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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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Ferlitsch M, Hassan C, Bisschops R, Bhandari P, Dinis-Ribeiro M, Risio M, Paspatis GA, Moss A, Libânio D, Lorenzo-Zúñiga V, Voiosu AM, Rutter MD, Pellisé M, Moons LMG, Probst A, Awadie H, Amato A, Takeuchi Y, Repici A, Rahmi G, Koecklin HU, Albéniz E, Rockenbauer LM, Waldmann E, Messmann H, Triantafyllou K, Jover R, Gralnek IM, Dekker E, Bourke MJ. Colorectal polypectomy and endoscopic mucosal resection: European Society of Gastrointestinal Endoscopy (ESGE) Guideline - Update 2024. Endoscopy 2024; 56:516-545. [PMID: 38670139 DOI: 10.1055/a-2304-3219] [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: 04/28/2024]
Abstract
1: ESGE recommends cold snare polypectomy (CSP), to include a clear margin of normal tissue (1-2 mm) surrounding the polyp, for the removal of diminutive polyps (≤ 5 mm).Strong recommendation, high quality of evidence. 2: ESGE recommends against the use of cold biopsy forceps excision because of its high rate of incomplete resection.Strong recommendation, moderate quality of evidence. 3: ESGE recommends CSP, to include a clear margin of normal tissue (1-2 mm) surrounding the polyp, for the removal of small polyps (6-9 mm).Strong recommendation, high quality of evidence. 4: ESGE recommends hot snare polypectomy for the removal of nonpedunculated adenomatous polyps of 10-19 mm in size.Strong recommendation, high quality of evidence. 5: ESGE recommends conventional (diathermy-based) endoscopic mucosal resection (EMR) for large (≥ 20 mm) nonpedunculated adenomatous polyps (LNPCPs).Strong recommendation, high quality of evidence. 6: ESGE suggests that underwater EMR can be considered an alternative to conventional hot EMR for the treatment of adenomatous LNPCPs.Weak recommendation, moderate quality of evidence. 7: Endoscopic submucosal dissection (ESD) may also be suggested as an alternative for removal of LNPCPs of ≥ 20 mm in selected cases and in high-volume centers.Weak recommendation, low quality evidence. 8: ESGE recommends that, after piecemeal EMR of LNPCPs by hot snare, the resection margins should be treated by thermal ablation using snare-tip soft coagulation to prevent adenoma recurrence.Strong recommendation, high quality of evidence. 9: ESGE recommends (piecemeal) cold snare polypectomy or cold EMR for SSLs of all sizes without suspected dysplasia.Strong recommendation, moderate quality of evidence. 10: ESGE recommends prophylactic endoscopic clip closure of the mucosal defect after EMR of LNPCPs in the right colon to reduce to reduce the risk of delayed bleeding.Strong recommendation, high quality of evidence. 11: ESGE recommends that en bloc resection techniques, such as en bloc EMR, ESD, endoscopic intermuscular dissection, endoscopic full-thickness resection, or surgery should be the techniques of choice in cases with suspected superficial invasive carcinoma, which otherwise cannot be removed en bloc by standard polypectomy or EMR.Strong recommendation, moderate quality of evidence.
