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Introzzi L, Zonca J, Cabitza F, Cherubini P, Reverberi C. Enhancing human-AI collaboration: The case of colonoscopy. Dig Liver Dis 2024; 56:1131-1139. [PMID: 37940501 DOI: 10.1016/j.dld.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 11/10/2023]
Abstract
Diagnostic errors impact patient health and healthcare costs. Artificial Intelligence (AI) shows promise in mitigating this burden by supporting Medical Doctors in decision-making. However, the mere display of excellent or even superhuman performance by AI in specific tasks does not guarantee a positive impact on medical practice. Effective AI assistance should target the primary causes of human errors and foster effective collaborative decision-making with human experts who remain the ultimate decision-makers. In this narrative review, we apply these principles to the specific scenario of AI assistance during colonoscopy. By unraveling the neurocognitive foundations of the colonoscopy procedure, we identify multiple bottlenecks in perception, attention, and decision-making that contribute to diagnostic errors, shedding light on potential interventions to mitigate them. Furthermore, we explored how existing AI devices fare in clinical practice and whether they achieved an optimal integration with the human decision-maker. We argue that to foster optimal Human-AI collaboration, future research should expand our knowledge of factors influencing AI's impact, establish evidence-based cognitive models, and develop training programs based on them. These efforts will enhance human-AI collaboration, ultimately improving diagnostic accuracy and patient outcomes. The principles illuminated in this review hold more general value, extending their relevance to a wide array of medical procedures and beyond.
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Affiliation(s)
- Luca Introzzi
- Department of Psychology, Università Milano - Bicocca, Milano, Italy
| | - Joshua Zonca
- Department of Psychology, Università Milano - Bicocca, Milano, Italy; Milan Center for Neuroscience, Università Milano - Bicocca, Milano, Italy
| | - Federico Cabitza
- Department of Informatics, Systems and Communication, Università Milano - Bicocca, Milano, Italy; IRCCS Istituto Ortopedico Galeazzi, Milano, Italy
| | - Paolo Cherubini
- Department of Brain and Behavioral Sciences, Università Statale di Pavia, Pavia, Italy
| | - Carlo Reverberi
- Department of Psychology, Università Milano - Bicocca, Milano, Italy; Milan Center for Neuroscience, Università Milano - Bicocca, Milano, Italy.
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Spadaccini M, Troya J, Khalaf K, Facciorusso A, Maselli R, Hann A, Repici A. Artificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going? Dig Liver Dis 2024; 56:1148-1155. [PMID: 38458884 DOI: 10.1016/j.dld.2024.01.203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 01/22/2024] [Accepted: 01/23/2024] [Indexed: 03/10/2024]
Abstract
Colorectal cancer is a significant global health concern, necessitating effective screening strategies to reduce its incidence and mortality rates. Colonoscopy plays a crucial role in the detection and removal of colorectal neoplastic precursors. However, there are limitations and variations in the performance of endoscopists, leading to missed lesions and suboptimal outcomes. The emergence of artificial intelligence (AI) in endoscopy offers promising opportunities to improve the quality and efficacy of screening colonoscopies. In particular, AI applications, including computer-aided detection (CADe) and computer-aided characterization (CADx), have demonstrated the potential to enhance adenoma detection and optical diagnosis accuracy. Additionally, AI-assisted quality control systems aim to standardize the endoscopic examination process. This narrative review provides an overview of AI principles and discusses the current knowledge on AI-assisted endoscopy in the context of screening colonoscopies. It highlights the significant role of AI in improving lesion detection, characterization, and quality assurance during colonoscopy. However, further well-designed studies are needed to validate the clinical impact and cost-effectiveness of AI-assisted colonoscopy before its widespread implementation.
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Affiliation(s)
- Marco Spadaccini
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy.
| | - Joel Troya
- Interventional and Experimental Endoscopy (InExEn), Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Kareem Khalaf
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | - Antonio Facciorusso
- Gastroenterology Unit, Department of Surgical and Medical Sciences, University of Foggia, Foggia, Italy
| | - Roberta Maselli
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
| | - Alexander Hann
- Interventional and Experimental Endoscopy (InExEn), Department of Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Alessandro Repici
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
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Maas MHJ, Rath T, Spada C, Soons E, Forbes N, Kashin S, Cesaro P, Eickhoff A, Vanbiervliet G, Salvi D, Belletrutti PJ, Siersema PD. A computer-aided detection system in the everyday setting of diagnostic, screening, and surveillance colonoscopy: an international, randomized trial. Endoscopy 2024. [PMID: 38749482 DOI: 10.1055/a-2328-2844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/29/2024]
Abstract
BACKGROUND Computer-aided detection (CADe) has been developed to improve detection during colonoscopy. After initial reports of high efficacy, there has been an increasing recognition of variability in the effectiveness of CADe systems. The aim of this study was to evaluate a CADe system in a varied colonoscopy population. METHODS A multicenter, randomized trial was conducted at seven hospitals (both university and non-university) in Europe and Canada. Participants referred for diagnostic, non-immunochemical fecal occult blood test (iFOBT) screening, or surveillance colonoscopy were randomized (1:1) to undergo CADe-assisted or conventional colonoscopy by experienced endoscopists. Participants with insufficient bowel preparation were excluded from the analysis. The primary outcome was adenoma detection rate (ADR). Secondary outcomes included adenomas per colonoscopy (APC) and sessile serrated lesions (SSLs) per colonoscopy. RESULTS 581 participants were enrolled, of whom 497 were included in the final analysis: 250 in the CADe arm and 247 in the conventional colonoscopy arm. The indication was surveillance in 202/497 colonoscopies (40.6 %), diagnostic in 199/497 (40.0 %), and non-iFOBT screening in 96/497 (19.3 %). Overall, ADR (38.4 % vs. 37.7 %; P = 0.43) and APC (0.66 vs. 0.66; P = 0.97) were similar between CADe and conventional colonoscopy. SSLs per colonoscopy was increased (0.30 vs. 0.19; P = 0.049) in the CADe arm vs. the conventional colonoscopy arm. CONCLUSIONS In this study conducted by experienced endoscopists, CADe did not result in a statistically significant increase in ADR. However, the ADR of our control group substantially surpassed our sample size assumptions, increasing the risk of an underpowered trial.
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Affiliation(s)
- Michiel H J Maas
- Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Timo Rath
- Department of Medicine I, Division of Gastroenterology, Universitätsklinikum Erlangen, Erlangen, Germany
| | - Cristiano Spada
- Department of Gastroenterology and Endoscopy, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy
- Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | - Elsa Soons
- Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Nauzer Forbes
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Sergey Kashin
- Department of Endoscopy, Yaroslavl Regional Cancer Hospital, Yaroslavl, Russia
| | - Paola Cesaro
- Department of Gastroenterology and Endoscopy, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy
| | - Axel Eickhoff
- Gastroenterology, Diabetology, Infectiology, Klinikum Hanau, Hanau, Germany
| | | | - Daniele Salvi
- Department of Gastroenterology and Endoscopy, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy
- Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | | | - Peter D Siersema
- Gastroenterology and Hepatology, Radboud University Medical Center, Nijmegen, the Netherlands
- ErasmusMC - University Medical Center, Rotterdam, the Netherlands
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Chow KW, Bell MT, Cumpian N, Amour M, Hsu RH, Eysselein VE, Srivastava N, Fleischman MW, Reicher S. Long-term impact of artificial intelligence on colorectal adenoma detection in high-risk colonoscopy. World J Gastrointest Endosc 2024; 16:335-342. [DOI: 10.4253/wjge.v16.i6.335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/16/2024] [Accepted: 04/28/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Improved adenoma detection rate (ADR) has been demonstrated with artificial intelligence (AI)-assisted colonoscopy. However, data on the real-world application of AI and its effect on colorectal cancer (CRC) screening outcomes is limited.
AIM To analyze the long-term impact of AI on a diverse at-risk patient population undergoing diagnostic colonoscopy for positive CRC screening tests or symptoms.
METHODS AI software (GI Genius, Medtronic) was implemented into the standard procedure protocol in November 2022. Data was collected on patient demographics, procedure indication, polyp size, location, and pathology. CRC screening outcomes were evaluated before and at different intervals after AI introduction with one year of follow-up.
RESULTS We evaluated 1008 colonoscopies (278 pre-AI, 255 early post-AI, 285 established post-AI, and 190 late post-AI). The ADR was 38.1% pre-AI, 42.0% early post-AI (P = 0.77), 40.0% established post-AI (P = 0.44), and 39.5% late post-AI (P = 0.77). There were no significant differences in polyp detection rate (PDR, baseline 59.7%), advanced ADR (baseline 16.2%), and non-neoplastic PDR (baseline 30.0%) before and after AI introduction.
CONCLUSION In patients with an increased pre-test probability of having an abnormal colonoscopy, the current generation of AI did not yield enhanced CRC screening metrics over high-quality colonoscopy. Although the potential of AI in colonoscopy is undisputed, current AI technology may not universally elevate screening metrics across all situations and patient populations. Future studies that analyze different AI systems across various patient populations are needed to determine the most effective role of AI in optimizing CRC screening in clinical practice.
