Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ : A Systematic Review and Meta-analysis.

BACKGROUND: Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE: To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES: Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION: Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION: The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS: Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION: The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION: Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE: European Commission. (PROSPERO: CRD42023402197).

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the current literature, highlighted potential areas, and outlined the necessary research in artificial intelligence (AI) to allow a clearer understanding of AI as it pertains to endoscopy currently. METHODS: A modified Delphi process was used to develop these consensus statements. RESULTS: Statement 1: Current advances in AI allow for the development of AI-based algorithms that can be applied to endoscopy to augment endoscopist performance in detection and characterization of endoscopic lesions. Statement 2: Computer vision-based algorithms provide opportunities to redefine quality metrics in endoscopy using AI, which can be standardized and can reduce subjectivity in reporting quality metrics. Natural language processing-based algorithms can help with the data abstraction needed for reporting current quality metrics in GI endoscopy effortlessly. Statement 3: AI technologies can support smart endoscopy suites, which may help optimize workflows in the endoscopy suite, including automated documentation. Statement 4: Using AI and machine learning helps in predictive modeling, diagnosis, and prognostication. High-quality data with multidimensionality are needed for risk prediction, prognostication of specific clinical conditions, and their outcomes when using machine learning methods. Statement 5: Big data and cloud-based tools can help advance clinical research in gastroenterology. Multimodal data are key to understanding the maximal extent of the disease state and unlocking treatment options. Statement 6: Understanding how to evaluate AI algorithms in the gastroenterology literature and clinical trials is important for gastroenterologists, trainees, and researchers, and hence education efforts by GI societies are needed. Statement 7: Several challenges regarding integrating AI solutions into the clinical practice of endoscopy exist, including understanding the role of human-AI interaction. Transparency, interpretability, and explainability of AI algorithms play a key role in their clinical adoption in GI endoscopy. Developing appropriate AI governance, data procurement, and tools needed for the AI lifecycle are critical for the successful implementation of AI into clinical practice. Statement 8: For payment of AI in endoscopy, a thorough evaluation of the potential value proposition for AI systems may help guide purchasing decisions in endoscopy. Reliable cost-effectiveness studies to guide reimbursement are needed. Statement 9: Relevant clinical outcomes and performance metrics for AI in gastroenterology are currently not well defined. To improve the quality and interpretability of research in the field, steps need to be taken to define these evidence standards. Statement 10: A balanced view of AI technologies and active collaboration between the medical technology industry, computer scientists, gastroenterologists, and researchers are critical for the meaningful advancement of AI in gastroenterology. CONCLUSIONS: The consensus process led by the ASGE AI Task Force and experts from various disciplines has shed light on the potential of AI in endoscopy and gastroenterology. AI-based algorithms have shown promise in augmenting endoscopist performance, redefining quality metrics, optimizing workflows, and aiding in predictive modeling and diagnosis. However, challenges remain in evaluating AI algorithms, ensuring transparency and interpretability, addressing governance and data procurement, determining payment models, defining relevant clinical outcomes, and fostering collaboration between stakeholders. Addressing these challenges while maintaining a balanced perspective is crucial for the meaningful advancement of AI in gastroenterology.

Physician perceptions on the current and future impact of artificial intelligence to the field of gastroenterology.

BACKGROUND AND AIMS: The use of artificial intelligence (AI) has transformative implications to the practice of gastroenterology and endoscopy. The aims of this study were to understand the perceptions of the gastroenterology community toward AI and to identify potential barriers for adoption. METHODS: A 16-question online survey exploring perceptions on the current and future implications of AI to the field of gastroenterology was developed by the American Society for Gastrointestinal Endoscopy AI Task Force and distributed to national and international society members. Participant demographic information including age, sex, experience level, and practice setting was collected. Descriptive statistics were used to summarize survey findings, and a Pearson χ2 analysis was performed to determine the association between participant demographic information and perceptions of AI. RESULTS: Of 10,162 invited gastroenterologists, 374 completed the survey. The mean age of participants was 46 years (standard deviation, 12), and 299 participants (80.0%) were men. One hundred seventy-nine participants (47.9%) had >10 years of practice experience, with nearly half working in the community setting. Only 25 participants (6.7%) reported the current use of AI in their clinical practice. Most participants (95.5%) believed that AI solutions will have a positive impact in their practice. One hundred seventy-six participants (47.1%) believed that AI will make clinical duties more technical but will also ease the burden of the electronic medical record (54.0%). The top 3 areas where AI was predicted to be most influential were endoscopic lesion detection (65.3%), endoscopic lesion characterization (65.8%), and quality metrics (32.6%). Participants voiced a desire for education on topics such as the clinical use of AI applications (64.4%), the advantages and limitations of AI applications (57.0%), and the technical methodology of AI (44.7%). Most participants (42.8%) expressed that the cost of AI implementation should be covered by their hospital. Demographic characteristics significantly associated with this perception included participants' years in practice and practice setting. CONCLUSIONS: Gastroenterologists have an overall positive perception regarding the use of AI in clinical practice but voiced concerns regarding its technical aspects and coverage of costs associated with implementation. Further education on the clinical use of AI applications with understanding of the advantages and limitations appears to be valuable in promoting adoption.

Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.

INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measurement. METHODS: This was a US-based, multicenter, prospective randomized trial examining a novel AI detection system (EW10-EC02) that enables a real-time colorectal polyp detection enabled with the colonoscope (CAD-EYE). Eligible average-risk subjects (45 years or older) undergoing screening or surveillance colonoscopy were randomized to undergo either CAD-EYE-assisted colonoscopy (CAC) or conventional colonoscopy (CC). Modified intention-to-treat analysis was performed for all patients who completed colonoscopy with the primary outcome of APC. Secondary outcomes included positive predictive value (total number of adenomas divided by total polyps removed) and adenoma detection rate. RESULTS: In modified intention-to-treat analysis, of 1,031 subjects (age: 59.1 ± 9.8 years; 49.9% male), 510 underwent CAC vs 523 underwent CC with no significant differences in age, gender, ethnicity, or colonoscopy indication between the 2 groups. CAC led to a significantly higher APC compared with CC: 0.99 ± 1.6 vs 0.85 ± 1.5, P = 0.02, incidence rate ratio 1.17 (1.03-1.33, P = 0.02) with no significant difference in the withdrawal time: 11.28 ± 4.59 minutes vs 10.8 ± 4.81 minutes; P = 0.11 between the 2 groups. Difference in positive predictive value of a polyp being an adenoma among CAC and CC was less than 10% threshold established: 48.6% vs 54%, 95% CI -9.56% to -1.48%. There were no significant differences in adenoma detection rate (46.9% vs 42.8%), advanced adenoma (6.5% vs 6.3%), sessile serrated lesion detection rate (12.9% vs 10.1%), and polyp detection rate (63.9% vs 59.3%) between the 2 groups. There was a higher polyp per colonoscopy with CAC compared with CC: 1.68 ± 2.1 vs 1.33 ± 1.8 (incidence rate ratio 1.27; 1.15-1.4; P < 0.01). DISCUSSION: Use of a novel AI detection system showed to a significantly higher number of adenomas per colonoscopy compared with conventional high-definition colonoscopy without any increase in colonoscopy withdrawal time, thus supporting the use of AI-assisted colonoscopy to improve colonoscopy quality ( ClinicalTrials.gov NCT04979962).

Recent advances in devices and technologies that might prove revolutionary for colonoscopy procedures.

INTRODUCTION: Colorectal cancer (CRC) is the third most common malignancy and second leading cause of cancer-related mortality in the world. Adenoma detection rate (ADR), a quality indicator for colonoscopy, has gained prominence as it is inversely related to CRC incidence and mortality. As such, recent efforts have focused on developing novel colonoscopy devices and technologies to improve ADR. AREAS COVERED: The main objective of this paper is to provide an overview of advancements in the fields of colonoscopy mechanical attachments, artificial intelligence-assisted colonoscopy, and colonoscopy optical enhancements with respect to ADR. We accomplished this by performing a comprehensive search of multiple electronic databases from inception to September 2023. This review is intended to be an introduction to colonoscopy devices and technologies. EXPERT OPINION: Numerous mechanical attachments and optical enhancements have been developed that have the potential to improve ADR and AI has gone from being an inaccessible concept to a feasible means for improving ADR. While these advances are exciting and portend a change in what will be considered standard colonoscopy, they continue to require refinement. Future studies should focus on combining modalities to further improve ADR and exploring the use of these technologies in other facets of colonoscopy.

Artificial Intelligence-Assisted Optical Diagnosis: A Comprehensive Review of Its Role in Leave-In-Situ and Resect-and-Discard Strategies in Colonoscopy.