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Affiliation(s)
- Monika Ferlitsch
- Department of Internal Medicine III, Division of Gastroenterology and Hepatology, Medical University of Vienna, Vienna, Austria
- Department of Gastroenterology, Evangelical Hospital, Vienna, Austria
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Raf Bisschops
- Department of Gastroenterology and Hepatology, University Hospitals Leuven, TARGID, KU Leuven, Leuven, Belgium
| | - Pradeep Bhandari
- Endoscopy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
| | - Mário Dinis-Ribeiro
- Department of Gastroenterology, Portuguese Oncology Institute of Porto, Porto, Portugal
- MEDCIDS/Faculty of Medicine, University of Porto, Porto, Portugal
- Porto Comprehensive Cancer Center (Porto.CCC) and RISE@CI-IPOP (Health Research Network), Porto, Portugal
| | - Mauro Risio
- Department of Pathology, Institute for Cancer Research and Treatment, Candiolo, Turin, Italy
| | - Gregorios A Paspatis
- Gastroenterology Department, Venizeleio General Hospital, Heraklion, Crete, Greece
| | - Alan Moss
- Department of Gastroenterology, Western Health, Melbourne, Australia
- Department of Medicine, Western Health, Melbourne Medical School, University of Melbourne, Melbourne, Australia
| | - Diogo Libânio
- Department of Gastroenterology, Portuguese Oncology Institute of Porto, Porto, Portugal
- MEDCIDS/Faculty of Medicine, University of Porto, Porto, Portugal
- Porto Comprehensive Cancer Center (Porto.CCC) and RISE@CI-IPOP (Health Research Network), Porto, Portugal
| | - Vincente Lorenzo-Zúñiga
- Endoscopy Unit, La Fe University and Polytechnic Hospital / IISLaFe, Valencia, Spain
- Department of Medicine, Catholic University of Valencia, Valencia, Spain
| | - Andrei M Voiosu
- Gastroenterology Department, Colentina Clinical Hospital, Bucharest, Romania
- Internal Medicine and Gastroenterology, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Matthew D Rutter
- Department of Gastroenterology, North Tees and Hartlepool NHS Foundation Trust, Stockton-on-Tees, UK
- Department of Gastroenterology, Faculty of Medical Sciences, Newcastle University, Newcastle-upon-Tyne, UK
| | - Maria Pellisé
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Leon M G Moons
- III Medizinische Klinik, Universitätsklinikum Augsburg, Augsburg, Germany
| | - Andreas Probst
- Department of Gastroenterology, University Hospital of Augsburg, Augsburg, Germany
| | - Halim Awadie
- Ellen and Pinchas Mamber Institute of Gastroenterology and Hepatology, Emek Medical Center, Afula, Israel
| | - Arnaldo Amato
- Digestive Endoscopy and Gastroenterology Department, Ospedale A. Manzoni, Lecco, Italy
| | - Yoji Takeuchi
- Department of Gastroenterology and Hepatology, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
- Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Gabriel Rahmi
- Hepatogastroenterology and Endoscopy Department, Hôpital européen Georges Pompidou, Paris, France
- Laboratoire de Recherches Biochirurgicales, APHP-Centre Université de Paris, Paris, France
| | - Hugo U Koecklin
- Hospital Universitari Germans Trias i Pujol, Badalona, Spain
- Teknon Medical Center, Barcelona, Spain
| | - Eduardo Albéniz
- Gastroenterology Department, Hospital Universitario de Navarra (HUN); Navarrabiomed, Universidad Pública de Navarra (UPNA), IdiSNA, Pamplona, Spain
| | - Lisa-Maria Rockenbauer
- Department of Internal Medicine III, Division of Gastroenterology and Hepatology, Medical University of Vienna, Vienna, Austria
| | - Elisabeth Waldmann
- Department of Internal Medicine III, Division of Gastroenterology and Hepatology, Medical University of Vienna, Vienna, Austria
| | - Helmut Messmann
- III Medizinische Klinik, Universitätsklinikum Augsburg, Augsburg, Germany
| | - Konstantinos Triantafyllou
- Hepatogastroenterology Unit, Second Department of Propaedeutic Internal Medicine, Medical School, National and Kapodastrian University of Athens, Attikon University General Hospital, Athens, Greece
| | - Rodrigo Jover
- Servicio de Medicina Digestiva, Hospital General Universitario Dr. Balmis, Instituto de Investigación Sanitaria ISABIAL, Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain
| | - Ian M Gralnek
- Ellen and Pinchas Mamber Institute of Gastroenterology and Hepatology, Emek Medical Center, Afula, Israel
- Rappaport Faculty of Medicine Technion Israel Institute of Technology, Haifa, Israel
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Michael J Bourke
- Department of Gastroenterology and Hepatology, Westmead Hospital, Sydney, Australia
- University of Sydney, Sydney, Australia
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Hassan C, Misawa M, Rizkala T, Mori Y, Sultan S, Facciorusso A, Antonelli G, Spadaccini M, Houwen BBSL, Rondonotti E, Patel H, Khalaf K, Li JW, Fernandez GM, Bhandari P, Dekker E, Gross S, Berzin T, Vandvik PO, Correale L, Kudo SE, Sharma P, Rex DK, Repici A, Foroutan F. Computer-Aided Diagnosis for Leaving Colorectal Polyps In Situ : A Systematic Review and Meta-analysis. Ann Intern Med 2024; 177:919-928. [PMID: 38768453 DOI: 10.7326/m23-2865] [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: 05/22/2024] Open