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Affiliation(s)
- Kenneth W Chow
- Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Matthew T Bell
- Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Nicholas Cumpian
- Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Maryanne Amour
- Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Ryan H Hsu
- Department of Bioengineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA 92093, United States
| | - Viktor E Eysselein
- Department of Gastroenterology, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Neetika Srivastava
- Department of Gastroenterology, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Michael W Fleischman
- Department of Gastroenterology, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
| | - Sofiya Reicher
- Department of Gastroenterology, Harbor-UCLA Medical Center, Torrance, CA 90502, United States
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Zhang C, Yao L, Jiang R, Wang J, Wu H, Li X, Wu Z, Luo R, Luo C, Tan X, Wang W, Xiao B, Hu H, Yu H. Assessment of the role of false-positive alerts in computer-aided polyp detection for assistance capabilities. J Gastroenterol Hepatol 2024. [PMID: 38744667 DOI: 10.1111/jgh.16615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/24/2024] [Accepted: 05/02/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND AND AIM False positives (FPs) pose a significant challenge in the application of artificial intelligence (AI) for polyp detection during colonoscopy. The study aimed to quantitatively evaluate the impact of computer-aided polyp detection (CADe) systems' FPs on endoscopists. METHODS The model's FPs were categorized into four gradients: 0-5, 5-10, 10-15, and 15-20 FPs per minute (FPPM). Fifty-six colonoscopy videos were collected for a crossover study involving 10 endoscopists. Polyp missed rate (PMR) was set as primary outcome. Subsequently, to further verify the impact of FPPM on the assistance capability of AI in clinical environments, a secondary analysis was conducted on a prospective randomized controlled trial (RCT) from Renmin Hospital of Wuhan University in China from July 1 to October 15, 2020, with the adenoma detection rate (ADR) as primary outcome. RESULTS Compared with routine group, CADe reduced PMR when FPPM was less than 5. However, with the continuous increase of FPPM, the beneficial effect of CADe gradually weakens. For secondary analysis of RCT, a total of 956 patients were enrolled. In AI-assisted group, ADR is higher when FPPM ≤ 5 compared with FPPM > 5 (CADe group: 27.78% vs 11.90%; P = 0.014; odds ratio [OR], 0.351; 95% confidence interval [CI], 0.152-0.812; COMBO group: 38.40% vs 23.46%, P = 0.029; OR, 0.427; 95% CI, 0.199-0.916). After AI intervention, ADR increased when FPPM ≤ 5 (27.78% vs 14.76%; P = 0.001; OR, 0.399; 95% CI, 0.231-0.690), but no statistically significant difference was found when FPPM > 5 (11.90% vs 14.76%, P = 0.788; OR, 1.111; 95% CI, 0.514-2.403). CONCLUSION The level of FPs of CADe does affect its effectiveness as an aid to endoscopists, with its best effect when FPPM is less than 5.
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Affiliation(s)
- Chenxia Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Liwen Yao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Ruiqing Jiang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Jing Wang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Huiling Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Xun Li
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Zhifeng Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Renquan Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Chaijie Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Xia Tan
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Wen Wang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Bing Xiao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Huiyan Hu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Engineering Research Center for Artificial lntelligence Endoscopy Interventional Treatment of Hubei Province, Wuhan, China
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Mascagni P, Alapatt D, Sestini L, Yu T, Alfieri S, Morales-Conde S, Padoy N, Perretta S. Applications of artificial intelligence in surgery: clinical, technical, and governance considerations. Cir Esp 2024:S2173-5077(24)00114-5. [PMID: 38704146 DOI: 10.1016/j.cireng.2024.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/06/2024]
Abstract
Artificial intelligence (AI) will power many of the tools in the armamentarium of digital surgeons. AI methods and surgical proof-of-concept flourish, but we have yet to witness clinical translation and value. Here we exemplify the potential of AI in the care pathway of colorectal cancer patients and discuss clinical, technical, and governance considerations of major importance for the safe translation of surgical AI for the benefit of our patients and practices.
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Affiliation(s)
- Pietro Mascagni
- IHU Strasbourg, Strasbourg, France; Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy; Università Cattolica del Sacro Cuore, Rome, Italy.
| | - Deepak Alapatt
- University of Strasbourg, CNRS, INSERM, ICube, UMR7357, Strasbourg, France
| | - Luca Sestini
- University of Strasbourg, CNRS, INSERM, ICube, UMR7357, Strasbourg, France
| | - Tong Yu
- University of Strasbourg, CNRS, INSERM, ICube, UMR7357, Strasbourg, France
| | - Sergio Alfieri
- Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy; Università Cattolica del Sacro Cuore, Rome, Italy
| | | | - Nicolas Padoy
- IHU Strasbourg, Strasbourg, France; University of Strasbourg, CNRS, INSERM, ICube, UMR7357, Strasbourg, France
| | - Silvana Perretta
- IHU Strasbourg, Strasbourg, France; IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France; Nouvel Hôpital Civil, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
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Savino A, Rondonotti E, Rocchetto S, Piagnani A, Bina N, Di Domenico P, Segatta F, Radaelli F. GI genius endoscopy module: a clinical profile. Expert Rev Med Devices 2024; 21:359-372. [PMID: 38618982 DOI: 10.1080/17434440.2024.2342508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 04/09/2024] [Indexed: 04/16/2024]
Abstract
INTRODUCTION The identification of early-stage colorectal cancers (CRC) and the resection of pre-cancerous neoplastic lesions through colonoscopy allows to decrease both CRC incidence and mortality. However, colonoscopy miss rates up to 26% for adenomas and 9% for advanced adenomas have been reported. In recent years, artificial intelligence (AI) systems have been emerging as easy-to-use tools, potentially lowering the risk of missing lesions. AREAS COVERED This review paper focuses on GI Genius device (Medtronic Co. Minneapolis, MN, U.S.A.) a computer-assisted tool designed to assist endoscopists during standard white-light colonoscopies in detecting mucosal lesions. EXPERT OPINION Randomized controlled trials (RCTs) suggest that GI Genius is a safe and effective tool for improving adenoma detection, especially in CRC screening and surveillance colonoscopies. However, its impact seems to be less significant among experienced endoscopists and in real-world clinical scenarios compared to the controlled conditions of RCTs. Furthermore, it appears that GI Genius mainly enhances the detection of non-advanced, small polyps, but does not significantly impact the identification of advanced and difficult-to-detect adenoma. When using GI Genius, no complications were documented. Only a small number of studies reported an increased in withdrawal time or the removal of non-neoplastic lesions.
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Affiliation(s)
- Alberto Savino
- Division of Gastroenterology, Department of Medicine and Surgery, University of Milano-Bicocca, Milano, Italy
| | | | - Simone Rocchetto
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Gastroenterology and Hepatology, University of Milan, Milan, Italy
| | - Alessandra Piagnani
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Gastroenterology and Hepatology, University of Milan, Milan, Italy
| | - Niccolò Bina
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | - Pasquale Di Domenico
- Gastrointestinal Unit, Department of Medicine, Surgery & Dentistry Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Francesco Segatta
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- Foundation IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Gastroenterology and Hepatology, University of Milan, Milan, Italy
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Patel HK, Mori Y, Hassan C, Rizkala T, Radadiya DK, Nathani P, Srinivasan S, Misawa M, Maselli R, Antonelli G, Spadaccini M, Facciorusso A, Khalaf K, Lanza D, Bonanno G, Rex DK, Repici A, Sharma P. Lack of Effectiveness of Computer Aided Detection for Colorectal Neoplasia: A Systematic Review and Meta-Analysis of Nonrandomized Studies. Clin Gastroenterol Hepatol 2024; 22:971-980.e15. [PMID: 38056803 DOI: 10.1016/j.cgh.2023.11.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/19/2023] [Accepted: 11/22/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND AND AIMS Benefits of computer-aided detection (CADe) in detecting colorectal neoplasia were shown in many randomized trials in which endoscopists' behavior was strictly controlled. However, the effect of CADe on endoscopists' performance in less-controlled setting is unclear. This systematic review and meta-analyses were aimed at clarifying benefits and harms of using CADe in real-world colonoscopy. METHODS We searched MEDLINE, EMBASE, Cochrane, and Google Scholar from inception to August 20, 2023. We included nonrandomized studies that compared the effectiveness between CADe-assisted and standard colonoscopy. Two investigators independently extracted study data and quality. Pairwise meta-analysis was performed utilizing risk ratio for dichotomous variables and mean difference (MD) for continuous variables with a 95% confidence interval (CI). RESULTS Eight studies were included, comprising 9782 patients (4569 with CADe and 5213 without CADe). Regarding benefits, there was a difference in neither adenoma detection rate (44% vs 38%; risk ratio, 1.11; 95% CI, 0.97 to 1.28) nor mean adenomas per colonoscopy (0.93 vs 0.79; MD, 0.14; 95% CI, -0.04 to 0.32) between CADe-assisted and standard colonoscopy, respectively. Regarding harms, there was no difference in the mean non-neoplastic lesions per colonoscopy (8 studies included for analysis; 0.52 vs 0.47; MD, 0.14; 95% CI, -0.07 to 0.34) and withdrawal time (6 studies included for analysis; 14.3 vs 13.4 minutes; MD, 0.8 minutes; 95% CI, -0.18 to 1.90). There was a substantial heterogeneity, and all outcomes were graded with a very low certainty of evidence. CONCLUSION CADe in colonoscopies neither improves the detection of colorectal neoplasia nor increases burden of colonoscopy in real-world, nonrandomized studies, questioning the generalizability of the results of randomized trials.
