1
|
Burke CA, Macaron C, Singh A. Artificial intelligence-assisted adenoma detection in people with Lynch syndrome. Lancet Gastroenterol Hepatol 2024; 9:776-777. [PMID: 39033773 DOI: 10.1016/s2468-1253(24)00223-1] [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: 07/02/2024] [Accepted: 07/03/2024] [Indexed: 07/23/2024]
Affiliation(s)
- Carol A Burke
- Department of Gastroenterology, Hepatology, and Nutrition, Cleveland Clinic, Cleveland, OH, USA; Sanford R Weiss MD Center for Hereditary Colorectal Neoplasia, Cleveland Clinic, Cleveland, OH, USA.
| | - Carole Macaron
- Department of Gastroenterology, Hepatology, and Nutrition, Cleveland Clinic, Cleveland, OH, USA; Sanford R Weiss MD Center for Hereditary Colorectal Neoplasia, Cleveland Clinic, Cleveland, OH, USA
| | - Aparajita Singh
- Division of Gastroenterology, University of San Francisco, San Francisco, CA, USA
| |
Collapse
|
2
|
Ortiz O, Daca-Alvarez M, Rivero-Sanchez L, Gimeno-Garcia AZ, Carrillo-Palau M, Alvarez V, Ledo-Rodriguez A, Ricciardiello L, Pierantoni C, Hüneburg R, Nattermann J, Bisschops R, Tejpar S, Huerta A, Riu Pons F, Alvarez-Urturi C, López-Vicente J, Repici A, Hassan C, Cid L, Cavestro GM, Romero-Mascarell C, Gordillo J, Puig I, Herraiz M, Betes M, Herrero J, Jover R, Balaguer F, Pellisé M. An artificial intelligence-assisted system versus white light endoscopy alone for adenoma detection in individuals with Lynch syndrome (TIMELY): an international, multicentre, randomised controlled trial. Lancet Gastroenterol Hepatol 2024; 9:802-810. [PMID: 39033774 DOI: 10.1016/s2468-1253(24)00187-0] [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: 04/20/2024] [Revised: 05/27/2024] [Accepted: 05/29/2024] [Indexed: 07/23/2024]
Abstract
BACKGROUND Computer-aided detection (CADe) systems for colonoscopy have been shown to increase small polyp detection during colonoscopy in the general population. People with Lynch syndrome represent an ideal target population for CADe-assisted colonoscopy because adenomas, the primary cancer precursor lesions, are characterised by their small size and higher likelihood of showing advanced histology. We aimed to evaluate the performance of CADe-assisted colonoscopy in detecting adenomas in individuals with Lynch syndrome. METHODS TIMELY was an international, multicentre, parallel, randomised controlled trial done in 11 academic centres and six community centres in Belgium, Germany, Italy, and Spain. We enrolled individuals aged 18 years or older with pathogenic or likely pathogenic MLH1, MSH2, MSH6, or EPCAM variants. Participants were consecutively randomly assigned (1:1) to either CADe (GI Genius) assisted white light endoscopy (WLE) or WLE alone. A centre-stratified randomisation sequence was generated through a computer-generated system with a separate randomisation list for each centre according to block-permuted randomisation (block size 26 patients per centre). Allocation was automatically provided by the online AEG-REDCap database. Participants were masked to the random assignment but endoscopists were not. The primary outcome was the mean number of adenomas per colonoscopy, calculated by dividing the total number of adenomas detected by the total number of colonoscopies and assessed in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT04909671. FINDINGS Between Sept 13, 2021, and April 6, 2023, 456 participants were screened for eligibility, 430 of whom were randomly assigned to receive CADe-assisted colonoscopy (n=214) or WLE (n=216). 256 (60%) participants were female and 174 (40%) were male. In the intention-to-treat analysis, the mean number of adenomas per colonoscopy was 0·64 (SD 1·57) in the CADe group and 0·64 (1·17) in the WLE group (adjusted rate ratio 1·03 [95% CI 0·72-1·47); p=0·87). No adverse events were reported during the trial. INTERPRETATION In this multicentre international trial, CADe did not improve the detection of adenomas in individuals with Lynch syndrome. High-quality procedures and thorough inspection and exposure of the colonic mucosa remain the cornerstone in surveillance of Lynch syndrome. FUNDING Spanish Gastroenterology Association, Spanish Society of Digestive Endoscopy, European Society of Gastrointestinal Endoscopy, Societat Catalana de Digestologia, Instituto Carlos III, Beca de la Marato de TV3 2020. Co-funded by the European Union.