Abstract
BACKGROUND Computer-aided diagnosis (CADx) allows prediction of polyp histology during colonoscopy, which may reduce unnecessary removal of nonneoplastic polyps. However, the potential benefits and harms of CADx are still unclear. PURPOSE To quantify the benefit and harm of using CADx in colonoscopy for the optical diagnosis of small (≤5-mm) rectosigmoid polyps. DATA SOURCES Medline, Embase, and Scopus were searched for articles published before 22 December 2023. STUDY SELECTION Histologically verified diagnostic accuracy studies that evaluated the real-time performance of physicians in predicting neoplastic change of small rectosigmoid polyps without or with CADx assistance during colonoscopy. DATA EXTRACTION The clinical benefit and harm were estimated on the basis of accuracy values of the endoscopist before and after CADx assistance. The certainty of evidence was assessed using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework. The outcome measure for benefit was the proportion of polyps predicted to be nonneoplastic that would avoid removal with the use of CADx. The outcome measure for harm was the proportion of neoplastic polyps that would be not resected and left in situ due to an incorrect diagnosis with the use of CADx. Histology served as the reference standard for both outcomes. DATA SYNTHESIS Ten studies, including 3620 patients with 4103 small rectosigmoid polyps, were analyzed. The studies that assessed the performance of CADx alone (9 studies; 3237 polyps) showed a sensitivity of 87.3% (95% CI, 79.2% to 92.5%) and specificity of 88.9% (CI, 81.7% to 93.5%) in predicting neoplastic change. In the studies that compared histology prediction performance before versus after CADx assistance (4 studies; 2503 polyps), there was no difference in the proportion of polyps predicted to be nonneoplastic that would avoid removal (55.4% vs. 58.4%; risk ratio [RR], 1.06 [CI, 0.96 to 1.17]; moderate-certainty evidence) or in the proportion of neoplastic polyps that would be erroneously left in situ (8.2% vs. 7.5%; RR, 0.95 [CI, 0.69 to 1.33]; moderate-certainty evidence). LIMITATION The application of optical diagnosis was only simulated, potentially altering the decision-making process of the operator. CONCLUSION Computer-aided diagnosis provided no incremental benefit or harm in the management of small rectosigmoid polyps during colonoscopy. PRIMARY FUNDING SOURCE European Commission. (PROSPERO: CRD42023402197).
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Affiliation(s)
- Cesare Hassan
- Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, and Humanitas Clinical and Research Center IRCCS, Endoscopy Unit, Rozzano, Italy (C.H., M.S., A.R.)
| | - Masashi Misawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan (M.M., S.K.)
| | - Tommy Rizkala
- Humanitas Clinical and Research Center IRCCS, Endoscopy Unit, Rozzano, Italy (T.R., L.C.)
| | - Yuichi Mori
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan; University of Oslo, Clinical Effectiveness Research Group, and Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway (Y.M.)
| | - Shahnaz Sultan
- Division of Gastroenterology, Hepatology, and Nutrition, University of Minnesota, and VA Health Care System, Minneapolis, Minnesota (S.S.)
| | - Antonio Facciorusso
- University of Foggia, Department of Medical Sciences, Section of Gastroenterology, Foggia, Italy (A.F.)
| | - Giulio Antonelli
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli, Ariccia, and Department of Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Rome, Italy (G.A.)
| | - Marco Spadaccini
- Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, and Humanitas Clinical and Research Center IRCCS, Endoscopy Unit, Rozzano, Italy (C.H., M.S., A.R.)
| | - Britt B S L Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands (B.B.S.L.H.)
| | | | - Harsh Patel
- Kansas City VA Medical Center, Gastroenterology and Hepatology, Kansas City, Missouri (H.P., P.S.)
| | - Kareem Khalaf
- Division of Gastroenterology, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada (K.K.)
| | - James Weiquan Li
- Department of Gastroenterology and Hepatology, Changi General Hospital, Singapore Health Services, and Duke-NUS Academic Medicine Centre, Singapore Health Services, Singapore (J.W.L.)
| | - Gloria M Fernandez
- Endoscopy Unit, Gastroenterology Department, Clinical Institute of Digestive and Metabolic Disease, Hospital Clínic de Barcelona, University of Barcelona, Barcelona, Spain (G.M.F.)
| | - Pradeep Bhandari
- Queen Alexandra Hospital, Department of Gastroenterology, Portsmouth, United Kingdom (P.B.)