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Affiliation(s)
- Harsh K Patel
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, Missouri
| | - Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway; Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy.
| | - Tommy Rizkala
- Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy
| | - Dhruvil K Radadiya
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, Missouri
| | - Piyush Nathani
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, Missouri
| | - Sachin Srinivasan
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, Missouri
| | - Masashi Misawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
| | - Roberta Maselli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy
| | - Giulio Antonelli
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli, Ariccia, Italy; Department of Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Rome, Italy
| | - Marco Spadaccini
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy
| | - Antonio Facciorusso
- Section of Gastroenterology, Department of Medical Sciences, University of Foggia, Foggia, Italy
| | - Kareem Khalaf
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Davide Lanza
- Gastroenterology and Hepatology, Clinica Moncucco, Lugano, Switzerland
| | - Giacomo Bonanno
- Endoscopy Unit, Humanitas Istituto Clinico Catanese, Catania, Italy
| | - Douglas K Rex
- Division of Gastroenterology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Italy
| | - Prateek Sharma
- Division of Gastroenterology, Indiana University School of Medicine, Indianapolis, Indiana; Gastroenterology and Hepatology, Kansas City VA Medical Center and University of Kansas School of Medicine, Kansas City, Missouri
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9
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Tiankanon K, Aniwan S, Kerr SJ, Mekritthikrai K, Kongtab N, Wisedopas N, Piyachaturawat P, Kulpatcharapong S, Linlawan S, Phromnil P, Muangpaisarn P, Orprayoon T, Chanyaswad J, Sunthornwechapong P, Vateekul P, Kullavanijaya P, Rerknimitr R. Improvement of adenoma detection rate by two computer-aided colonic polyp detection systems in high adenoma detectors: a randomized multicenter trial. Endoscopy 2024; 56:273-282. [PMID: 37963587 DOI: 10.1055/a-2210-7999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
BACKGROUND This study aimed to evaluate the benefits of a self-developed computer-aided polyp detection system (SD-CADe) and a commercial system (CM-CADe) for high adenoma detectors compared with white-light endoscopy (WLE) as a control. METHODS Average-risk 50-75-year-old individuals who underwent screening colonoscopy at five referral centers were randomized to SD-CADe, CM-CADe, or WLE groups (1:1:1 ratio). Trainees and staff with an adenoma detection rate (ADR) of ≥35% were recruited. The primary outcome was ADR. Secondary outcomes were the proximal adenoma detection rate (pADR), advanced adenoma detection rate (AADR), and the number of adenomas, proximal adenomas, and advanced adenomas per colonoscopy (APC, pAPC, and AAPC, respectively). RESULTS The study enrolled 1200 participants. The ADR in the control, CM-CADe, and SD-CADe groups was 38.3%, 50.0%, and 54.8%, respectively. The pADR was 23.0%, 32.3%, and 38.8%, respectively. AADR was 6.0%, 10.3%, and 9.5%, respectively. After adjustment, the ADR and pADR in both intervention groups were significantly higher than in controls (all P<0.05). The APC in the control, CM-CADe, and SD-CADe groups was 0.66, 1.04, and 1.16, respectively. The pAPC was 0.33, 0.53, and 0.64, respectively, and the AAPC was 0.07, 0.12, and 0.10, respectively. Both CADe systems showed significantly higher APC and pAPC than WLE. AADR and AAPC were improved in both CADe groups versus control, although the differences were not statistically significant. CONCLUSION Even in high adenoma detectors, CADe significantly improved ADR and APC. The AADR tended to be higher with both systems, and this may enhance colorectal cancer prevention.
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Affiliation(s)
- Kasenee Tiankanon
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Satimai Aniwan
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Stephen J Kerr
- Biostatistics Excellence Center, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- The Kirby Institute, University of New South Wales, Sydney, Australia
| | - Krittaya Mekritthikrai
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Natanong Kongtab
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Naruemon Wisedopas
- Department of Pathology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | | | | | | | - Poonrada Phromnil
- Department of Medicine, Khlong Khlung Hospital, Kamphaeng Phet, Thailand
| | - Puth Muangpaisarn
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Prapokklao Hospital, Chanthaburi, Thailand
| | - Theerapat Orprayoon
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Prapokklao Hospital, Chanthaburi, Thailand
| | - Jaruwan Chanyaswad
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Prapokklao Hospital, Chanthaburi, Thailand
| | | | - Peerapon Vateekul
- Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
| | - Pinit Kullavanijaya
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Rungsun Rerknimitr
- Division of Gastroenterology, Chulalongkorn University, Bangkok, Thailand
- Gastrointestinal Endoscopy Excellence Center, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
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10
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Khan R, Ruan Y, Yuan Y, Khalaf K, Sabrie NS, Gimpaya N, Scaffidi MA, Bansal R, Vaska M, Brenner DR, Hilsden RJ, Heitman SJ, Leontiadis GI, Grover SC, Forbes N. Relative Efficacies of Interventions to Improve the Quality of Screening-Related Colonoscopy: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials. Gastroenterology 2024:S0016-5085(24)00301-9. [PMID: 38513744 DOI: 10.1053/j.gastro.2024.03.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 03/11/2024] [Accepted: 03/12/2024] [Indexed: 03/23/2024]
Abstract
BACKGROUND & AIMS Significant variability exists in colonoscopy quality indicators, including adenoma detection rate (ADR). We synthesized evidence from randomized trials in a network meta-analysis on interventions to improve colonoscopy quality. METHODS We included trials from database inceptions to September 25, 2023, of patients undergoing screening-related colonoscopy and presented efficacies of interventions within domains (periprocedural parameters, endoscopist-directed interventions, intraprocedural techniques, endoscopic technologies, distal attachment devices, and additive substances) compared to standard colonoscopy. The primary outcome was ADR. We used a Bayesian random-effects model using Markov-chain Monte Carlo simulation, with 10,000 burn-ins and 100,000 iterations. We calculated odds ratios with 95% credible intervals and present surface under the cumulative ranking (SUCRA) curves. RESULTS We included 124 trials evaluating 37 interventions for the primary outcome. Nine interventions resulted in statistically significant improvements in ADR compared to standard colonoscopy (9-minute withdrawal time, dual observation, water exchange, i-SCAN [Pentax Ltd], linked color imaging, computer-aided detection, Endocuff [Olympus Corp], Endocuff Vision [Olympus Corp], and oral methylene blue). Dual observation (SUCRA, 0.84) and water exchange (SUCRA, 0.78) ranked highest among intraprocedural techniques; i-SCAN (SUCRA, 0.95), linked color imaging (SUCRA, 0.85), and computer-aided detection (SUCRA, 0.78) among endoscopic technologies; WingCap (A&A Medical Supply LLC) (SUCRA, 0.87) and Endocuff (SUCRA, 0.85) among distal attachment devices and oral methylene blue (SUCRA, 0.94) among additive substances. No interventions improved detection of advanced adenomas, and only narrow-band imaging improved detection of serrated lesions (odds ratio, 2.94; 95% credible interval, 1.46-6.25). CONCLUSIONS Several interventions are effective in improving adenoma detection and overall colonoscopy quality, many of which are cost-free. These results can inform endoscopists, unit managers, and endoscopy societies on relative efficacies.
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Affiliation(s)
- Rishad Khan
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Yibing Ruan
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Cancer Epidemiology and Prevention Research, Cancer Control Alberta, Alberta Health Services, Calgary, Alberta, Canada
| | - Yuhong Yuan
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada; Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Kareem Khalaf
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nasruddin S Sabrie
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Nikko Gimpaya
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Michael A Scaffidi
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada; Faculty of Health Sciences, School of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Rishi Bansal
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Marcus Vaska
- Knowledge Resource Service, Alberta Health Services, Calgary, Alberta, Canada
| | - Darren R Brenner
- Department of Oncology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Department of Cancer Epidemiology and Prevention Research, Cancer Control Alberta, Alberta Health Services, Calgary, Alberta, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Robert J Hilsden
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Division of Gastroenterology and Hepatology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Steven J Heitman
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Division of Gastroenterology and Hepatology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Grigorios I Leontiadis
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada; Farncombe Family Digestive Health Research Institute, McMaster University, Hamilton, Ontario, Canada
| | - Samir C Grover
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada; Li Ka Shing Knowledge Institute, University of Toronto, Toronto, Ontario, Canada
| | - Nauzer Forbes
- Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; Division of Gastroenterology and Hepatology, Department of Medicine, University of Calgary, Calgary, Alberta, Canada.
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11
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Thiruvengadam NR, Solaimani P, Shrestha M, Buller S, Carson R, Reyes-Garcia B, Gnass RD, Wang B, Albasha N, Leonor P, Saumoy M, Coimbra R, Tabuenca A, Srikureja W, Serrao S. The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial. Clin Gastroenterol Hepatol 2024:S1542-3565(24)00225-8. [PMID: 38437999 DOI: 10.1016/j.cgh.2024.02.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/12/2024] [Accepted: 02/13/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND & AIMS The use of computer-aided detection (CADe) has increased the adenoma detection rates (ADRs) during colorectal cancer (CRC) screening/surveillance in randomized controlled trials (RCTs) but has not shown benefit in real-world implementation studies. We performed a single-center pragmatic RCT to evaluate the impact of real-time CADe on ADRs in colonoscopy performed by community gastroenterologists. METHODS We enrolled 1100 patients undergoing colonoscopy for CRC screening, surveillance, positive fecal-immunohistochemical tests, and diagnostic indications at one community-based center from September 2022 to March 2023. Patients were randomly assigned (1:1) to traditional colonoscopy or real-time CADe. Blinded pathologists analyzed histopathologic findings. The primary outcome was ADR (the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy (APC), sessile-serrated lesion detection rate, and non-neoplastic resection rate. RESULTS The median age was 55.5 years (interquartile range, 50-62 years), 61% were female, 72.7% were of Hispanic ethnicity, and 9.1% had inadequate bowel preparation. The ADR for the CADe group was significantly higher than the traditional colonoscopy group (42.5% vs 34.4%; P = .005). The mean APC was significantly higher in the CADe group compared with the traditional colonoscopy group (0.89 ± 1.46 vs 0.60 ± 1.12; P < .001). The improvement in adenoma detection was driven by increased detection of <5 mm adenomas. CADe had a higher sessile-serrated lesion detection rate than traditional colonoscopy (4.7% vs 2.0%; P = .01). The improvement in ADR with CADe was significantly higher in the first half of the study (47.2% vs 33.7%; P = .002) compared with the second half (38.7% vs 34.9%; P = .33). CONCLUSIONS In a single-center pragmatic RCT, real-time CADe modestly improved ADR and APC in average-detector community endoscopists. (ClinicalTrials.gov number, NCT05963724).