Collapse
Affiliation(s)
- Oswaldo Ortiz
- Hospital Clinic Barcelona, Gastroenterology Department, Barcelona, Spain; Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomédiques August Pi i Sunyer, Barcelona, Spain
| | - Maria Daca-Alvarez
- Hospital Clinic Barcelona, Gastroenterology Department, Barcelona, Spain; Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomédiques August Pi i Sunyer, Barcelona, Spain
| | - Liseth Rivero-Sanchez
- Hospital Clinic Barcelona, Gastroenterology Department, Barcelona, Spain; Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomédiques August Pi i Sunyer, Barcelona, Spain
| | | | - Marta Carrillo-Palau
- Hospital Universitario de Canarias, Digestive System Service, Santa Cruz de Tenerife, Spain
| | - Victoria Alvarez
- Complejo Hospitalario de Pontevedra, Department of Gastroenterology, Pontevedra, Spain
| | | | - Luigi Ricciardiello
- IRCCS Azienda Ospedaliero Universitaria di Bologna, Bologna, Italy; Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy; Gastroenterology, Hepatology, and Nutrition, University of Texas at MD Anderson Cancer Center, Houston, TX, USA
| | | | - Robert Hüneburg
- Department of Internal Medicine I and National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany; European Reference Network for Genetic Tumor Risk Syndromes (ERN Genturis), Bonn, Germany
| | - Jacob Nattermann
- Department of Internal Medicine I and National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany; European Reference Network for Genetic Tumor Risk Syndromes (ERN Genturis), Bonn, Germany
| | - Raf Bisschops
- Gastroenterology Department, University Hospital Leuven, Leuven, Belgium
| | - Sabine Tejpar
- Gastroenterology Department, University Hospital Leuven, Leuven, Belgium
| | - Alain Huerta
- Hospital Galdakao-Usansolo, Department of Gastroenterology, Galdakao, Spain
| | - Faust Riu Pons
- Gastroenterology Department, Hospital del Mar Research Institute, Barcelona, Spain
| | | | - Jorge López-Vicente
- Hospital Universitario de Móstoles, Digestive System Service, Móstoles, Spain
| | - Alessandro Repici
- Gastroenterology Department, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Cessare Hassan
- Gastroenterology Department, IRCCS Humanitas Research Hospital, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Lucia Cid
- Hospital Alvaro Cunqueiro, Galicia, Spain; Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain
| | - Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Jordi Gordillo
- Hospital de la Santa Creu i Sant Pau, Gastroenterology Unit, Barcelona, Spain
| | - Ignasi Puig
- Institut de Recerca i Innovació en Ciències de la Vida i de la Salut a la Catalunya Central (IRIS-CC), Vic, Spain; Digestive Diseases Department, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, Spain; Facultat de Medicina, Universitat de Vic-Central de Cataluña (UVIC-UCC), Vic, Spain
| | - Maite Herraiz
- University of Navarra Clinic-IdiSNA, Gastroenterology Department, Pamplona, Spain
| | - Maite Betes
- University of Navarra Clinic-IdiSNA, Gastroenterology Department, Pamplona, Spain
| | - Jesús Herrero
- Complexo Hospitalario Universitario de Ourense, Instituto de Investigación Biomédica Galicia Sur, CIBERehd, Ourense, Spain
| | - Rodrigo Jover
- Hospital Universitario de Alicante, Pais Valencia, Spain
| | - Francesc Balaguer
- Hospital Clinic Barcelona, Gastroenterology Department, Barcelona, Spain; Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomédiques August Pi i Sunyer, Barcelona, Spain; University of Barcelona, Barcelona, Spain
| | - Maria Pellisé
- Hospital Clinic Barcelona, Gastroenterology Department, Barcelona, Spain; Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomédiques August Pi i Sunyer, Barcelona, Spain; University of Barcelona, Barcelona, Spain.
| |
Collapse
|
3
|
Maida M, Dahiya DS, Shah YR, Tiwari A, Gopakumar H, Vohra I, Khan A, Jaber F, Ramai D, Facciorusso A. Screening and Surveillance of Colorectal Cancer: A Review of the Literature. Cancers (Basel) 2024; 16:2746. [PMID: 39123473 PMCID: PMC11312202 DOI: 10.3390/cancers16152746] [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: 07/13/2024] [Accepted: 07/31/2024] [Indexed: 08/12/2024] Open
Abstract
Colorectal cancer (CRC) has the highest mortality rate among men and is the second highest among women under fifty, with incidence and mortality rates rising in younger populations. Studies indicate that up to one-third of patients diagnosed before fifty have a family history or genetic factors, highlighting the need for earlier screening. Contrariwise, diagnosis in healthy subjects through screening strategies enables early-stage detection of the tumor and better clinical outcomes. In recent years, mortality rates of CRC in Western countries have been on a steady decline, which is largely attributed to widespread screening programs and advancements in treatment modalities. Indeed, early detection through screening significantly improves prognosis, with stark differences in survival rates between localized and metastatic disease. This article aims to provide a comprehensive review of the existing literature, delving into the performance and efficacy of various CRC screening strategies. It navigates through available screening tools, evaluating their efficacy and cost-effectiveness. The discussion extends to delineating target populations for screening, emphasizing the importance of tailored approaches for individuals at heightened risk.
Collapse
Affiliation(s)
- Marcello Maida
- Department of Medicine and Surgery, University of Enna ‘Kore’, 94100 Enna, Italy;
| | - Dushyant Singh Dahiya
- Division of Gastroenterology, Hepatology and Motility, The University of Kansas School of Medicine, Kansas City, KS 66160, USA
| | - Yash R. Shah
- Department of Internal Medicine, Trinity Health Oakland/Wayne State University, Pontiac, MI 48341, USA
| | - Angad Tiwari
- Department of Internal Medicine, Maharani Laxmi Bai Medical College, Jhansi 284001, India;
| | - Harishankar Gopakumar
- Division of Gastroenterology and Hepatology, University of Illinois College of Medicine at Peoria, Peoria, IL 61605, USA; (H.G.); (I.V.)
| | - Ishaan Vohra
- Division of Gastroenterology and Hepatology, University of Illinois College of Medicine at Peoria, Peoria, IL 61605, USA; (H.G.); (I.V.)
| | - Aqsa Khan
- Department of Internal Medicine, Parkview Health, Fort Wayne, IN 46805, USA;
| | - Fouad Jaber
- Department of Internal Medicine, University of Missouri-Kansas City, Kansas City, KS 64110, USA;
| | - Daryl Ramai
- Division of Gastroenterology and Hepatology, The University of Utah School of Medicine, Salt Lake City, UT 84132, USA;
| | - Antonio Facciorusso
- Gastroenterology Unit, Department of Biomedical Science, Foggia University Hospital, 71122 Foggia, Italy
| |
Collapse
|
4
|
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; 167:560-590. [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] [MESH Headings] [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.