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, and Bergman Clinics Maag and Darm Amsterdam, Amsterdam, the Netherlands (E.D.)
| | - Seth Gross
- Department of Gastroenterology, Tisch Hospital, New York University Langone Medical Center, New York, New York (S.G.)
| | - Tyler Berzin
- Center for Advanced Endoscopy, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (T.B.)
| | - Per Olav Vandvik
- Department of Medicine, Lovisenberg Diaconal Hospital, Oslo, Norway (P.O.V.)
| | - Loredana Correale
- Humanitas Clinical and Research Center IRCCS, Endoscopy Unit, Rozzano, Italy (T.R., L.C.)
| | - Shin-Ei Kudo
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan (M.M., S.K.)
| | - Prateek Sharma
- Kansas City VA Medical Center, Gastroenterology and Hepatology, Kansas City, Missouri (H.P., P.S.)
| | - Douglas K Rex
- Indiana University School of Medicine, Division of Gastroenterology, Indianapolis, Indiana (D.K.R.)
| | - Alessandro Repici
- Humanitas University, Department of Biomedical Sciences, Pieve Emanuele, and Humanitas Clinical and Research Center IRCCS, Endoscopy Unit, Rozzano, Italy (C.H., M.S., A.R.)
| | - Farid Foroutan
- Ted Rogers Centre for Heart Research, University Health Network, Toronto, Ontario, Canada (F.F.)
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4
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Cassinotti A, Duca P, Maconi G, Beretta E, Sampietro GM, Pellegrinelli A, Nebuloni M, Ardizzone S. Accuracy of optical diagnosis with narrow band imaging in the surveillance of ulcerative colitis: a prospective study comparing Kudo, Kudo-IBD and NICE classifications. Int J Colorectal Dis 2024; 39:77. [PMID: 38782770 PMCID: PMC11116216 DOI: 10.1007/s00384-024-04635-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2024] [Indexed: 05/25/2024]
Abstract
PURPOSE The diagnostic accuracy of Narrow Band Imaging (NBI) in the endoscopic surveillance of ulcerative colitis (UC) has been disappointing in most trials which used the Kudo classification. We aim to compare the performance of NBI in the lesion characterization of UC, when applied according to three different classifications (NICE, Kudo, Kudo-IBD). METHODS In a prospective, real-life study, all visible lesions found during consecutive surveillance colonoscopies with NBI (Exera-II CV-180) for UC were classified as suspected or non-suspected for neoplasia according to the NICE, Kudo and Kudo-IBD criteria. The sensitivity (SE), specificity (SP), positive (+LR) and negative (-LR) likelihood ratios of the three classifications were calculated, using histology as the reference standard. RESULTS 394 lesions (mean size 6 mm, range 2-40 mm) from 84 patients were analysed. Twenty-one neoplastic (5%), 49 hyperplastic (12%), and 324 inflammatory (82%) lesions were found. The diagnostic accuracy of the NICE, Kudo and Kudo-IBD classifications were, respectively: SE 76%-71%-86%; SP 55-69%-79% (p < 0.05 Kudo-IBD vs. both Kudo and NICE); +LR 1.69-2.34-4.15 (p < 0.05 Kudo-IBD vs. both Kudo and NICE); -LR 0.43-0.41-0.18. CONCLUSION The diagnostic accuracy of NBI in the differentiation of neoplastic and non-neoplastic lesions in UC is low if used with conventional classifications of the general population, but it is significantly better with the modified Kudo classification specific for UC.
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Affiliation(s)
- Andrea Cassinotti
- Gastroenterology Unit, ASST Fatebenefratelli Sacco, Luigi Sacco University Hospital, Milan, Italy
- Gastroenterology and Digestive Endoscopy Unit, ASST Sette Laghi, Varese, Italy
| | | | - Giovanni Maconi
- Gastroenterology Unit, ASST Fatebenefratelli Sacco, Luigi Sacco University Hospital, Milan, Italy.