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Affiliation(s)
- Nikhil R Thiruvengadam
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California.
| | - Pejman Solaimani
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Manish Shrestha
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Seth Buller
- Loma Linda University School of Medicine, Loma Linda, California
| | - Rachel Carson
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Breanna Reyes-Garcia
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Ronaldo D Gnass
- Department of Pathology, Riverside University Health System, Moreno Valley, California
| | - Bing Wang
- Department of Pathology, Loma Linda University School of Medicine, Loma Linda, California
| | - Natalie Albasha
- University of California Riverside School of Medicine, Riverside, California; Department of Medicine, Scripps Green Hospital, La Jolla, California
| | - Paul Leonor
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Monica Saumoy
- Center for Digestive Health, Penn Medicine Princeton Medical Center, Plainsboro, New Jersey
| | - Raul Coimbra
- Comparative Effectiveness and Clinical Outcomes Research Center, Riverside University Health System, Moreno Valley, California; Department of Surgery, Riverside University Health System, Moreno Valley, California
| | - Arnold Tabuenca
- Department of Surgery, Riverside University Health System, Moreno Valley, California; Department of Surgery, University of California Riverside School of Medicine, Riverside, California
| | - Wichit Srikureja
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
| | - Steve Serrao
- Division of Gastroenterology and Hepatology, Riverside University Health System, Moreno Valley, California; Division of Gastroenterology and Hepatology, Loma Linda University Health, Loma Linda, California
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12
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Wei MT, Fay S, Yung D, Ladabaum U, Kopylov U. Artificial Intelligence-Assisted Colonoscopy in Real-World Clinical Practice: A Systematic Review and Meta-Analysis. Clin Transl Gastroenterol 2024; 15:e00671. [PMID: 38146871 PMCID: PMC10962886 DOI: 10.14309/ctg.0000000000000671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 11/29/2023] [Indexed: 12/27/2023] Open
Abstract
INTRODUCTION Artificial intelligence (AI) could minimize the operator-dependent variation in colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection rate (ADR) and adenomas per colonoscopy (APC) in randomized controlled trials. There is a need to assess the impact of CADe in real-world settings. METHODS We searched MEDLINE, EMBASE, and Web of Science for nonrandomized real-world studies of CADe in colonoscopy. Random-effects meta-analyses were performed to examine the effect of CADe on ADR and APC. The study is registered under PROSPERO (CRD42023424037). There was no funding for this study. RESULTS Twelve of 1,314 studies met inclusion criteria. Overall, ADR was statistically significantly higher with vs without CADe (36.3% vs 35.8%, risk ratio [RR] 1.13, 95% confidence interval [CI] 1.01-1.28). This difference remained significant in subgroup analyses evaluating 6 prospective (37.3% vs 35.2%, RR 1.15, 95% CI 1.01-1.32) but not 6 retrospective (35.7% vs 36.2%, RR 1.12, 95% CI 0.92-1.36) studies. Among 6 studies with APC data, APC rate ratio with vs without CADe was 1.12 (95% CI 0.95-1.33). In 4 studies with GI Genius (Medtronic), there was no difference in ADR with vs without CADe (RR 0.96, 95% CI 0.85-1.07). DISCUSSION ADR, but not APC, was slightly higher with vs without CADe among all available real-world studies. This difference was attributed to the results of prospective but not retrospective studies. The discrepancies between these findings and those of randomized controlled trials call for future research on the true impact of current AI technology on colonoscopy quality and the subtleties of human-AI interactions.
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Affiliation(s)
- Mike Tzuhen Wei
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
| | - Shmuel Fay
- Department of Gastroenterology, Sheba Medical Center, Ramat Gan, Israel
- Tel Aviv University Medical School, Tel Aviv, Israel
| | - Diana Yung
- Gold Coast Hospital and Health Service, Gold Coast, Australia.
| | - Uri Ladabaum
- Division of Gastroenterology and Hepatology, Stanford University School of Medicine, Stanford, California, USA
| | - Uri Kopylov
- Department of Gastroenterology, Sheba Medical Center, Ramat Gan, Israel
- Tel Aviv University Medical School, Tel Aviv, Israel
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13
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Maas MHJ, Neumann H, Shirin H, Katz LH, Benson AA, Kahloon A, Soons E, Hazzan R, Landsman MJ, Lebwohl B, Lewis SK, Sivanathan V, Ngamruengphong S, Jacob H, Siersema PD. A computer-aided polyp detection system in screening and surveillance colonoscopy: an international, multicentre, randomised, tandem trial. Lancet Digit Health 2024; 6:e157-e165. [PMID: 38395537 DOI: 10.1016/s2589-7500(23)00242-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 11/01/2023] [Accepted: 11/16/2023] [Indexed: 02/25/2024]
Abstract
BACKGROUND Studies on the effect of computer-aided detection (CAD) in a daily clinical screening and surveillance colonoscopy population practice are scarce. The aim of this study was to evaluate a novel CAD system in a screening and surveillance colonoscopy population. METHODS This multicentre, randomised, controlled trial was done in ten hospitals in Europe, the USA, and Israel by 31 endoscopists. Patients referred for non-immunochemical faecal occult blood test (iFOBT) screening or surveillance colonoscopy were included. Patients were randomomly assigned to CAD-assisted colonoscopy or conventional colonoscopy; a subset was further randomly assigned to undergo tandem colonoscopy: CAD followed by conventional colonoscopy or conventional colonoscopy followed by CAD. Primary objectives included adenoma per colonoscopy (APC) and adenoma per extraction (APE). Secondary objectives included adenoma miss rate (AMR) in the tandem colonoscopies. The study was registered at ClinicalTrials.gov, NCT04640792. FINDINGS A total of 916 patients were included in the modified intention-to-treat analysis: 449 in the CAD group and 467 in the conventional colonoscopy group. APC was higher with CAD compared with conventional colonoscopy (0·70 vs 0·51, p=0·015; 314 adenomas per 449 colonoscopies vs 238 adenomas per 467 colonoscopies; poisson effect ratio 1·372 [95% CI 1·068-1·769]), while showing non-inferiority of APE compared with conventional colonoscopy (0·59 vs 0·66; p<0·001 for non-inferiority; 314 of 536 extractions vs 238 of 360 extractions). AMR in the 127 (61 with CAD first, 66 with conventional colonoscopy first) patients completing tandem colonoscopy was 19% (11 of 59 detected during the second pass) in the CAD first group and 36% (16 of 45 detected during the second pass) in the conventional colonoscopy first group (p=0·024). INTERPRETATION CAD increased adenoma detection in non-iFOBT screening and surveillance colonoscopies and reduced adenoma miss rates compared with conventional colonoscopy, without an increase in the resection of non-adenomatous lesions. FUNDING Magentiq Eye.
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Affiliation(s)
- Michiel H J Maas
- Department of Gastroenterology & Hepatology, Radboud University Medical Center, Nijmegen, Netherlands.
| | - Helmut Neumann
- University Medical Center Mainz, Interventional Endoscopy Center, I Medizinische Klinik und Poliklinik, Mainz, Germany
| | - Haim Shirin
- Institute of Gastroenterology and Liver Diseases, Shamir (Assaf Harofeh) Medical Center, Zerifin, Israel
| | - Lior H Katz
- Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Institute of Gastroenterology and Liver Diseases, Jerusalem, Israel
| | - Ariel A Benson
- Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Institute of Gastroenterology and Liver Diseases, Jerusalem, Israel
| | - Arslan Kahloon
- College of Medicine, Division of Gastroenterology, University of Tennessee, Chattanooga, TN, USA
| | - Elsa Soons
- Department of Gastroenterology & Hepatology, Radboud University Medical Center, Nijmegen, Netherlands
| | - Rawi Hazzan
- Assuta Centers, Haifa Gastroenterology Institute, Haifa, Israel
| | - Marc J Landsman
- Department of Gastroenterology, MetroHealth Medical Center, Cleveland, OH, USA
| | - Benjamin Lebwohl
- Department of Gastroenterology, Columbia University Irving Medical Center, New York, NY, USA
| | - Suzanne K Lewis
- Department of Gastroenterology, Columbia University Irving Medical Center, New York, NY, USA
| | - Visvakanth Sivanathan
- University Medical Center Mainz, Interventional Endoscopy Center, I Medizinische Klinik und Poliklinik, Mainz, Germany
| | | | - Harold Jacob
- Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Institute of Gastroenterology and Liver Diseases, Jerusalem, Israel
| | - Peter D Siersema
- Department of Gastroenterology & Hepatology, Radboud University Medical Center, Nijmegen, Netherlands; Department of Gastroenterology & Hepatology, Erasmus MC, University Medical Center, Rotterdam, Netherlands
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14
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Shaukat A, Crockett SD. Colorectal Cancer Screening: Time to Spring Forward. Am J Gastroenterol 2024; 119:395-396. [PMID: 38857481 DOI: 10.14309/ajg.0000000000002713] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 06/12/2024]
Affiliation(s)
- Aasma Shaukat
- Division of Gastroenterology, NYU Grossman School of Medicine, New York, New York, USA; and
| | - Seth D Crockett
- Division of Gastroenterology and Hepatology, Oregon Health & Science University and Portland VA Medical Center, Portland, Oregon, USA
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15
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Schöler J, Alavanja M, de Lange T, Yamamoto S, Hedenström P, Varkey J. Impact of AI-aided colonoscopy in clinical practice: a prospective randomised controlled trial. BMJ Open Gastroenterol 2024; 11:e001247. [PMID: 38290758 PMCID: PMC10870789 DOI: 10.1136/bmjgast-2023-001247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/11/2024] [Indexed: 02/01/2024] Open
Abstract
OBJECTIVE Colorectal cancer (CRC) has a significant role in cancer-related mortality. Colonoscopy, combined with adenoma removal, has proven effective in reducing CRC incidence. However, suboptimal colonoscopy quality often leads to missed polyps. The impact of artificial intelligence (AI) on adenoma and polyp detection rate (ADR, PDR) is yet to be established. DESIGN We conducted a randomised controlled trial at Sahlgrenska University Hospital in Sweden. Patients underwent colonoscopy with or without the assistance of AI (AI-C or conventional colonoscopy (CC)). Examinations were performed with two different AI systems, that is, Fujifilm CADEye and Medtronic GI Genius. The primary outcome was ADR. RESULTS Among 286 patients, 240 underwent analysis (average age: 66 years). The ADR was 42% for all patients, and no significant difference emerged between AI-C and CC groups (41% vs 43%). The overall PDR was 61%, with a trend towards higher PDR in the AI-C group. Subgroup analysis revealed higher detection rates for sessile serrated lesions (SSL) with AI assistance (AI-C 22%, CC 11%, p=0.004). No difference was noticed in the detection of polyps or adenomas per colonoscopy. Examinations were most often performed by experienced endoscopists, 78% (n=86 AI-C, 100 CC). CONCLUSION Amidst the ongoing AI integration, ADR did not improve with AI. Particularly noteworthy is the enhanced detection rates for SSL by AI assistance, especially since they pose a risk for postcolonoscopy CRC. The integration of AI into standard colonoscopy practice warrants further investigation and the development of improved software might be necessary before enforcing its mandatory implementation. TRIAL REGISTRATION NUMBER NCT05178095.