Collapse
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.
| |
Collapse
|
5
|
Sugino S, Yoshida N, Guo Z, Zhang R, Inoue K, Hirose R, Dohi O, Itoh Y, Nemoto D, Togashi K, Yamamoto H, Zhu X. Non-polypoid Colorectal Lesions Detection and False Positive Detection by Artificial Intelligence under Blue Laser Imaging and Linked Color Imaging. J Anus Rectum Colon 2024; 8:212-220. [PMID: 39086882 PMCID: PMC11286363 DOI: 10.23922/jarc.2023-070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 03/28/2024] [Indexed: 08/02/2024] Open
Abstract
Objectives Artificial intelligence (AI) with white light imaging (WLI) is not enough for detecting non-polypoid colorectal polyps and it still has high false positive rate (FPR). We developed AIs using blue laser imaging (BLI) and linked color imaging (LCI) to detect them with specific learning sets (LS). Methods The contents of LS were as follows, LS (WLI): 1991 WLI images of lesion of 2-10 mm, LS (IEE): 5920 WLI, BLI, and LCI images of non-polypoid and small lesions of 2-20 mm. LS (IEE) was extracted from videos and included both in-focus and out-of-focus images. We designed three AIs as follows: AI (WLI) finetuned by LS (WLI), AI (IEE) finetuned by LS (WLI)+LS (IEE), and AI (HQ) finetuned by LS (WLI)+LS (IEE) only with images in focus. Polyp detection using a test set of WLI, BLI, and LCI videos of 100 non-polypoid or non-reddish lesions of 2-20 mm and FPR using movies of 15 total colonoscopy were analyzed, compared to 2 experts and 2 trainees. Results The sensitivity for LCI in AI (IEE) (83%) was compared to that for WLI in AI (IEE) (76%: p=0.02), WLI in AI (WLI) (57%: p<0.01), BLI in AI (IEE) (78%: p=0.14), and LCI in trainees (74%: p<0.01). The sensitivity for LCI in AI (IEE) (83%) was significantly higher than that in AI (HQ) (78%: p<0.01). The FPR for LCI (6.5%) in AI (IEE) were significantly lower than that in AI (HQ) (17.3%: p<0.01). Conclusions AI finetuned by appropriate LS detected non-reddish and non-polypoid polyps under LCI.
Collapse
Affiliation(s)
- Satoshi Sugino
- Department of Gastroenterology, Asahi University Hospital, Gifu, Japan
| | - Naohisa Yoshida
- Department of Gastroenterology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Zhe Guo
- Biomedical Information Engineering Lab, The University of Aizu, Fukushima, Japan
| | - Ruiyao Zhang
- Biomedical Information Engineering Lab, The University of Aizu, Fukushima, Japan
| | - Ken Inoue
- Department of Gastroenterology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Ryohei Hirose
- Department of Gastroenterology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Osamu Dohi
- Department of Gastroenterology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Yoshito Itoh
- Department of Gastroenterology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Daiki Nemoto
- Department of Coloproctology, Aizu Medical Center, Fukushima Medical University, Fukushima, Japan
| | - Kazutomo Togashi
- Department of Coloproctology, Aizu Medical Center, Fukushima Medical University, Fukushima, Japan
| | - Hironori Yamamoto
- Department of Gastroenterology, Jichi Medical University, Tochigi, Japan
| | - Xin Zhu
- Biomedical Information Engineering Lab, The University of Aizu, Fukushima, Japan
| |
Collapse
|
6
|
Castillo-Iturra J, Sánchez A, Balaguer F. Colonoscopic surveillance in Lynch syndrome: guidelines in perspective. Fam Cancer 2024:10.1007/s10689-024-00414-y. [PMID: 39066849 DOI: 10.1007/s10689-024-00414-y] [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: 03/01/2024] [Accepted: 07/03/2024] [Indexed: 07/30/2024]
Abstract
Lynch syndrome predisposes to a high risk of colorectal cancer and colonoscopy remains the primary preventive strategy. The prevention of colorectal cancer through colonoscopy relies on identifying and removing adenomas, the main precursor lesion. Nevertheless, colonoscopy is not an optimal strategy since post-colonoscopy colorectal cancer remains an important issue. In continuation of a 2021 journal review, the present article seeks to offer an updated perspective by examining relevant articles from the past 3 years. We place recent findings in the context of existing guidelines, with a specific focus on colonoscopy surveillance. Key aspects explored include colonoscopy quality standards, timing of initiation, and surveillance intervals. Our review provides a comprehensive analysis of adenoma-related insights in Lynch syndrome, delving into emerging technologies like virtual chromoendoscopy and artificial intelligence-assisted endoscopy. This review aims to contribute valuable insights into the topic of colonoscopy surveillance in Lynch syndrome.