Colorectal cancer screening plays a vital role in early detection and removal of precancerous adenomas, contributing to decreased mortality rates. Most polyps found during colonoscopies are small and unlikely to harbor advanced neoplasia or invasive cancer, leading to the development of "leave-in-situ" and "resect-and-discard" approaches. These strategies could lead to significant cost savings and efficiencies, but their implementation has been hampered by concerns around financial incentives, medical-legal risks, and local rules for tissue handling. This article reviews the potential of artificial intelligence to enhance the accuracy of polyp diagnosis through computer-aided diagnosis (CADx). While the adoption of CADx in optical biopsy has shown mixed results, it has the potential to significantly improve the management of colorectal polyps. Several studies reviewed in this article highlight the varied results of CADx in optical biopsy for colorectal polyps. Although artificial intelligence does not consistently outperform expert endoscopists, it has the potential to serve as a beneficial secondary reader, aiding in accurate optical diagnosis and increasing the confidence of the endoscopist. These studies indicate that although CADx holds great potential, it is yet to fully meet the performance thresholds necessary for clinical implementation.

Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial.

BACKGROUND & AIMS: Both computer-aided detection (CADe)-assisted and Endocuff-assisted colonoscopy have been found to increase adenoma detection. We investigated the performance of the combination of the 2 tools compared with CADe-assisted colonoscopy alone to detect colorectal neoplasias during colonoscopy in a multicenter randomized trial. METHODS: Men and women undergoing colonoscopy for colorectal cancer screening, polyp surveillance, or clincial indications at 6 centers in Italy and Switzerland were enrolled. Patients were assigned (1:1) to colonoscopy with the combinations of CADe (GI-Genius; Medtronic) and a mucosal exposure device (Endocuff Vision [ECV]; Olympus) or to CADe-assisted colonoscopy alone (control group). All detected lesions were removed and sent to histopathology for diagnosis. The primary outcome was adenoma detection rate (percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy, advanced adenomas and serrated lesions detection rate, the rate of unnecessary polypectomies (polyp resection without histologically proven adenomas), and withdrawal time. RESULTS: From July 1, 2021 to May 31, 2022, there were 1316 subjects randomized and eligible for analysis; 660 to the ECV group, 656 to the control group). The adenoma detection rate was significantly higher in the ECV group (49.6%) than in the control group (44.0%) (relative risk, 1.12; 95% CI, 1.00-1.26; P = .04). Adenomas detected per colonoscopy were significantly higher in the ECV group (mean ± SD, 0.94 ± 0.54) than in the control group (0.74 ± 0.21) (incidence rate ratio, 1.26; 95% CI, 1.04-1.54; P = .02). The 2 groups did not differ in term of detection of advanced adenomas and serrated lesions. There was no significant difference between groups in mean ± SD withdrawal time (9.01 ± 2.48 seconds for the ECV group vs 8.96 ± 2.24 seconds for controls; P = .69) or proportion of subjects undergoing unnecessary polypectomies (relative risk, 0.89; 95% CI, 0.69-1.14; P = .38). CONCLUSIONS: The combination of CADe and ECV during colonoscopy increases adenoma detection rate and adenomas detected per colonoscopy without increasing withdrawal time compared with CADe alone. CLINICALTRIALS: gov, Number: NCT04676308.

Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and reliability need to be rigorously assessed. In this article, we provide a guiding framework for all stakeholders in the endoscopy AI ecosystem regarding the standards, metrics, and evaluation methods for emerging and existing AI applications to aid in their clinical adoption and implementation. We also provide guidance and best practices for evaluation of AI technologies as they mature in the endoscopy space. Note, this is a living document; periodic updates will be published as progress is made and applications evolve in the field of AI in endoscopy.

Impact of comprehensive family history and genetic analysis in the multidisciplinary pancreatic tumor clinic setting.

