials.gov/. Clinical trial number: NCT03030404.

Clinical Evaluation of Computer-Aided Colorectal Neoplasia Detection Using a Novel Endoscopic Artificial Intelligence: A Single-Center Randomized Controlled Trial.

INTRODUCTION: Computer-aided diagnostic systems are emerging in the field of gastrointestinal endoscopy. In this study, we assessed the clinical performance of the computer-aided detection (CADe) of colonic adenomas using a new endoscopic artificial intelligence system. METHODS: This was a single-center prospective randomized study including 415 participants allocated into the CADe group (n = 207) and control group (n = 208). All endoscopic examinations were performed by experienced endoscopists. The performance of the CADe was assessed based on the adenoma detection rate (ADR). Additionally, we compared the adenoma miss rate for the rectosigmoid colon (AMRrs) between the groups. RESULTS: The basic demographic and procedural characteristics of the CADe and control groups were as follows: mean age, 54.9 and 55.9 years; male sex, 73.9% and 69.7% of participants; and mean withdrawal time, 411.8 and 399.0 s, respectively. The ADR was 59.4% in the CADe group and 47.6% in the control group (p = 0.018). The AMRrs was 11.9% in the CADe group and 26.0% in the control group (p = 0.037). CONCLUSION: The colonoscopy with the CADe system yielded an 11.8% higher ADR than that performed by experienced endoscopists alone. Moreover, there was no need to extend the examination time or request the assistance of additional medical staff to achieve this improved effectiveness. We believe that the novel CADe system can lead to considerable advances in colorectal cancer diagnosis.