Collapse
Affiliation(s)
- Joaquín Castillo-Iturra
- Department of astroenterology, Hospital Clínic de Barcelona, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Ariadna Sánchez
- Department of astroenterology, Hospital Clínic de Barcelona, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Francesc Balaguer
- Department of astroenterology, Hospital Clínic de Barcelona, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
- Facultat de Medicina i Ciències de la Salud, Universitat de Barcelona (UB), Barcelona, Spain.
| |
Collapse
|
7
|
Lui TKL, Lam CPM, To EWP, Ko MKL, Tsui VWM, Liu KSH, Hui CKY, Cheung MKS, Mak LLY, Hui RWH, Wong SY, Seto WK, Leung WK. Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial. Am J Gastroenterol 2024; 119:1318-1325. [PMID: 38305278 PMCID: PMC11208055 DOI: 10.14309/ajg.0000000000002684] [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: 10/11/2023] [Accepted: 12/19/2023] [Indexed: 02/03/2024]
Abstract
INTRODUCTION Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of various colonic lesions. METHODS This was a 3-arm prospective randomized colonoscopy study involving patients aged 40 years or older. Participants were randomly assigned in a 1:1:1 ratio to undergo Endocuff with AI, AI alone, or standard high-definition (HD) colonoscopy. The primary outcome was adenoma detection rate (ADR) between the Endocuff-AI and AI groups while secondary outcomes included detection rates of polyp (PDR), sessile serrated lesion (sessile detection rate [SDR]), and advanced adenoma (advanced adenoma detection rate) between the 2 groups. RESULTS A total of 682 patients were included (mean age 65.4 years, 52.3% male), with 53.7% undergoing diagnostic colonoscopy. The ADR for the Endocuff-AI, AI, and HD groups was 58.7%, 53.8%, and 46.3%, respectively, while the corresponding PDR was 77.0%, 74.0%, and 61.2%. A significant increase in ADR, PDR, and SDR was observed between the Endocuff-AI and AI groups (ADR difference: 4.9%, 95% CI: 1.4%-8.2%, P = 0.03; PDR difference: 3.0%, 95% CI: 0.4%-5.8%, P = 0.04; SDR difference: 6.4%, 95% CI: 3.4%-9.7%, P < 0.01). Both Endocuff-AI and AI groups had a higher ADR, PDR, SDR, and advanced adenoma detection rate than the HD group (all P < 0.01). DISCUSSION Endocuff in combination with AI further improves various colonic lesion detection rates when compared with AI alone.
Collapse
Affiliation(s)
- Thomas Ka-Luen Lui
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | | | - Elvis Wai-Pan To
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
- Department of Medicine, Tung Wah Hospital, Hong Kong, China.
| | | | | | | | | | - Michael Ka-Shing Cheung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | - Loey Lung-Yi Mak
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | - Rex Wan-Hin Hui
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | - Siu-Yin Wong
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | - Wai Kay Seto
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| | - Wai K. Leung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
- Department of Medicine, Queen Mary Hospital, Hong Kong, China;
| |
Collapse
|
8
|
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.
Collapse
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
| |
Collapse
|
9
|
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; 102 Suppl 1:S66-S71. [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] [MESH Headings] [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.
Collapse
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
| |
Collapse
|
10
|
Maeda Y, Kudo SE, Santacroce G, Ogata N, Misawa M, Iacucci M. Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review. Dig Liver Dis 2024; 56:1119-1125. [PMID: 38643020 DOI: 10.1016/j.dld.2024.04.005] [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: 12/27/2023] [Revised: 03/11/2024] [Accepted: 04/04/2024] [Indexed: 04/22/2024]
Abstract
This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of patients with ulcerative colitis. The use of artificial intelligence (AI) has increased substantially across several medical fields, including gastrointestinal endoscopy. Evidence suggests that it may be helpful to predict histologic remission and relapse, which would be beneficial because current histological diagnosis is limited by the inconvenience of obtaining biopsies and the high cost and time-intensiveness of pathological diagnosis. MEDLINE and the Cochrane Central Register of Controlled Trials were searched for studies published between January 1, 2000, and October 31, 2023. Nine studies fulfilled the selection criteria and were included; five evaluated the prediction of histologic remission, two assessed the prediction of clinical outcomes, and two evaluated both. Seven were prospective observational or cohort studies, while two were retrospective observational studies. No randomized controlled trials were identified. AI-assisted colonoscopy demonstrated sensitivity between 65 %-98 % and specificity values of 80 %-97 % for identifying histologic remission. Furthermore, it was able to predict future relapse in patients with ulcerative colitis. However, several challenges and barriers still exist to its routine clinical application, which should be overcome before the true potential of AI-assisted colonoscopy can be fully realized.