BACKGROUND: Genetic testing is recommended for all pancreatic ductal adenocarcinoma (PDAC) patients. Prior research demonstrates that multidisciplinary pancreatic cancer clinics (MDPCs) improve treatment- and survival-related outcomes for PDAC patients. However, limited information exists regarding the utility of integrated genetics in the MDPC setting. We hypothesized that incorporating genetics in an MDPC serving both PDAC patients and high-risk individuals (HRI) could: (1) improve compliance with guideline-based genetic testing for PDAC patients, and (2) optimize HRI identification and PDAC surveillance participation to improve early detection and survival. METHODS: Demographics, genetic testing results, and pedigrees were reviewed for PDAC patients and HRI at one institution over 45 months. Genetic testing analyzed 16 PDAC-associated genes at minimum. RESULTS: Overall, 969 MDPC subjects were evaluated during the study period; another 56 PDAC patients were seen outside the MDPC. Among 425 MDPC PDAC patients, 333 (78.4%) completed genetic testing; 29 (8.7%) carried a PDAC-related pathogenic germline variant (PGV). Additionally, 32 (9.6%) met familial pancreatic cancer (FPC) criteria. These PDAC patients had 191 relatives eligible for surveillance or genetic testing. Only 2/56 (3.6%) non-MDPC PDAC patients completed genetic testing (p < 0.01). Among 544 HRI, 253 (46.5%) had a known PGV or a designation of FPC, and were eligible for surveillance at baseline; of the remainder, 15/291 (5.2%) were eligible following genetic testing and PGV identification. CONCLUSION: Integrating genetics into the multidisciplinary setting significantly improved genetic testing compliance by reducing logistical barriers for PDAC patients, and clarified cancer risks for their relatives while conserving clinical resources. Overall, we identified 206 individuals newly eligible for surveillance or genetic testing (191 relatives of MDPC PDAC patients, and 15 HRI from this cohort), enabling continuity of care for PDAC patients and at-risk relatives in one clinic.

Impact of Artificial Intelligence on Colonoscopy Surveillance After Polyp Removal: A Pooled Analysis of Randomized Trials.

BACKGROUND AND AIMS: Artificial intelligence (AI) tools aimed at improving polyp detection have been shown to increase the adenoma detection rate during colonoscopy. However, it is unknown how increased polyp detection rates by AI affect the burden of patient surveillance after polyp removal. METHODS: We conducted a pooled analysis of 9 randomized controlled trials (5 in China, 2 in Italy, 1 in Japan, and 1 in the United States) comparing colonoscopy with or without AI detection aids. The primary outcome was the proportion of patients recommended to undergo intensive surveillance (ie, 3-year interval). We analyzed intervals for AI and non-AI colonoscopies for the U.S. and European recommendations separately. We estimated proportions by calculating relative risks using the Mantel-Haenszel method. RESULTS: A total of 5796 patients (51% male, mean 53 years of age) were included; 2894 underwent AI-assisted colonoscopy and 2902 non-AI colonoscopy. When following U.S. guidelines, the proportion of patients recommended intensive surveillance increased from 8.4% (95% CI, 7.4%-9.5%) in the non-AI group to 11.3% (95% CI, 10.2%-12.6%) in the AI group (absolute difference, 2.9% [95% CI, 1.4%-4.4%]; risk ratio, 1.35 [95% CI, 1.16-1.57]). When following European guidelines, it increased from 6.1% (95% CI, 5.3%-7.0%) to 7.4% (95% CI, 6.5%-8.4%) (absolute difference, 1.3% [95% CI, 0.01%-2.6%]; risk ratio, 1.22 [95% CI, 1.01-1.47]). CONCLUSIONS: The use of AI during colonoscopy increased the proportion of patients requiring intensive colonoscopy surveillance by approximately 35% in the United States and 20% in Europe (absolute increases of 2.9% and 1.3%, respectively). While this may contribute to improved cancer prevention, it significantly adds patient burden and healthcare costs.

Safe, efficient, and effective screening colonoscopy.

PURPOSE OF REVIEW: Colorectal cancer continues to be one of the most common causes of cancer-related death. Widespread dissemination of screening colonoscopy in the United States has led to a significant reduction in the incidence and mortality. Here we review current literature with an aim to highlight recent improvements in the safety, efficiency, and effectiveness of screening colonoscopy. RECENT FINDINGS: Colon capsule endoscopy is an emerging noninvasive method to capture images of colonic mucosa for select patients with appreciable sensitivity for polyp detection. Recent literature supports the use of the novel oral anticoagulant apixaban over other anticoagulants to reduce the risk of gastrointestinal bleeding related to colonoscopy. Cold snare polypectomy for smaller lesions and prophylactic clipping following resection of large polyps in the proximal colon may reduce the rate of delayed bleeding. Novel methods and devices for improving bowel preparation continue to emerge. Mechanical attachment devices and artificial intelligence represent recent innovations to improve polyp detection. SUMMARY: Clinicians should be aware of relevant data and literature that continue to improve the quality and safety of screening colonoscopy and incorporate these findings into their clinical practice.

Robotics in therapeutic endoscopy (with video).