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Affiliation(s)
- Johanna Schöler
- Medical Department, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Marko Alavanja
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Goteborg, Sweden
- Department of Medicine, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Thomas de Lange
- Medical Department, Sahlgrenska University Hospital, Goteborg, Sweden
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Goteborg, Sweden
| | - Shunsuke Yamamoto
- Department of Medicine, Sahlgrenska University Hospital, Goteborg, Sweden
- Department of Gastroenterology and Hepatology, National Hospital Organization Osaka National Hospital, Osaka, Japan
| | - Per Hedenström
- Medical Department, Sahlgrenska University Hospital, Goteborg, Sweden
- Department of Medicine, Sahlgrenska University Hospital, Goteborg, Sweden
| | - Jonas Varkey
- Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Goteborg, Sweden
- Division of Gastroenterology, Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
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Yao L, Li X, Wu Z, Wang J, Luo C, Chen B, Luo R, Zhang L, Zhang C, Tan X, Lu Z, Zhu C, Huang Y, Tan T, Liu Z, Li Y, Li S, Yu H. Effect of artificial intelligence on novice-performed colonoscopy: a multicenter randomized controlled tandem study. Gastrointest Endosc 2024; 99:91-99.e9. [PMID: 37536635 DOI: 10.1016/j.gie.2023.07.044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/21/2023] [Accepted: 07/22/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND AIMS The efficacy and safety of colonoscopy performed by artificial intelligence (AI)-assisted novices remain unknown. The aim of this study was to compare the lesion detection capability of novices, AI-assisted novices, and experts. METHODS This multicenter, randomized, noninferiority tandem study was conducted across 3 hospitals in China from May 1, 2022, to November 11, 2022. Eligible patients were randomized into 1 of 3 groups: the CN group (control novice group, withdrawal performed by a novice independently), the AN group (AI-assisted novice group, withdrawal performed by a novice with AI assistance), or the CE group (control expert group, withdrawal performed by an expert independently). Participants underwent a repeat colonoscopy conducted by an AI-assisted expert to evaluate the lesion miss rate and ensure lesion detection. The primary outcome was the adenoma miss rate (AMR). RESULTS A total of 685 eligible patients were analyzed: 229 in the CN group, 227 in the AN group, and 229 in the CE group. Both AMR and polyp miss rate were lower in the AN group than in the CN group (18.82% vs 43.69% [P < .001] and 21.23% vs 35.38% [P < .001], respectively). The noninferiority margin was met between the AN and CE groups of both AMR and polyp miss rate (18.82% vs 26.97% [P = .202] and 21.23% vs 24.10% [P < .249]). CONCLUSIONS AI-assisted colonoscopy lowered the AMR of novices, making them noninferior to experts. The withdrawal technique of new endoscopists can be enhanced by AI-assisted colonoscopy. (Clinical trial registration number: NCT05323279.).
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Affiliation(s)
- Liwen Yao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xun Li
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhifeng Wu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jing Wang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chaijie Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Boru Chen
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Renquan Luo
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lihui Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chenxia Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xia Tan
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zihua Lu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ci Zhu
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Yuan Huang
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Tao Tan
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Zhifeng Liu
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Ying Li
- Digestive Endoscopy Center, Wuhan Eighth Hospital, Wuhan, China
| | - Shuyu Li
- Department of Endoscopy, The Third People's Hospital of Hubei Province, Wuhan, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China.
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17
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Zhang L, Yao L, Lu Z, Yu H. Current status of quality control in screening esophagogastroduodenoscopy and the emerging role of artificial intelligence. Dig Endosc 2024; 36:5-15. [PMID: 37522555 DOI: 10.1111/den.14649] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 07/27/2023] [Indexed: 08/01/2023]
Abstract
Esophagogastroduodenoscopy (EGD) screening is being implemented in countries with a high incidence of upper gastrointestinal (UGI) cancer. High-quality EGD screening ensures the yield of early diagnosis and prevents suffering from advanced UGI cancer and minimal operational-related discomfort. However, performance varied dramatically among endoscopists, and quality control for EGD screening remains suboptimal. Guidelines have recommended potential measures for endoscopy quality improvement and research has been conducted for evidence. Moreover, artificial intelligence offers a promising solution for computer-aided diagnosis and quality control during EGD examinations. In this review, we summarized the key points for quality assurance in EGD screening based on current guidelines and evidence. We also outline the latest evidence, limitations, and future prospects of the emerging role of artificial intelligence in EGD quality control, aiming to provide a foundation for improving the quality of EGD screening.
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Affiliation(s)
- Lihui Zhang
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
| | - Liwen Yao
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zihua Lu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
- Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China
- Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China
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18
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Wei MT, Chen Y, Quan SY, Pan JY, Wong RJ, Friedland S. Evaluation of computer aided detection during colonoscopy among Veterans: Randomized clinical trial. Artif Intell Med Imaging 2023; 4:1-9. [DOI: 10.35711/aimi.v4.i1.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/10/2023] [Accepted: 10/30/2023] [Indexed: 12/05/2023] Open
Abstract
BACKGROUND There has been significant interest in use of computer aided detection (CADe) devices in colonoscopy to improve polyp detection and reduce miss rate.
AIM To investigate the use of CADe amongst veterans.
METHODS Between September 2020 and December 2021, we performed a randomized controlled trial to evaluate the impact of CADe. Patients at Veterans Affairs Palo Alto Health Care System presenting for screening or low-risk surveillance were randomized to colonoscopy performed with or without CADe. Primary outcomes of interest included adenoma detection rate (ADR), adenomas per colonoscopy (APC), and adenomas per extraction. In addition, we measured serrated polyps per colonoscopy, non-adenomatous, non-serrated polyps per colonoscopy, serrated polyp detection rate, and procedural time.
RESULTS A total of 244 patients were enrolled (124 with CADe), with similar patient characteristics (age, sex, body mass index, indication) between the two groups. Use of CADe was found to have decreased number of adenomas (1.79 vs 2.53, P = 0.030) per colonoscopy compared to without CADe. There was no significant difference in number of serrated polyps or non-adenomatous non-serrated polyps per colonoscopy between the two groups. Overall, use of CADe was found to have lower ADR (68.5% vs 80.0%, P = 0.041) compared to without use of CADe. Serrated polyp detection rate was lower with CADe (3.2% vs 7.5%) compared to without CADe, but this was not statistically significant (P = 0.137). There was no significant difference in withdrawal and procedure times between the two groups or in detection of adenomas per extraction (71.4% vs 73.1%, P = 0.613). No adverse events were identified.
CONCLUSION While several randomized controlled trials have demonstrated improved ADR and APC with use of CADe, in this RCT performed at a center with high ADR, use of CADe was found to have decreased APC and ADR. Further studies are needed to understand the true impact of CADe on performance quality among endoscopists as well as determine criteria for endoscopists to consider when choosing to adopt CADe in their practices.
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Affiliation(s)
- Mike T Wei
- Department of Gastroenterology and Hepatology, Stanford University Medical Center, Palo Alto, CA 94305, United States
| | - Yu Chen
- Department of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94305, United States
| | - Susan Y Quan
- Department of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94305, United States
| | - Jennifer Y Pan
- Department of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94305, United States
| | - Robert J Wong
- Department of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94305, United States
| | - Shai Friedland
- Department of Gastroenterology and Hepatology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94305, United States
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19
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Goetz N, Hanigan K, Cheng RKY. Artificial intelligence fails to improve colonoscopy quality: A single centre retrospective cohort study. Artif Intell Gastrointest Endosc 2023; 4:18-26. [DOI: 10.37126/aige.v4.i2.18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/07/2023] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND Limited data currently exists on the clinical utility of Artificial Intelligence Assisted Colonoscopy (AIAC) outside of clinical trials.
AIM To evaluate the impact of AIAC on key markers of colonoscopy quality compared to conventional colonoscopy (CC).
METHODS This single-centre retrospective observational cohort study included all patients undergoing colonoscopy at a secondary centre in Brisbane, Australia. CC outcomes between October 2021 and October 2022 were compared with AIAC outcomes after the introduction of the Olympus Endo-AID module from October 2022 to January 2023. Endoscopists who conducted over 50 procedures before and after AIAC introduction were included. Procedures for surveillance of inflammatory bowel disease were excluded. Patient demographics, proceduralist specialisation, indication for colonoscopy, and colonoscopy quality metrics were collected. Adenoma detection rate (ADR) and sessile serrated lesion detection rate (SSLDR) were calculated for both AIAC and CC.
RESULTS The study included 746 AIAC procedures and 2162 CC procedures performed by seven endoscopists. Baseline patient demographics were similar, with median age of 60 years with a slight female predominance (52.1%). Procedure indications, bowel preparation quality, and caecal intubation rates were comparable between groups. AIAC had a slightly longer withdrawal time compared to CC, but the difference was not statistically significant. The introduction of AIAC did not significantly change ADR (52.1% for AIAC vs 52.6% for CC, P = 0.91) or SSLDR (17.4% for AIAC vs 18.1% for CC, P = 0.44).
CONCLUSION The implementation of AIAC failed to improve key markers of colonoscopy quality, including ADR, SSLDR and withdrawal time. Further research is required to assess the utility and cost-efficiency of AIAC for high performing endoscopists.