Collapse
Affiliation(s)
- Yasuharu Maeda
- Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan; APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland.
| | - Shin-Ei Kudo
- Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan
| | - Giovanni Santacroce
- APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland
| | - Noriyuki Ogata
- Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan
| | - Masashi Misawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, 35-1 Chigasaki-chuo, Tsuzuki, Yokohama 224-8503, Japan
| | - Marietta Iacucci
- APC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, T12 YT20, Ireland
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|
12
|
Han R, Acosta JN, Shakeri Z, Ioannidis JPA, Topol EJ, Rajpurkar P. Randomised controlled trials evaluating artificial intelligence in clinical practice: a scoping review. Lancet Digit Health 2024; 6:e367-e373. [PMID: 38670745 PMCID: PMC11068159 DOI: 10.1016/s2589-7500(24)00047-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 03/01/2024] [Accepted: 03/04/2024] [Indexed: 04/28/2024]
Abstract
This scoping review of randomised controlled trials on artificial intelligence (AI) in clinical practice reveals an expanding interest in AI across clinical specialties and locations. The USA and China are leading in the number of trials, with a focus on deep learning systems for medical imaging, particularly in gastroenterology and radiology. A majority of trials (70 [81%] of 86) report positive primary endpoints, primarily related to diagnostic yield or performance; however, the predominance of single-centre trials, little demographic reporting, and varying reports of operational efficiency raise concerns about the generalisability and practicality of these results. Despite the promising outcomes, considering the likelihood of publication bias and the need for more comprehensive research including multicentre trials, diverse outcome measures, and improved reporting standards is crucial. Future AI trials should prioritise patient-relevant outcomes to fully understand AI's true effects and limitations in health care.
Collapse
Affiliation(s)
- Ryan Han
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA; University of California Los Angeles-Caltech Medical Scientist Training Program, Los Angeles, CA, USA
| | - Julián N Acosta
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Rad AI, San Francisco, CA, USA
| | - Zahra Shakeri
- Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - John P A Ioannidis
- Stanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, CA, USA; Meta-Research Innovation Center at Stanford, Stanford University, Stanford, CA, USA
| | - Eric J Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA.
| | - Pranav Rajpurkar
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
13
|
Anvari S, Dadgar K, Galts C, Bretthauer M. Gastroenterology/Hepatology: What You May Have Missed in 2023. Ann Intern Med 2024; 177:S27-S36. [PMID: 38621241 DOI: 10.7326/m24-0505] [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: 04/17/2024] Open
Abstract
This article summarizes clinically important gastroenterology developments from 2023 for internal medicine specialists. In colorectal cancer screening, a new RNA fecal screening test is on the horizon, as well as a new analysis on the benefits of using artificial intelligence in screening colonoscopy to detect more polyps. There is new evidence for management of gastrointestinal bleeding, a new drug for treatment of recurrent small-intestinal angiodysplasia, and a new endoscopic treatment method in patients with gastrointestinal tumor bleeding. The authors feature a randomized trial about amitriptyline as treatment for patients with irritable bowel syndrome by primary care providers and bring you news about new biologic agents for inflammatory bowel disease and eosinophilic esophagitis. Finally, they review 2 important articles on new terminology and management of metabolic dysfunction-associated fatty liver disease.
Collapse
Affiliation(s)
- Sama Anvari
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada (S.A., K.D., C.G.)
| | - Kayla Dadgar
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada (S.A., K.D., C.G.)
| | - Ciarán Galts
- Division of Gastroenterology, Department of Medicine, McMaster University, Hamilton, Ontario, Canada (S.A., K.D., C.G.)
| | - Michael Bretthauer
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway (M.B.)
| |
Collapse
|
14
|
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.
Collapse
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
| |
Collapse
|
15
|
Leung WK. Artificial intelligence-assisted assessment for Forrest classification of peptic ulcer bleeding: hype or reality? Endoscopy 2024; 56:343-344. [PMID: 38479415 DOI: 10.1055/a-2277-2035] [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: 04/25/2024]
Affiliation(s)
- Wai K Leung
- Department of Medicine, The University of Hong Kong, Hong Kong, Hong Kong
| |
Collapse
|
16
|
Lee MCM, Parker CH, Liu LWC, Farahvash A, Jeyalingam T. Impact of study design on adenoma detection in the evaluation of artificial intelligence-aided colonoscopy: a systematic review and meta-analysis. Gastrointest Endosc 2024; 99:676-687.e16. [PMID: 38272274 DOI: 10.1016/j.gie.2024.01.021] [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] [Received: 09/09/2023] [Revised: 12/19/2023] [Accepted: 01/10/2024] [Indexed: 01/27/2024]
Abstract
BACKGROUND AND AIMS Randomized controlled trials (RCTs) have reported that artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies-namely, parallel and tandem designs-have been used to evaluate the efficacy of AI-assisted colonoscopy in RCTs. Systematic reviews and meta-analyses have reported a pooled effect that includes both study designs. However, it is unclear whether there are inconsistencies in the reported results of these 2 designs. Here, we aimed to determine whether study characteristics moderate between-trial differences in outcomes when evaluating the effectiveness of AI-assisted polyp detection. METHODS A systematic search of Ovid MEDLINE, Embase, Cochrane Central, Web of Science, and IEEE Xplore was performed through March 1, 2023, for RCTs comparing AI-assisted colonoscopy with routine high-definition colonoscopy in polyp detection. The primary outcome of interest was the impact of study type on the adenoma detection rate (ADR). Secondary outcomes included the impact of the study type on adenomas per colonoscopy and withdrawal time, as well as the impact of geographic location, AI system, and endoscopist experience on ADR. Pooled event analysis was performed using a random-effects model. RESULTS Twenty-four RCTs involving 17,413 colonoscopies (AI assisted: 8680; non-AI assisted: 8733) were included. AI-assisted colonoscopy improved overall ADR (risk ratio [RR], 1.24; 95% confidence interval [CI], 1.17-1.31; I2 = 53%; P < .001). Tandem studies collectively demonstrated improved ADR in AI-aided colonoscopies (RR, 1.18; 95% CI, 1.08-1.30; I2 = 0%; P < .001), as did parallel studies (RR, 1.26; 95% CI, 1.17-1.35; I2 = 62%; P < .001), with no statistical subgroup difference between study design. Both tandem and parallel study designs revealed improvement in adenomas per colonoscopy in AI-aided colonoscopies, but this improvement was more marked among tandem studies (P < .001). AI assistance significantly increased withdrawal times for parallel (P = .002), but not tandem, studies. ADR improvement was more marked among studies conducted in Asia compared to Europe and North America in a subgroup analysis (P = .007). Type of AI system used or endoscopist experience did not affect overall improvement in ADR. CONCLUSIONS Either parallel or tandem study design can capture the improvement in ADR resulting from the use of AI-assisted polyp detection systems. Tandem studies powered to detect differences in endoscopic performance through paired comparison may be a resource-efficient method of evaluating new AI-assisted technologies.