- Department of Biochemical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy.
| | - Elena Beretta
- Gastroenterology Unit, ASST Fatebenefratelli Sacco, Luigi Sacco University Hospital, Milan, Italy
| | | | | | - Manuela Nebuloni
- Department of Biochemical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
- Pathology Unit, ASST Fatebenefratelli Sacco, Luigi Sacco University Hospital, Milan, Italy
| | - Sandro Ardizzone
- Gastroenterology Unit, ASST Fatebenefratelli Sacco, Luigi Sacco University Hospital, Milan, Italy
- Department of Biochemical and Clinical Sciences "L. Sacco", University of Milan, Milan, Italy
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Cheng Y, Li L, Bi Y, Su S, Zhang B, Feng X, Wang N, Zhang W, Yao Y, Ru N, Xiang J, Sun L, Hu K, Wen F, Wang Z, Bai L, Wang X, Wang R, Lv X, Wang P, Meng F, Xiao W, Linghu E, Chai N. Computer-aided diagnosis system for optical diagnosis of colorectal polyps under white light imaging. Dig Liver Dis 2024:S1590-8658(24)00723-0. [PMID: 38744557 DOI: 10.1016/j.dld.2024.04.023] [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: 12/31/2023] [Revised: 03/21/2024] [Accepted: 04/23/2024] [Indexed: 05/16/2024]
Abstract
OBJECTIVES This study presents a novel computer-aided diagnosis (CADx) designed for optically diagnosing colorectal polyps using white light imaging (WLI).We aimed to evaluate the effectiveness of the CADx and its auxiliary role among endoscopists with different levels of expertise. METHODS We collected 2,324 neoplastic and 3,735 nonneoplastic polyp WLI images for model training, and 838 colorectal polyp images from 740 patients for model validation. We compared the diagnostic accuracy of the CADx with that of 15 endoscopists under WLI and narrow band imaging (NBI). The auxiliary benefits of CADx for endoscopists of different experience levels and for identifying different types of colorectal polyps was also evaluated. RESULTS The CADx demonstrated an optical diagnostic accuracy of 84.49%, showing considerable superiority over all endoscopists, irrespective of whether WLI or NBI was used (P < 0.001). Assistance from the CADx significantly improved the diagnostic accuracy of the endoscopists from 68.84% to 77.49% (P = 0.001), with the most significant impact observed among novice endoscopists. Notably, novices using CADx-assisted WLI outperform junior and expert endoscopists without such assistance. CONCLUSIONS The CADx demonstrated a crucial role in substantially enhancing the precision of optical diagnosis for colorectal polyps under WLI and showed the greatest auxiliary benefits for novice endoscopists.
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Affiliation(s)
- Yaxuan Cheng
- Chinese PLA Medical School, Beijing, 100853, PR China; Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Longsong Li
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Yawei Bi
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Song Su
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Bo Zhang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Xiuxue Feng
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Nanjun Wang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Wengang Zhang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Yi Yao
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Nan Ru
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Jingyuan Xiang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Lihua Sun
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Kang Hu
- Department of Gastroenterology, The 987 Hospital of PLA Joint Logistic Support Force, Baoji, 721004, PR China
| | - Feng Wen
- Department of Gastroenterology, General Hospital of Central Theater Command of PLA,Wuhan 430070, PR China
| | - Zixin Wang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Lu Bai
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Xueting Wang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Runzi Wang
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Xingping Lv
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Pengju Wang
- Chinese PLA Medical School, Beijing, 100853, PR China; Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China
| | - Fanqi Meng
- Medical Department, HighWise Medical Technology Co, Ltd, Changsha, 410000, PR China
| | - Wen Xiao
- Medical Department, HighWise Medical Technology Co, Ltd, Changsha, 410000, PR China
| | - Enqiang Linghu
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China.
| | - Ningli Chai
- Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing, 100853, PR China.