Since its inception, endoscopy has evolved from a solely diagnostic procedure to an expanding therapeutic field within gastroenterology. The incorporation of robotics in gastroenterology initially addressed shortcomings of flexible endoscopes in natural orifice transluminal endoscopy. Developing therapeutic endoscopic robotic platforms now offer operators improved ergonomics, visualization, dexterity, precision, and control and the possibility of increasing proficiency and standardization of complex endoscopic procedures including endoscopic submucosal dissection, endoscopic full-thickness resection, and endoscopic suturing. The following review discusses the history, potential applications, and tools currently available and in development for robotics in therapeutic endoscopy.

Diagnostic yield of inpatient capsule endoscopy.

BACKGROUND: Capsule endoscopy (CE) provides a novel approach to evaluate obscure gastrointestinal bleeding. Yet CE is not routinely utilized in the inpatient setting for a variety of reasons. We sought to identify factors that predict complete CE and diagnostically meaningful CE, as well as assess the impact of inpatient CE on further hospital management.1 na d2 METHODS: We conducted a retrospective review of patients undergoing inpatient CE at a tertiary referral, academic center over a 3 year period. We analyzed data on patient demographics, medical history, endoscopic procedures, hospital course, and results of CE. The primary outcome was complete CE and the secondary outcome was positive findings of pathology on CE. RESULTS: 131 patients were included (56.5% were men 43.5% women, median age of 71.0 years). Overall, CE was complete in 77.1% of patients. Complete CE was not related to motility risk factors, gender, or administration modality. Patients with incomplete CE tended to be older, have lower BMI, and Caucasian, however results did not reach statistical significance (p = 0.06; p = 0.06; p = 0.08 respectively). Positive CE was noted in 73.3% of patients, with 35.1% of all patients having active bleeding. Positive CE was not associated with AVM risk factors or medication use. 28.0% of patients underwent subsequent hospital procedures, among which 67.6% identified the same pathology seen on CE. CONCLUSIONS: Contrary to previous studies, we found the majority of inpatient CEs were complete and positive for pathology. We found high rates of correlation between CE and subsequent procedures. The use of CE in the inpatient setting helps to guide the diagnosis and treatment of hospitalized patients with obscure gastrointestinal bleeding.

Diagnosis and Management of Cancer Risk in the Gastrointestinal Hamartomatous Polyposis Syndromes: Recommendations From the US Multi-Society Task Force on Colorectal Cancer.

The gastrointestinal hamartomatous polyposis syndromes are rare, autosomal dominant disorders associated with an increased risk of benign and malignant intestinal and extraintestinal tumors. They include Peutz-Jeghers syndrome, juvenile polyposis syndrome, the PTEN hamartoma tumor syndrome (including Cowden's syndrome and Bannayan-Riley-Ruvalcaba syndrome), and hereditary mixed polyposis syndrome. Diagnoses are based on clinical criteria and, in some cases, confirmed by demonstrating the presence of a germline pathogenic variant. The best understood hamartomatous polyposis syndrome is Peutz-Jeghers syndrome, caused by germline pathogenic variants in the STK11 gene. The management is focused on prevention of bleeding and mechanical obstruction of the small bowel by polyps and surveillance of organs at increased risk for cancer. Juvenile polyposis syndrome is caused by a germline pathogenic variant in either the SMAD4 or BMPR1A genes, with differing clinical courses. Patients with SMAD4 pathogenic variants may have massive gastric polyposis, which can result in gastrointestinal bleeding and/or protein-losing gastropathy. Patients with SMAD4 mutations usually have the simultaneous occurrence of hereditary hemorrhagic telangiectasia (juvenile polyposis syndrome-hereditary hemorrhagic telangiectasia overlap syndrome) that can result in epistaxis, gastrointestinal bleeding from mucocutaneous telangiectasias, and arteriovenous malformations. Germline pathogenic variants in the PTEN gene cause overlapping clinical phenotypes (known as the PTEN hamartoma tumor syndromes), including Cowden's syndrome and related disorders that are associated with an increased risk of gastrointestinal and colonic polyposis, colon cancer, and other extraintestinal manifestations and cancers. Due to the relative rarity of the hamartomatous polyposis syndromes, recommendations for management are based on few studies. This US Multi-Society Task Force on Colorectal Cancer consensus statement summarizes the clinical features, assesses the current literature, and provides guidance for diagnosis, assessment, and management of patients with the hamartomatous polyposis syndromes, with a focus on endoscopic management.