Collapse
Affiliation(s)
- Michelle C M Lee
- Division of Gastroenterology and Hepatology, Department of Medicine, University Health Network, University of Toronto, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Colleen H Parker
- Division of Gastroenterology and Hepatology, Department of Medicine, University Health Network, University of Toronto, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Louis W C Liu
- Division of Gastroenterology and Hepatology, Department of Medicine, University Health Network, University of Toronto, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Armin Farahvash
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Thurarshen Jeyalingam
- Division of Gastroenterology and Hepatology, Department of Medicine, University Health Network, University of Toronto, Toronto, Ontario, Canada; Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
17
|
Mori Y, Patel HK, Repici A, Rex DK, Sharma P, Hassan C. Computer-aided detection for colorectal neoplasia in randomized and non-randomized studies. Endosc Int Open 2024; 12:E598-E599. [PMID: 38654966 PMCID: PMC11039027 DOI: 10.1055/a-2295-2177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 03/20/2024] [Indexed: 04/26/2024] Open
Affiliation(s)
- Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
| | - Harsh K Patel
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, United States
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
- Endoscopy Unit, Humanitas Clinicial and Research Center - IRCCS, Milan, Italy
| | - Douglas K Rex
- Division of Gastroenterology, Indiana University School of Medicine, Indianapolis, United States
| | - Prateek Sharma
- Gastroenterology and Hepatology, University of Kansas Medical Center, Kansas City, United States
- Gastroenterology and Hepatology, Kansas City VA Medical Center and University of Kansas School of Medicine, Kansas City, United States
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
- Endoscopy Unit, Humanitas Clinicial and Research Center - IRCCS, Milan, Italy
| |
Collapse
|
18
|
Campion JR, O'Connor DB, Lahiff C. Human-artificial intelligence interaction in gastrointestinal endoscopy. World J Gastrointest Endosc 2024; 16:126-135. [PMID: 38577646 PMCID: PMC10989254 DOI: 10.4253/wjge.v16.i3.126] [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: 12/31/2023] [Revised: 01/18/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024] Open
Abstract
The number and variety of applications of artificial intelligence (AI) in gastrointestinal (GI) endoscopy is growing rapidly. New technologies based on machine learning (ML) and convolutional neural networks (CNNs) are at various stages of development and deployment to assist patients and endoscopists in preparing for endoscopic procedures, in detection, diagnosis and classification of pathology during endoscopy and in confirmation of key performance indicators. Platforms based on ML and CNNs require regulatory approval as medical devices. Interactions between humans and the technologies we use are complex and are influenced by design, behavioural and psychological elements. Due to the substantial differences between AI and prior technologies, important differences may be expected in how we interact with advice from AI technologies. Human–AI interaction (HAII) may be optimised by developing AI algorithms to minimise false positives and designing platform interfaces to maximise usability. Human factors influencing HAII may include automation bias, alarm fatigue, algorithm aversion, learning effect and deskilling. Each of these areas merits further study in the specific setting of AI applications in GI endoscopy and professional societies should engage to ensure that sufficient emphasis is placed on human-centred design in development of new AI technologies.