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6
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López-Serrano A, Voces A, Lorente JR, Santonja FJ, Algarra A, Latorre P, Del Pozo P, Paredes JM. Artificial intelligence for dysplasia detection during surveillance colonoscopy in patients with ulcerative colitis: A cross-sectional, non-inferiority, diagnostic test comparison study. GASTROENTEROLOGIA Y HEPATOLOGIA 2024:S0210-5705(24)00168-7. [PMID: 38740327 DOI: 10.1016/j.gastrohep.2024.502210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 05/03/2024] [Accepted: 05/03/2024] [Indexed: 05/16/2024]
Abstract
BACKGROUND AND STUDY AIM High-definition virtual chromoendoscopy, along with targeted biopsies, is recommended for dysplasia surveillance in ulcerative colitis patients at risk for colorectal cancer. Computer-aided detection (CADe) systems aim to improve colonic adenoma detection, however their efficacy in detecting polyps and adenomas in this context remains unclear. This study evaluates the CADe Discovery™ system's effectiveness in detecting colonic dysplasia in ulcerative colitis patients at risk for colorectal cancer. PATIENTS AND METHODS A prospective cross-sectional, non-inferiority, diagnostic test comparison study was conducted on ulcerative colitis patients undergoing colorectal cancer surveillance colonoscopy between January 2021 and April 2021. Patients underwent virtual chromoendoscopy (VCE) with iSCAN 1 and 3 with optical enhancement. One endoscopist, blinded to CADe Discovery™ system results, examined colon sections, while a second endoscopist concurrently reviewed CADe images. Suspicious areas detected by both techniques underwent resection. Proportions of dysplastic lesions and patients with dysplasia detected by VCE or CADe were calculated. RESULTS Fifty-two patients were included, and 48 lesions analyzed. VCE and CADe each detected 9 cases of dysplasia (21.4% and 20.0%, respectively; p=0.629) in 8 patients and 7 patients (15.4% vs. 13.5%, respectively; p=0.713). Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy for dysplasia detection using VCE or CADe were 90% and 90%, 13% and 5%, 21% and 2%, 83% and 67%, and 29.2% and 22.9%, respectively. CONCLUSIONS The CADe Discovery™ system shows similar diagnostic performance to VCE with iSCAN in detecting colonic dysplasia in ulcerative colitis patients at risk for colorectal cancer.
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Affiliation(s)
- Antonio López-Serrano
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain; Department of Medicine, Universitat de Valencia, Valencia, Spain.
| | - Alba Voces
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
| | - José Ramón Lorente
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
| | | | - Angela Algarra
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
| | - Patricia Latorre
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
| | - Pablo Del Pozo
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
| | - José María Paredes
- Gastroenterology Department, Hospital Universitari Dr. Peset, Valencia, Spain
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7
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Safavian N, Toh SKC, Pani M, Lee R. Enhancing endoscopic measurement: validating a quantitative method for polyp size and location estimation in upper gastrointestinal endoscopy. Surg Endosc 2024; 38:2505-2514. [PMID: 38467860 PMCID: PMC11078852 DOI: 10.1007/s00464-024-10758-2] [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: 11/26/2023] [Accepted: 02/16/2024] [Indexed: 03/13/2024]
Abstract
BACKGROUND Accurate measurement of polyps size is crucial in predicting malignancy, planning relevant intervention strategies and surveillance schedules. Endoscopists' visual estimations can lack precision. This study builds on our prior research, with the aim to evaluate a recently developed quantitative method to measure the polyp size and location accurately during a simulated endoscopy session. METHODS The quantitative method merges information about endoscopic positions obtained from an electromagnetic tracking sensor, with corresponding points on the images of the segmented polyp border. This yields real-scale 3D coordinates of the border of the polyp. By utilising the sensor, positions of any anatomical landmarks are attainable, enabling the estimation of a polyp's location relative to them. To verify the method's reliability and accuracy, simulated endoscopies were conducted in pig stomachs, where polyps were artificially created and assessed in a test-retest manner. The polyp measurements were subsequently compared against clipper measurements. RESULTS The average size of the fifteen polyps evaluated was approximately 12 ± 4.3 mm, ranging from 5 to 20 mm. The test-retest reliability, measured by the Intraclass Correlation Coefficient (ICC) for polyp size estimation, demonstrated an absolute agreement of 0.991 (95% CI 0.973-0.997, p < 0.05). Bland & Altman analysis revealed a mean estimation difference of - 0.17 mm (- 2.03%) for polyp size and, a mean difference of - 0.4 mm (- 0.21%) for polyp location. Both differences were statistically non-significant (p > 0.05). When comparing the proposed method with calliper measurements, the Bland & Altman plots showed 95% of size estimation differences between - 1.4 and 1.8 mm (- 13 to 17.4%) which was not significant (p > 0.05). CONCLUSIONS The proposed method of measurements of polyp size and location was found to be highly accurate, offering great potential for clinical implementation to improve polyp assessment. This level of performance represents a notable improvement over visual estimation technique used in clinical practice.
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Affiliation(s)
| | - Simon K C Toh
- Department of Upper GI Surgery, Queen Alexandra Hospital, Portsmouth Hospital University NHS Trust, Portsmouth, UK
| | - Martino Pani
- Faculty of Technology, University of Portsmouth, Portsmouth, UK
| | - Raymond Lee
- Faculty of Technology, University of Portsmouth, Portsmouth, UK.