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Affiliation(s)
- Naeman Goetz
- Department of Gastroenterology, Redcliffe Hospital, Redcliffe 4020, Australia
| | - Katherine Hanigan
- Department of Gastroenterology, Redcliffe Hospital, Redcliffe 4020, Australia
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20
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Mulki R, Qayed E, Yang D, Chua TY, Singh A, Yu JX, Bartel MJ, Tadros MS, Villa EC, Lightdale JR. The 2022 top 10 list of endoscopy topics in medical publishing: an annual review by the American Society for Gastrointestinal Endoscopy Editorial Board. Gastrointest Endosc 2023; 98:1009-1016. [PMID: 37977661 DOI: 10.1016/j.gie.2023.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 08/09/2023] [Accepted: 08/29/2023] [Indexed: 11/19/2023]
Abstract
Using a systematic literature search of original articles published during 2022 in Gastrointestinal Endoscopy and other high-impact medical and gastroenterology journals, the 10-member Editorial Board of the American Society for Gastrointestinal Endoscopy composed a list of the 10 most significant topic areas in GI endoscopy during the study year. Each Editorial Board member was directed to consider 3 criteria in generating candidate lists-significance, novelty, and global impact on clinical practice-and subject matter consensus was facilitated by the Chair through electronic voting. The 10 identified areas collectively represent advances in the following endoscopic spheres: artificial intelligence, endoscopic submucosal dissection, Barrett's esophagus, interventional EUS, endoscopic resection techniques, pancreaticobiliary endoscopy, management of acute pancreatitis, endoscopic environmental sustainability, the NordICC trial, and spiral enteroscopy. Each board member was assigned a consensus topic area around which to summarize relevant important articles, thereby generating this précis of the "top 10" endoscopic advances of 2022.
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Affiliation(s)
- Ramzi Mulki
- Division of Gastroenterology and Hepatology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Emad Qayed
- Division of Digestive Diseases, Department of Medicine, Emory University, Atlanta, Georgia, USA
| | - Dennis Yang
- Center of Interventional Endoscopy (CIE) Advent Health, Orlando, Florida, USA
| | - Tiffany Y Chua
- Division of Digestive Diseases, Harbor-University of California Los Angeles, Torrance, California, USA
| | - Ajaypal Singh
- Division of Digestive Diseases and Nutrition, Rush University Medical Center, Chicago, Illinois, USA
| | - Jessica X Yu
- Division of Gastroenterology and Hepatology, Oregon Health & Science University, Portland, Oregon, USA
| | | | | | - Edward C Villa
- NorthShore University Health System, Chicago, Illinois, USA
| | - Jenifer R Lightdale
- Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, Massachusetts, USA
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21
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Samarasena J, Yang D, Berzin TM. AGA Clinical Practice Update on the Role of Artificial Intelligence in Colon Polyp Diagnosis and Management: Commentary. Gastroenterology 2023; 165:1568-1573. [PMID: 37855759 DOI: 10.1053/j.gastro.2023.07.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 06/06/2023] [Accepted: 07/17/2023] [Indexed: 10/20/2023]
Abstract
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.
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Affiliation(s)
- Jason Samarasena
- Division of Gastroenterology, University of California Irvine, Orange, California
| | - Dennis Yang
- Center for Interventional Endoscopy, AdventHealth, Orlando, Florida.
| | - Tyler M Berzin
- Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts
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22
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Hassan C, Repici A, Mori Y. Cost of artificial intelligence: Elephant in the room and its cage. Dig Endosc 2023; 35:900-901. [PMID: 37160614 DOI: 10.1111/den.14567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 04/13/2023] [Indexed: 05/11/2023]
Affiliation(s)
- Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
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23
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Young E, Edwards L, Singh R. The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization. Cancers (Basel) 2023; 15:5126. [PMID: 37958301 PMCID: PMC10647850 DOI: 10.3390/cancers15215126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/14/2023] [Accepted: 10/14/2023] [Indexed: 11/15/2023] Open
Abstract
Colorectal cancer remains a leading cause of cancer-related morbidity and mortality worldwide, despite the widespread uptake of population surveillance strategies. This is in part due to the persistent development of 'interval colorectal cancers', where patients develop colorectal cancer despite appropriate surveillance intervals, implying pre-malignant polyps were not resected at a prior colonoscopy. Multiple techniques have been developed to improve the sensitivity and accuracy of lesion detection and characterisation in an effort to improve the efficacy of colorectal cancer screening, thereby reducing the incidence of interval colorectal cancers. This article presents a comprehensive review of the transformative role of artificial intelligence (AI), which has recently emerged as one such solution for improving the quality of screening and surveillance colonoscopy. Firstly, AI-driven algorithms demonstrate remarkable potential in addressing the challenge of overlooked polyps, particularly polyp subtypes infamous for escaping human detection because of their inconspicuous appearance. Secondly, AI empowers gastroenterologists without exhaustive training in advanced mucosal imaging to characterise polyps with accuracy similar to that of expert interventionalists, reducing the dependence on pathologic evaluation and guiding appropriate resection techniques or referrals for more complex resections. AI in colonoscopy holds the potential to advance the detection and characterisation of polyps, addressing current limitations and improving patient outcomes. The integration of AI technologies into routine colonoscopy represents a promising step towards more effective colorectal cancer screening and prevention.
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Affiliation(s)
- Edward Young
- Faculty of Health and Medical Sciences, University of Adelaide, Lyell McEwin Hospital, Haydown Rd, Elizabeth Vale, SA 5112, Australia
| | - Louisa Edwards
- Faculty of Health and Medical Sciences, University of Adelaide, Queen Elizabeth Hospital, Port Rd, Woodville South, SA 5011, Australia
| | - Rajvinder Singh
- Faculty of Health and Medical Sciences, University of Adelaide, Lyell McEwin Hospital, Haydown Rd, Elizabeth Vale, SA 5112, Australia
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24
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Berzin TM, Glissen Brown J. Navigating the "Trough of Disillusionment" for CADe Polyp Detection: What Can We Learn About Negative AI Trials and the Physician-AI Hybrid? Am J Gastroenterol 2023; 118:1743-1745. [PMID: 37141122 DOI: 10.14309/ajg.0000000000002286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 05/05/2023]
Affiliation(s)
- Tyler M Berzin
- Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Jeremy Glissen Brown
- Division of Gastroenterology, Duke University Medical Center, Durham, North Carolina, USA
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25
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Anderson JC, Rex DK. Performing High-Quality, Safe, Cost-Effective, and Efficient Basic Colonoscopy in 2023: Advice From Two Experts. Am J Gastroenterol 2023; 118:1779-1786. [PMID: 37463252 DOI: 10.14309/ajg.0000000000002407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/05/2023] [Indexed: 07/20/2023]
Abstract
Based on published evidence and our expert experience, we provide recommendations to maximize the efficacy, safety, efficiency, and cost-effectiveness of routine colonoscopy. High-quality colonoscopy begins with colon preparation using a split or same-day dose and preferably a low-volume regimen for optimal patient tolerance and compliance. Successful cecal intubation can be achieved by choosing the correct colonoscope and using techniques to facilitate navigation through challenges such as severe angulations and redundant colons. Safety is a primary goal, and complications such as perforation and splenic rupture can be prevented by avoiding pushing through fixed resistance and avoiding loops in proximal colon. Furthermore, barotrauma can be avoided by converting to water filling only (no gas insufflation) in every patient with a narrowed, angulated sigmoid. Optimal polyp detection relies primarily on compulsive attention to inspection as manifested by adequate inspection time, vigorous probing of the spaces between haustral folds, washing and removing residual debris, and achieving full distention. Achieving minimum recommended adenoma detection rate thresholds (30% in men and 20% in women) is mandatory, and colonoscopists should aspire to adenoma detection rate approaching 50% in screening patients. Distal attachments can improve mucosal exposure and increase detection while shortening withdrawal times. Complete resection of polyps complements polyp detection in preventing colorectal cancer. Cold resection is the preferred method for all polyps < 10 mm. For effective cold resection, an adequate rim of normal tissue should be captured in the snare. Finally, cost-effective high-quality colonoscopy requires the procedure not be overused, as demonstrated by following updated United States Multi Society Task Force on Colorectal Cancer postpolypectomy surveillance recommendations.
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Affiliation(s)
- Joseph C Anderson
- Division of Gastroenterology, Department of Medicine, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA
- Division of Gastroenterology, Department of Medicine, White River Junction VAMC, White River Junction, Vermont, USA
- Division of Gastroenterology, Department of Medicine, University of Connecticut School of Medicine, Farmington, Connecticut, USA
| | - Douglas K Rex
- Department of Medicine, Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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26
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Hassan C, Mori Y, Sharma P. The Pros and Cons of Artificial Intelligence in Endoscopy. Am J Gastroenterol 2023; 118:1720-1722. [PMID: 37052360 DOI: 10.14309/ajg.0000000000002287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/27/2023] [Indexed: 04/14/2023]
Affiliation(s)
- Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Endoscopy Unit, Humanitas Clinical and Research Center, IRCCS, Rozzano, Italy
| | - Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
| | - Prateek Sharma
- University of Kansas School of Medicine and VA Medical Center, Kansas City, Kansas, USA
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27
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Mangas-Sanjuan C, de-Castro L, Cubiella J, Díez-Redondo P, Suárez A, Pellisé M, Fernández N, Zarraquiños S, Núñez-Rodríguez H, Álvarez-García V, Ortiz O, Sala-Miquel N, Zapater P, Jover R. Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias : A Randomized Trial. Ann Intern Med 2023; 176:1145-1152. [PMID: 37639723 DOI: 10.7326/m22-2619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/31/2023] Open
Abstract
BACKGROUND The role of computer-aided detection in identifying advanced colorectal neoplasia is unknown. OBJECTIVE To evaluate the contribution of computer-aided detection to colonoscopic detection of advanced colorectal neoplasias as well as adenomas, serrated polyps, and nonpolypoid and right-sided lesions. DESIGN Multicenter, parallel, randomized controlled trial. (ClinicalTrials.gov: NCT04673136). SETTING Spanish colorectal cancer screening program. PARTICIPANTS 3213 persons with a positive fecal immunochemical test. INTERVENTION Enrollees were randomly assigned to colonoscopy with or without computer-aided detection. MEASUREMENTS Advanced colorectal neoplasia was defined as advanced adenoma and/or advanced serrated polyp. RESULTS The 2 comparison groups showed no significant difference in advanced colorectal neoplasia detection rate (34.8% with intervention vs. 34.6% for controls; adjusted risk ratio [aRR], 1.01 [95% CI, 0.92 to 1.10]) or the mean number of advanced colorectal neoplasias detected per colonoscopy (0.54 [SD, 0.95] with intervention vs. 0.52 [SD, 0.95] for controls; adjusted rate ratio, 1.04 [99.9% CI, 0.88 to 1.22]). Adenoma detection rate also did not differ (64.2% with intervention vs. 62.0% for controls; aRR, 1.06 [99.9% CI, 0.91 to 1.23]). Computer-aided detection increased the mean number of nonpolypoid lesions (0.56 [SD, 1.25] vs. 0.47 [SD, 1.18] for controls; adjusted rate ratio, 1.19 [99.9% CI, 1.01 to 1.41]), proximal adenomas (0.94 [SD, 1.62] vs. 0.81 [SD, 1.52] for controls; adjusted rate ratio, 1.17 [99.9% CI, 1.03 to 1.33]), and lesions of 5 mm or smaller (polyps in general and adenomas and serrated lesions in particular) detected per colonoscopy. LIMITATIONS The high adenoma detection rate in the control group may limit the generalizability of the findings to endoscopists with low detection rates. CONCLUSION Computer-aided detection did not improve colonoscopic identification of advanced colorectal neoplasias. PRIMARY FUNDING SOURCE Medtronic.