Collapse
Affiliation(s)
- John R Campion
- Department of Gastroenterology, Mater Misericordiae University Hospital, Dublin D07 AX57, Ireland
- School of Medicine, University College Dublin, Dublin D04 C7X2, Ireland
| | - Donal B O'Connor
- Department of Surgery, Trinity College Dublin, Dublin D02 R590, Ireland
| | - Conor Lahiff
- Department of Gastroenterology, Mater Misericordiae University Hospital, Dublin D07 AX57, Ireland
- School of Medicine, University College Dublin, Dublin D04 C7X2, Ireland
| |
Collapse
|
19
|
Lau LHS, Ho JCL, Lai JCT, Ho AHY, Wu CWK, Lo VWH, Lai CMS, Scheppach MW, Sia F, Ho KHK, Xiao X, Yip TCF, Lam TYT, Kwok HYH, Chan HCH, Lui RN, Chan TT, Wong MTL, Ho MF, Ko RCW, Hon SF, Chu S, Futaba K, Ng SSM, Yip HC, Tang RSY, Wong VWS, Chan FKL, Chiu PWY. Effect of Real-Time Computer-Aided Polyp Detection System (ENDO-AID) on Adenoma Detection in Endoscopists-in-Training: A Randomized Trial. Clin Gastroenterol Hepatol 2024; 22:630-641.e4. [PMID: 37918685 DOI: 10.1016/j.cgh.2023.10.019] [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: 07/17/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 11/04/2023]
Abstract
BACKGROUND The effect of computer-aided polyp detection (CADe) on adenoma detection rate (ADR) among endoscopists-in-training remains unknown. METHODS We performed a single-blind, parallel-group, randomized controlled trial in Hong Kong between April 2021 and July 2022 (NCT04838951). Eligible subjects undergoing screening/surveillance/diagnostic colonoscopies were randomized 1:1 to receive colonoscopies with CADe (ENDO-AID[OIP-1]) or not (control) during withdrawal. Procedures were performed by endoscopists-in-training with <500 procedures and <3 years' experience. Randomization was stratified by patient age, sex, and endoscopist experience (beginner vs intermediate level, <200 vs 200-500 procedures). Image enhancement and distal attachment devices were disallowed. Subjects with incomplete colonoscopies or inadequate bowel preparation were excluded. Treatment allocation was blinded to outcome assessors. The primary outcome was ADR. Secondary outcomes were ADR for different adenoma sizes and locations, mean number of adenomas, and non-neoplastic resection rate. RESULTS A total of 386 and 380 subjects were randomized to CADe and control groups, respectively. The overall ADR was significantly higher in the CADe group than in the control group (57.5% vs 44.5%; adjusted relative risk, 1.41; 95% CI, 1.17-1.72; P < .001). The ADRs for <5 mm (40.4% vs 25.0%) and 5- to 10-mm adenomas (36.8% vs 29.2%) were higher in the CADe group. The ADRs were higher in the CADe group in both the right colon (42.0% vs 30.8%) and left colon (34.5% vs 27.6%), but there was no significant difference in advanced ADR. The ADRs were higher in the CADe group among beginner (60.0% vs 41.9%) and intermediate-level (56.5% vs 45.5%) endoscopists. Mean number of adenomas (1.48 vs 0.86) and non-neoplastic resection rate (52.1% vs 35.0%) were higher in the CADe group. CONCLUSIONS Among endoscopists-in-training, the use of CADe during colonoscopies was associated with increased overall ADR. (ClinicalTrials.gov, Number: NCT04838951).
Collapse
Affiliation(s)
- Louis H S Lau
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR; Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR
| | - Jacky C L Ho
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Jimmy C T Lai
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Agnes H Y Ho
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Claudia W K Wu
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Vincent W H Lo
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Carol M S Lai
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Markus W Scheppach
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; Gastroenterology, Faculty of Medicine, University of Augsburg, Augsburg, Germany
| | - Felix Sia
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR
| | - Kyle H K Ho
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR
| | - Xiang Xiao
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; Medical Data Analytic Centre, The Chinese University of Hong Kong, Hong Kong SAR
| | - Terry C F Yip
- Medical Data Analytic Centre, The Chinese University of Hong Kong, Hong Kong SAR
| | - Thomas Y T Lam
- Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Hong Kong SAR
| | - Hanson Y H Kwok
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Heyson C H Chan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Rashid N Lui
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Ting-Ting Chan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Marc T L Wong
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Man-Fung Ho
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Rachel C W Ko
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Sok-Fei Hon
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Simon Chu
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Koari Futaba
- Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Simon S M Ng
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Hon-Chi Yip
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR
| | - Raymond S Y Tang
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR; Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR
| | - Vincent W S Wong
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR; Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR
| | - Francis K L Chan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR; Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; State Key Laboratory of Digestive Disease, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong SAR
| | - Philip W Y Chiu
- Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong SAR; Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR.
| |
Collapse
|
20
|
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
| |
Collapse
|
21
|
Khalaf K, Fujiyoshi MRA, Spadaccini M, Rizkala T, Ramai D, Colombo M, Fugazza A, Facciorusso A, Carrara S, Hassan C, Repici A. From Staining Techniques to Artificial Intelligence: A Review of Colorectal Polyps Characterization. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:89. [PMID: 38256350 PMCID: PMC10818333 DOI: 10.3390/medicina60010089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 12/24/2023] [Accepted: 12/26/2023] [Indexed: 01/24/2024]
Abstract
This review article provides a comprehensive overview of the evolving techniques in image-enhanced endoscopy (IEE) for the characterization of colorectal polyps, and the potential of artificial intelligence (AI) in revolutionizing the diagnostic accuracy of endoscopy. We discuss the historical use of dye-spray and virtual chromoendoscopy for the characterization of colorectal polyps, which are now being replaced with more advanced technologies. Specifically, we focus on the application of AI to create a "virtual biopsy" for the detection and characterization of colorectal polyps, with potential for replacing histopathological diagnosis. The incorporation of AI has the potential to provide an evolutionary learning system that aids in the diagnosis and management of patients with the best possible outcomes. A detailed analysis of the literature supporting AI-assisted diagnostic techniques for the detection and characterization of colorectal polyps, with a particular emphasis on AI's characterization mechanism, is provided. The benefits of AI over traditional IEE techniques, including the reduction in human error in diagnosis, and its potential to provide an accurate diagnosis with similar accuracy to the gold standard are presented. However, the need for large-scale testing of AI in clinical practice and the importance of integrating patient data into the diagnostic process are acknowledged. In conclusion, the constant evolution of IEE technology and the potential for AI to revolutionize the field of endoscopy in the future are presented.