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8
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Rondonotti E, Bergna IMB, Paggi S, Amato A, Andrealli A, Scardino G, Tamanini G, Lenoci N, Mandelli G, Terreni N, Rocchetto SI, Piagnani A, Di Paolo D, Bina N, Filippi E, Ambrosiani L, Hassan C, Correale L, Radaelli F. White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice. Endosc Int Open 2024; 12:E676-E683. [PMID: 38774861 PMCID: PMC11108657 DOI: 10.1055/a-2303-0922] [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: 07/05/2023] [Accepted: 04/04/2024] [Indexed: 05/24/2024] Open
Abstract
Background and study aims Artificial Intelligence (AI) systems could make the optical diagnosis (OD) of diminutive colorectal polyps (DCPs) more reliable and objective. This study was aimed at prospectively evaluating feasibility and diagnostic performance of AI-standalone and AI-assisted OD of DCPs in a real-life setting by using a white light-based system (GI Genius, Medtronic Co, Minneapolis, Minnesota, United States). Patients and methods Consecutive colonoscopy outpatients with at least one DCP were evaluated by 11 endoscopists (5 experts and 6 non-experts in OD). DCPs were classified in real time by AI (AI-standalone OD) and by the endoscopist with the assistance of AI (AI-assisted OD), with histopathology as the reference standard. Results Of the 480 DCPs, AI provided the outcome "adenoma" or "non-adenoma" in 81.4% (95% confidence interval [CI]: 77.5-84.6). Sensitivity, specificity, positive and negative predictive value, and accuracy of AI-standalone OD were 97.0% (95% CI 94.0-98.6), 38.1% (95% CI 28.9-48.1), 80.1% (95% CI 75.2-84.2), 83.3% (95% CI 69.2-92.0), and 80.5% (95% CI 68.7-82.8%), respectively. Compared with AI-standalone, the specificity of AI-assisted OD was significantly higher (58.9%, 95% CI 49.7-67.5) and a trend toward an increase was observed for other diagnostic performance measures. Overall accuracy and negative predictive value of AI-assisted OD for experts and non-experts were 85.8% (95% CI 80.0-90.4) vs. 80.1% (95% CI 73.6-85.6) and 89.1% (95% CI 75.6-95.9) vs. 80.0% (95% CI 63.9-90.4), respectively. Conclusions Standalone AI is able to provide an OD of adenoma/non-adenoma in more than 80% of DCPs, with a high sensitivity but low specificity. The human-machine interaction improved diagnostic performance, especially when experts were involved.
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Affiliation(s)
| | - Irene Maria Bambina Bergna
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
- Gastroenterology and Digestive Endoscopy Unit, Alessandro Manzoni Hospital, Lecco, Italy
| | - Silvia Paggi
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | - Arnaldo Amato
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- Gastroenterology and Digestive Endoscopy Unit, Alessandro Manzoni Hospital, Lecco, Italy
| | | | | | | | | | | | | | - SImone Rocchetto
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
| | - Alessandra Piagnani
- Gastroenterology Unit, Valduce Hospital, Como, Italy
- University of Milan, Milano, Italy
| | | | - Niccolò Bina
- Gastroenterology Unit, Valduce Hospital, Como, Italy
| | | | | | - Cesare Hassan
- Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy
| | - Loredana Correale
- Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, Italy
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9
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Huynh TM, Le QD, Le NQ, Le HM, Quach DT. Implementing narrow banding imaging with dual focus magnification for histological prediction of small rectosigmoid polyps in Vietnamese setting. JGH Open 2024; 8:e13058. [PMID: 38737501 PMCID: PMC11087732 DOI: 10.1002/jgh3.13058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 02/03/2024] [Accepted: 03/14/2024] [Indexed: 05/14/2024]
Abstract
Background and Aim Small rectosigmoid colorectal polyps (<10 mm) are prevalent, with a low prevalence of advanced neoplastic lesions. The "diagnose-and-leave" strategy, employing narrow band imaging (NBI), is gaining popularity for its safety and cost-effectiveness by reducing polypectomy complications and minimizing histopathology expenses. This study assessed the diagnostic efficacy of NBI with dual focus (DF) magnification for real-time neoplastic prediction of rectosigmoid polyps and explored the feasibility of implementing this strategy in Vietnam. Methods In a prospective single-center study, 307 rectosigmoid polyps from 245 patients were analyzed using three consecutive endoscopic modes: white light endoscopy (WLE), NBI, and NBI-DF. Endoscopists assessed polyps for size, location, macroscopic shape, optical diagnosis, and confidence levels before histopathological evaluation. High confidence was assigned when the polyp exhibited all features of a single histology type. Predictions were compared with final histopathology results. Results Of the total, 237 (77.2%) were diminutive (≤5 mm) polyps, and 18 (5.8%) were advanced neoplastic lesions. WLE + NBI and WLE + NBI + NBI-DF exhibited significantly higher accuracy compared to WLE (88.6% and 90.2% vs 74.2%, P < 0.01). For diminutive polyps, the DF mode significantly increased the rate of high-confidence optical diagnoses (89.1% vs 94.9%, P < 0.001). WLE + NBI + NBI-DF demonstrated high sensitivity (90.1%), specificity (95.5%), and negative predictive value (93.4%) in high-confidence predictions, enabling the implementation of the "diagnose-and-leave" strategy. This approach would have reduced 58.2% of unnecessary polypectomies without missing any advanced neoplastic lesions. Conclusion NBI and DF modes provide accurate neoplastic predictions for rectosigmoid polyps. For diminutive polyps, DF magnification improves the confidence level of the optical diagnosis, allowing the safe implementation of the "diagnose-and-leave" strategy.