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Affiliation(s)
- Carolina Mangas-Sanjuan
- Department of Gastroenterology, Hospital General Universitario Dr. Balmis, Servicio de Medicina Digestiva, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Spain (C.M., N.S.)
| | - Luisa de-Castro
- Department of Gastroenterology, Hospital Álvaro Cunqueiro, Digestive Pathology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain (L. de-C., N.F.)
| | - Joaquín Cubiella
- Department of Gastroenterology, Hospital Universitario de Ourense, Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas (CIBERehd), Ourense, Spain (J.C., S.Z.)
| | - Pilar Díez-Redondo
- Department of Gastroenterology, Hospital Río-Hortega, Valladolid, Spain (P.D., H.N.)
| | - Adolfo Suárez
- Department of Gastroenterology, Hospital Central de Asturias, Oviedo, Spain (A.S., V.A.)
| | - María Pellisé
- Department of Gastroenterology, Hospital Clínic Barcelona, Barcelona, Spain (M.P., O.O.)
| | - Nereida Fernández
- Department of Gastroenterology, Hospital Álvaro Cunqueiro, Digestive Pathology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain (L. de-C., N.F.)
| | - Sara Zarraquiños
- Department of Gastroenterology, Hospital Universitario de Ourense, Centro de Investigación Biomédica en Red Enfermedades Hepáticas y Digestivas (CIBERehd), Ourense, Spain (J.C., S.Z.)
| | - Henar Núñez-Rodríguez
- Department of Gastroenterology, Hospital Río-Hortega, Valladolid, Spain (P.D., H.N.)
| | | | - Oswaldo Ortiz
- Department of Gastroenterology, Hospital Clínic Barcelona, Barcelona, Spain (M.P., O.O.)
| | - Noelia Sala-Miquel
- Department of Gastroenterology, Hospital General Universitario Dr. Balmis, Servicio de Medicina Digestiva, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Spain (C.M., N.S.)
| | - Pedro Zapater
- Hospital General Universitario Dr. Balmis, Clinical Pharmacology Department, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Departamento de Farmacología, Universidad Miguel Hernández, Alicante, CIBERehd, Spain (P.Z.)
| | - Rodrigo Jover
- Department of Gastroenterology, Hospital General Universitario Dr. Balmis, Servicio de Medicina Digestiva, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain (R.J.)
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Shung DL. From Tool to Team Member: A Second Set of Eyes for Polyp Detection. Ann Intern Med 2023; 176:1271-1272. [PMID: 37639722 DOI: 10.7326/m23-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/31/2023] Open
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Sudarevic B, Sodmann P, Kafetzis I, Troya J, Lux TJ, Saßmannshausen Z, Herlod K, Schmidt SA, Brand M, Schöttker K, Zoller WG, Meining A, Hann A. Artificial intelligence-based polyp size measurement in gastrointestinal endoscopy using the auxiliary waterjet as a reference. Endoscopy 2023; 55:871-876. [PMID: 37080235 PMCID: PMC10465238 DOI: 10.1055/a-2077-7398] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 04/19/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND Measurement of colorectal polyp size during endoscopy is mainly performed visually. In this work, we propose a novel polyp size measurement system (Poseidon) based on artificial intelligence (AI) using the auxiliary waterjet as a measurement reference. METHODS Visual estimation, biopsy forceps-based estimation, and Poseidon were compared using a computed tomography colonography-based silicone model with 28 polyps of defined sizes. Four experienced gastroenterologists estimated polyp sizes visually and with biopsy forceps. Furthermore, the gastroenterologists recorded images of each polyp with the waterjet in proximity for the application of Poseidon. Additionally, Poseidon's measurements of 29 colorectal polyps during routine clinical practice were compared with visual estimates. RESULTS In the silicone model, visual estimation had the largest median percentage error of 25.1 % (95 %CI 19.1 %-30.4 %), followed by biopsy forceps-based estimation: median 20.0 % (95 %CI 14.4 %-25.6 %). Poseidon gave a significantly lower median percentage error of 7.4 % (95 %CI 5.0 %-9.4 %) compared with other methods. During routine colonoscopies, Poseidon presented a significantly lower median percentage error (7.7 %, 95 %CI 6.1 %-9.3 %) than visual estimation (22.1 %, 95 %CI 15.1 %-26.9 %). CONCLUSION In this work, we present a novel AI-based method for measuring colorectal polyp size with significantly higher accuracy than other common sizing methods.
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Affiliation(s)
- Boban Sudarevic
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
- Department of Internal Medicine and Gastroenterology, Katharinenhospital, Stuttgart, Germany
| | - Philipp Sodmann
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Ioannis Kafetzis
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Joel Troya
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Thomas J. Lux
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Zita Saßmannshausen
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Katja Herlod
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Stefan A. Schmidt
- Department of Diagnostic and Interventional Radiology, University Hospital Ulm, Ulm, Germany
| | - Markus Brand
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Katrin Schöttker
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Wolfram G. Zoller
- Department of Internal Medicine and Gastroenterology, Katharinenhospital, Stuttgart, Germany
| | - Alexander Meining
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
| | - Alexander Hann
- Interventional and Experimental Endoscopy (InExEn), Internal Medicine II, University Hospital Würzburg, Würzburg, Germany
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Maida M, Marasco G, Facciorusso A, Shahini E, Sinagra E, Pallio S, Ramai D, Murino A. Effectiveness and application of artificial intelligence for endoscopic screening of colorectal cancer: the future is now. Expert Rev Anticancer Ther 2023; 23:719-729. [PMID: 37194308 DOI: 10.1080/14737140.2023.2215436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 05/15/2023] [Indexed: 05/18/2023]
Abstract
INTRODUCTION Artificial intelligence (AI) in gastrointestinal endoscopy includes systems designed to interpret medical images and increase sensitivity during examination. This may be a promising solution to human biases and may provide support during diagnostic endoscopy. AREAS COVERED This review aims to summarize and evaluate data supporting AI technologies in lower endoscopy, addressing their effectiveness, limitations, and future perspectives. EXPERT OPINION Computer-aided detection (CADe) systems have been studied with promising results, allowing for an increase in adenoma detection rate (ADR), adenoma per colonoscopy (APC), and a reduction in adenoma miss rate (AMR). This may lead to an increase in the sensitivity of endoscopic examinations and a reduction in the risk of interval-colorectal cancer. In addition, computer-aided characterization (CADx) has also been implemented, aiming to distinguish adenomatous and non-adenomatous lesions through real-time assessment using advanced endoscopic imaging techniques. Moreover, computer-aided quality (CADq) systems have been developed with the aim of standardizing quality measures in colonoscopy (e.g. withdrawal time and adequacy of bowel cleansing) both to improve the quality of examinations and set a reference standard for randomized controlled trials.
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Affiliation(s)
- Marcello Maida
- Gastroenterology and Endoscopy Unit, S. Elia-Raimondi Hospital, Caltanissetta, Italy
| | - Giovanni Marasco
- IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy
- Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy
| | - Antonio Facciorusso
- Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy
| | - Endrit Shahini
- Gastroenterology Unit, National Institute of Gastroenterology-IRCCS "Saverio de Bellis", Castellana Grotte, Bari, Italy
| | - Emanuele Sinagra
- Gastroenterology and Endoscopy Unit, Fondazione Istituto San Raffaele Giglio, Cefalu, Italy
| | - Socrate Pallio
- Digestive Diseases Endoscopy Unit, Policlinico G. Martino Hospital, University of Messina, Messina, Italy
| | - Daryl Ramai
- Gastroenterology & Hepatology, University of Utah Health, Salt Lake City, UT, USA
| | - Alberto Murino
- Royal Free Unit for Endoscopy, The Royal Free Hospital and University College London Institute for Liver and Digestive Health, Hampstead, London, UK
- Department of Gastroenterology, Cleveland Clinic London, London, UK
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Galati JS, Lin K, Gross SA. Recent advances in devices and technologies that might prove revolutionary for colonoscopy procedures. Expert Rev Med Devices 2023; 20:1087-1103. [PMID: 37934873 DOI: 10.1080/17434440.2023.2280773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 11/03/2023] [Indexed: 11/09/2023]
Abstract
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.