Diagnosis and management of cancer risk in the gastrointestinal hamartomatous polyposis syndromes: recommendations from the U.S. Multi-Society Task Force on Colorectal Cancer.

The gastrointestinal hamartomatous polyposis syndromes are rare, autosomal dominant disorders associated with an increased risk of benign and malignant intestinal and extraintestinal tumors. They include Peutz-Jeghers syndrome, juvenile polyposis syndrome, the PTEN hamartoma tumor syndrome (including Cowden's syndrome and Bannayan-Riley-Ruvalcaba syndrome), and hereditary mixed polyposis syndrome. Diagnoses are based on clinical criteria and, in some cases, confirmed by demonstrating the presence of a germline pathogenic variant. The best understood hamartomatous polyposis syndrome is Peutz-Jeghers syndrome, caused by germline pathogenic variants in the STK11 gene. The management is focused on prevention of bleeding and mechanical obstruction of the small bowel by polyps and surveillance of organs at increased risk for cancer. Juvenile polyposis syndrome is caused by a germline pathogenic variant in either the SMAD4 or BMPR1A genes, with differing clinical courses. Patients with SMAD4 pathogenic variants may have massive gastric polyposis, which can result in gastrointestinal bleeding and/or protein-losing gastropathy. Patients with SMAD4 mutations usually have the simultaneous occurrence of hereditary hemorrhagic telangiectasia (juvenile polyposis syndrome-hereditary hemorrhagic telangiectasia overlap syndrome) that can result in epistaxis, gastrointestinal bleeding from mucocutaneous telangiectasias, and arteriovenous malformations. Germline pathogenic variants in the PTEN gene cause overlapping clinical phenotypes (known as the PTEN hamartoma tumor syndromes), including Cowden's syndrome and related disorders that are associated with an increased risk of gastrointestinal and colonic polyposis, colon cancer, and other extraintestinal manifestations and cancers. Due to the relative rarity of the hamartomatous polyposis syndromes, recommendations for management are based on few studies. This U.S. Multi-Society Task Force on Colorectal Cancer consensus statement summarizes the clinical features, assesses the current literature, and provides guidance for diagnosis, assessment, and management of patients with the hamartomatous polyposis syndromes, with a focus on endoscopic management.

Diagnosis and Management of Cancer Risk in the Gastrointestinal Hamartomatous Polyposis Syndromes: Recommendations From the US Multi-Society Task Force on Colorectal Cancer.

The gastrointestinal hamartomatous polyposis syndromes are rare, autosomal dominant disorders associated with an increased risk of benign and malignant intestinal and extraintestinal tumors. They include Peutz-Jeghers syndrome, juvenile polyposis syndrome, the PTEN hamartoma tumor syndrome (including Cowden's syndrome and Bannayan-Riley-Ruvalcaba syndrome), and hereditary mixed polyposis syndrome. Diagnoses are based on clinical criteria and, in some cases, confirmed by demonstrating the presence of a germline pathogenic variant. The best understood hamartomatous polyposis syndrome is Peutz-Jeghers syndrome, caused by germline pathogenic variants in the STK11 gene. The management is focused on prevention of bleeding and mechanical obstruction of the small bowel by polyps and surveillance of organs at increased risk for cancer. Juvenile polyposis syndrome is caused by a germline pathogenic variant in either the SMAD4 or BMPR1A genes, with differing clinical courses. Patients with SMAD4 pathogenic variants may have massive gastric polyposis, which can result in gastrointestinal bleeding and/or protein-losing gastropathy. Patients with SMAD4 mutations usually have the simultaneous occurrence of hereditary hemorrhagic telangiectasia (juvenile polyposis syndrome-hereditary hemorrhagic telangiectasia overlap syndrome) that can result in epistaxis, gastrointestinal bleeding from mucocutaneous telangiectasias, and arteriovenous malformations. Germline pathogenic variants in the PTEN gene cause overlapping clinical phenotypes (known as the PTEN hamartoma tumor syndromes), including Cowden's syndrome and related disorders that are associated with an increased risk of gastrointestinal and colonic polyposis, colon cancer, and other extraintestinal manifestations and cancers. Due to the relative rarity of the hamartomatous polyposis syndromes, recommendations for management are based on few studies. This U.S Multi-Society Task Force on Colorectal Cancer consensus statement summarizes the clinical features, assesses the current literature, and provides guidance for diagnosis, assessment, and management of patients with the hamartomatous polyposis syndromes, with a focus on endoscopic management.