Collapse
Affiliation(s)
- Kareem Khalaf
- Division of Gastroenterology, St. Michael’s Hospital, University of Toronto, Toronto, ON M5B 1T8, Canada; (K.K.); (M.R.A.F.)
| | - Mary Raina Angeli Fujiyoshi
- Division of Gastroenterology, St. Michael’s Hospital, University of Toronto, Toronto, ON M5B 1T8, Canada; (K.K.); (M.R.A.F.)
- Digestive Diseases Center, Showa University Koto Toyosu Hospital, Tokyo 135-8577, Japan
| | - Marco Spadaccini
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
- Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
| | - Tommy Rizkala
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
- Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
| | - Daryl Ramai
- Gastroenterology and Hepatology, University of Utah Health, Salt Lake City, UT 84132, USA;
| | - Matteo Colombo
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
| | - Alessandro Fugazza
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
| | - Antonio Facciorusso
- Department of Endoscopy, Section of Gastroenterology, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy;
| | - Silvia Carrara
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
| | - Cesare Hassan
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
- Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
| | - Alessandro Repici
- Department of Endoscopy, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy; (T.R.); (M.C.); (A.F.); (S.C.); (C.H.); (A.R.)
- Department of Biomedical Sciences, Humanitas University, 20089 Rozzano, Italy
| |
Collapse
|
22
|
Lou S, Du F, Song W, Xia Y, Yue X, Yang D, Cui B, Liu Y, Han P. Artificial intelligence for colorectal neoplasia detection during colonoscopy: a systematic review and meta-analysis of randomized clinical trials. EClinicalMedicine 2023; 66:102341. [PMID: 38078195 PMCID: PMC10698672 DOI: 10.1016/j.eclinm.2023.102341] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 05/11/2024] Open
Abstract
BACKGROUND The use of artificial intelligence (AI) in detecting colorectal neoplasia during colonoscopy holds the potential to enhance adenoma detection rates (ADRs) and reduce adenoma miss rates (AMRs). However, varied outcomes have been observed across studies. Thus, this study aimed to evaluate the potential advantages and disadvantages of employing AI-aided systems during colonoscopy. METHODS Using Medical Subject Headings (MeSH) terms and keywords, a comprehensive electronic literature search was performed of the Embase, Medline, and the Cochrane Library databases from the inception of each database until October 04, 2023, in order to identify randomized controlled trials (RCTs) comparing AI-assisted with standard colonoscopy for detecting colorectal neoplasia. Primary outcomes included AMR, ADR, and adenomas detected per colonoscopy (APC). Secondary outcomes comprised the poly missed detection rate (PMR), poly detection rate (PDR), and poly detected per colonoscopy (PPC). We utilized random-effects meta-analyses with Hartung-Knapp adjustment to consolidate results. The prediction interval (PI) and I2 statistics were utilized to quantify between-study heterogeneity. Moreover, meta-regression and subgroup analyses were performed to investigate the potential sources of heterogeneity. This systematic review and meta-analysis is registered with PROSPERO (CRD42023428658). FINDINGS This study encompassed 33 trials involving 27,404 patients. Those undergoing AI-aided colonoscopy experienced a significant decrease in PMR (RR, 0.475; 95% CI, 0.294-0.768; I2 = 87.49%) and AMR (RR, 0.495; 95% CI, 0.390-0.627; I2 = 48.76%). Additionally, a significant increase in PDR (RR, 1.238; 95% CI, 1.158-1.323; I2 = 81.67%) and ADR (RR, 1.242; 95% CI, 1.159-1.332; I2 = 78.87%), along with a significant increase in the rates of PPC (IRR, 1.388; 95% CI, 1.270-1.517; I2 = 91.99%) and APC (IRR, 1.390; 95% CI, 1.277-1.513; I2 = 86.24%), was observed. This resulted in 0.271 more PPCs (95% CI, 0.144-0.259; I2 = 65.61%) and 0.202 more APCs (95% CI, 0.144-0.259; I2 = 68.15%). INTERPRETATION AI-aided colonoscopy significantly enhanced the detection of colorectal neoplasia detection, likely by reducing the miss rate. However, future studies should focus on evaluating the cost-effectiveness and long-term benefits of AI-aided colonoscopy in reducing cancer incidence. FUNDING This work was supported by the Heilongjiang Provincial Natural Science Foundation of China (LH2023H096), the Postdoctoral research project in Heilongjiang Province (LBH-Z22210), the National Natural Science Foundation of China's General Program (82072640) and the Outstanding Youth Project of Heilongjiang Natural Science Foundation (YQ2021H023).
Collapse
Affiliation(s)
- Shenghan Lou
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Fenqi Du
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Wenjie Song
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Yixiu Xia
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Xinyu Yue
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Da Yang
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Binbin Cui
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Yanlong Liu
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| | - Peng Han
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
- Key Laboratory of Tumor Immunology in Heilongjiang, No.150 Haping Road, Harbin, Heilongjiang, 150081, China
| |
Collapse
|
23
|
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
|