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Affiliation(s)
- Jonathan S Galati
- Department of Internal Medicine, NYU Langone Health, New York, NY, USA
| | - Kevin Lin
- Department of Internal Medicine, NYU Langone Health, New York, NY, USA
| | - Seth A Gross
- Division of Gastroenterology, NYU Langone Health, New York, NY, USA
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Ayoub F, Sengupta N. Computer-aided polyp detection (CADe) in real life: not the "CADe-llac" we were promised. Gastrointest Endosc 2023; 98:110-112. [PMID: 37331763 DOI: 10.1016/j.gie.2023.03.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 06/20/2023]
Affiliation(s)
- Fares Ayoub
- Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA
| | - Neil Sengupta
- Section of Gastroenterology, Hepatology, and Nutrition, University of Chicago Medicine, Chicago, Illinois, USA
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Spadaccini M, Schilirò A, Sharma P, Repici A, Hassan C, Voza A. Adenoma detection rate in colonoscopy: how can it be improved? Expert Rev Gastroenterol Hepatol 2023; 17:1089-1099. [PMID: 37869781 DOI: 10.1080/17474124.2023.2273990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 10/18/2023] [Indexed: 10/24/2023]
Abstract
INTRODUCTION The introduction of widespread colonoscopy screening programs has helped in decreasing the incidence of Colorectal Cancer (CRC). However, 'back-to-back' colonoscopies revealed relevant percentage of missed adenomas. Quality indicators were created to further homogenize detection performances and decrease the incidence of post-colonoscopy CRC. Among them, the Adenoma Detection Rate (ADR), defined as the percentage obtained by dividing the number of endoscopic procedures in which at least one adenoma was resected, by the total number of procedures, was found to be inversely associated with the risks of interval colorectal cancer, advanced-stage interval cancer, and fatal interval cancer. AREAS COVERED In this paper, we performed a comprehensive review of the literature focusing on promising new devices and technologies, which are meant to positively affect the endoscopist performance in detecting adenomas, therefore increasing ADR. EXPERT OPINION Considering the current knowledge, although several devices and technologies have been proposed with this intent, the recent implementation of AI ranked over all of the other strategies and it is likely to become the new standard within few years. However, the combination of different device/technologies need to be investigated in the future aiming at even further increasing of endoscopist detection performances.
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Affiliation(s)
- Marco Spadaccini
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Humanitas Clinical and Research Center -IRCCS-, Endoscopy Unit, Rozzano, Italy
| | - Alessandro Schilirò
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
| | | | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Humanitas Clinical and Research Center -IRCCS-, Endoscopy Unit, Rozzano, Italy
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Humanitas Clinical and Research Center -IRCCS-, Endoscopy Unit, Rozzano, Italy
| | - Antonio Voza
- Humanitas Clinical and Research Center -IRCCS-, Emergency Department, Rozzano, Italy
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Spadaccini M, Hassan C, Rondonotti E, Antonelli G, Andrisani G, Lollo G, Auriemma F, Iacopini F, Facciorusso A, Maselli R, Fugazza A, Bambina Bergna IM, Cereatti F, Mangiavillano B, Radaelli F, Di Matteo F, Gross SA, Sharma P, Mori Y, Bretthauer M, Rex DK, Repici A. Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial. Gastroenterology 2023; 165:244-251.e3. [PMID: 37061169 DOI: 10.1053/j.gastro.2023.03.237] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 03/08/2023] [Accepted: 03/27/2023] [Indexed: 04/17/2023]
Abstract
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.
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Affiliation(s)
- Marco Spadaccini
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, Humanitas Clinical and Research Center, Istituto di Ricovero e Cura a Carattere Scientifico, Rozzano, Italy.
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, Humanitas Clinical and Research Center, Istituto di Ricovero e Cura a Carattere Scientifico, Rozzano, Italy
| | | | - Giulio Antonelli
- Department of Anatomical, Histological, Forensic Medicine, and Orthopaedics Sciences, Sapienza University of Rome, Rome, Italy; Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli Hospital, Ariccia, Italy
| | - Gianluca Andrisani
- Digestive Endoscopy Unit, Campus Bio-Medico, University of Rome, Rome, Italy
| | - Gianluca Lollo
- Department of Gastroenterology and Hepatology, Università della Svizzera Italiana, Lugano, Switzerland
| | - Francesco Auriemma
- Gastrointestinal Endoscopy Unit, Humanitas Mater Domini, Castellanza, Italy
| | - Federico Iacopini
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli Hospital, Ariccia, Italy
| | - Antonio Facciorusso
- Gastroenterology Unit, Department of Surgical and Medical Sciences, University of Foggia, Foggia, Italy
| | - Roberta Maselli
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, Humanitas Clinical and Research Center, Istituto di Ricovero e Cura a Carattere Scientifico, Rozzano, Italy
| | - Alessandro Fugazza
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
| | | | - Fabrizio Cereatti
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli Hospital, Ariccia, Italy
| | - Benedetto Mangiavillano
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Gastrointestinal Endoscopy Unit, Humanitas Mater Domini, Castellanza, Italy
| | | | - Francesco Di Matteo
- Digestive Endoscopy Unit, Campus Bio-Medico, University of Rome, Rome, Italy
| | - Seth A Gross
- Division of Gastroenterology and Hepatology, New York University Langone Health, New York, New York
| | - Prateek Sharma
- Gastroenterology and Hepatology, Kansas City Veterans Affairs Medical Center, Kansas City, Missouri
| | - Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway; Digestive Disease Center, Showa University, Northern Yokohama Hospital, Yokohama, Japan
| | | | - Douglas K Rex
- Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy; Endoscopy Unit, Humanitas Clinical and Research Center, Istituto di Ricovero e Cura a Carattere Scientifico, Rozzano, Italy
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Mansour NM. Artificial Intelligence in Colonoscopy. Curr Gastroenterol Rep 2023; 25:122-129. [PMID: 37129831 DOI: 10.1007/s11894-023-00872-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/03/2023] [Indexed: 05/03/2023]
Abstract
PURPOSE OF REVIEW Artificial intelligence (AI) is a rapidly growing field in gastrointestinal endoscopy, and its potential applications are virtually endless, with studies demonstrating use of AI for early gastric cancer, inflammatory bowel disease, Barrett's esophagus, capsule endoscopy, as well as other areas in gastroenterology. Much of the early studies and applications of AI in gastroenterology have revolved around colonoscopy, particularly with regards to real-time polyp detection and characterization. This review will cover much of the existing data on computer-aided detection (CADe), computer-aided diagnosis (CADx), and briefly discuss some other interesting applications of AI for colonoscopy, while also considering some of the challenges and limitations that exist around the use of AI for colonoscopy. RECENT FINDINGS Multiple randomized controlled trials have now been published which show a statistically significant improvement when using AI to improve adenoma detection and reduce adenoma miss rates during colonoscopy. There is also a growing pool of literature showing that AI can be helpful for characterizing/diagnosing colorectal polyps in real time. AI has also shown promise in other areas of colonoscopy, including polyp sizing and automated measurement and monitoring of quality metrics during colonoscopy. AI is a promising tool that has the ability to shape the future of gastrointestinal endoscopy, with much of the early data showing significant benefits to use of AI during colonoscopy. However, there remain several challenges that may delay or hamper the widespread use of AI in the field.
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Affiliation(s)
- Nabil M Mansour
- Section of Gastroenterology and Hepatology, Baylor College of Medicine, 7200 Cambridge St., Suite 8B, Houston, TX, 77030, USA.
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Cherubini A, Dinh NN. A Review of the Technology, Training, and Assessment Methods for the First Real-Time AI-Enhanced Medical Device for Endoscopy. Bioengineering (Basel) 2023; 10:bioengineering10040404. [PMID: 37106592 PMCID: PMC10136070 DOI: 10.3390/bioengineering10040404] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 02/25/2023] [Accepted: 03/22/2023] [Indexed: 04/29/2023] Open
Abstract
Artificial intelligence (AI) has the potential to assist in endoscopy and improve decision making, particularly in situations where humans may make inconsistent judgments. The performance assessment of the medical devices operating in this context is a complex combination of bench tests, randomized controlled trials, and studies on the interaction between physicians and AI. We review the scientific evidence published about GI Genius, the first AI-powered medical device for colonoscopy to enter the market, and the device that is most widely tested by the scientific community. We provide an overview of its technical architecture, AI training and testing strategies, and regulatory path. In addition, we discuss the strengths and limitations of the current platform and its potential impact on clinical practice. The details of the algorithm architecture and the data that were used to train the AI device have been disclosed to the scientific community in the pursuit of a transparent AI. Overall, the first AI-enabled medical device for real-time video analysis represents a significant advancement in the use of AI for endoscopies and has the potential to improve the accuracy and efficiency of colonoscopy procedures.
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Affiliation(s)
- Andrea Cherubini
- Cosmo Intelligent Medical Devices, D02KV60 Dublin, Ireland
- Milan Center for Neuroscience, University of Milano-Bicocca, 20126 Milano, Italy
| | - Nhan Ngo Dinh
- Cosmo Intelligent Medical Devices, D02KV60 Dublin, Ireland
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Zimmermann-Fraedrich K, Rösch T. Artificial intelligence and the push for small adenomas: all we need? Endoscopy 2023; 55:320-323. [PMID: 36882088 DOI: 10.1055/a-2038-7078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Affiliation(s)
| | - Thomas Rösch
- Department of Interdisciplinary Endoscopy University Hospital Hamburg-Eppendorf, Hamburg, Germany
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Byrne MF, Von Renteln D, Barkun AN. Artificial Intelligence-Aided Colonoscopy for Characterizing and Detecting Colorectal Polyps: Required, Nice to Have, or Overhyped? Gastroenterology 2023; 164:332-333. [PMID: 36634825 DOI: 10.1053/j.gastro.2023.01.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 01/14/2023]
Affiliation(s)
- Michael F Byrne
- Division of Gastroenterology, Vancouver General Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Daniel Von Renteln
- Department of Medicine, Division of Gastroenterology, Montreal University Hospital Center, Montreal University Hospital Research Center, Université de Montréal, Montreal, Quebec, Canada
| | - Alan N Barkun
- Division of Gastroenterology, McGill University, McGill University Health Centre, Montreal, Quebec, Canada.
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Pitfalls of Advanced Endoscopy Technologies in Gastrointestinal Cancer Screening. Am J Gastroenterol 2023; 118:371-372. [PMID: 36191280 DOI: 10.14309/ajg.0000000000002046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 09/26/2022] [Indexed: 12/11/2022]
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Response to Hassan et al. Am J Gastroenterol 2022; 117:2089. [PMID: 36455226 DOI: 10.14309/ajg.0000000000002033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
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