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Affiliation(s)
- Tien Manh Huynh
- Department of Internal MedicineUniversity of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam
- GI Endoscopy DepartmentUniversity Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam
| | - Quang Dinh Le
- Department of Internal MedicineUniversity of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam
- GI Endoscopy DepartmentUniversity Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam
- Department of EndoscopyNhan Dan Gia Dinh HospitalHo Chi Minh CityVietnam
| | - Nhan Quang Le
- Department of Internal MedicineUniversity of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam
- GI Endoscopy DepartmentUniversity Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam
| | - Huy Minh Le
- GI Endoscopy DepartmentUniversity Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam
- Department of Histology‐Embryology and PathologyUniversity of Medicine and Pharmacy at Ho Chi Minh CityHo Chi MinhVietnam
| | - Duc Trong Quach
- Department of Internal MedicineUniversity of Medicine and Pharmacy at Ho Chi Minh CityHo Chi Minh CityVietnam
- GI Endoscopy DepartmentUniversity Medical Center Ho Chi Minh CityHo Chi Minh CityVietnam
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10
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Wang Y, Ni H, Zhou J, Liu L, Lin J, Yin M, Gao J, Zhu S, Yin Q, Zhu J, Li R. A Semi-Supervised Learning Framework for Classifying Colorectal Neoplasia Based on the NICE Classification. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024:10.1007/s10278-024-01123-9. [PMID: 38653910 DOI: 10.1007/s10278-024-01123-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 04/25/2024]
Abstract
Labelling medical images is an arduous and costly task that necessitates clinical expertise and large numbers of qualified images. Insufficient samples can lead to underfitting during training and poor performance of supervised learning models. In this study, we aim to develop a SimCLR-based semi-supervised learning framework to classify colorectal neoplasia based on the NICE classification. First, the proposed framework was trained under self-supervised learning using a large unlabelled dataset; subsequently, it was fine-tuned on a limited labelled dataset based on the NICE classification. The model was evaluated on an independent dataset and compared with models based on supervised transfer learning and endoscopists using accuracy, Matthew's correlation coefficient (MCC), and Cohen's kappa. Finally, Grad-CAM and t-SNE were applied to visualize the models' interpretations. A ResNet-backboned SimCLR model (accuracy of 0.908, MCC of 0.862, and Cohen's kappa of 0.896) outperformed supervised transfer learning-based models (means: 0.803, 0.698, and 0.742) and junior endoscopists (0.816, 0.724, and 0.863), while performing only slightly worse than senior endoscopists (0.916, 0.875, and 0.944). Moreover, t-SNE showed a better clustering of ternary samples through self-supervised learning in SimCLR than through supervised transfer learning. Compared with traditional supervised learning, semi-supervised learning enables deep learning models to achieve improved performance with limited labelled endoscopic images.
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Affiliation(s)
- Yu Wang
- Department of Hepatobiliary Surgery, Jintan Affiliated Hospital of Jiangsu University, Changzhou, Jiangsu, 213200, China
| | - Haoxiang Ni
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China
| | - Jielu Zhou
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Department of Geriatrics, Kowloon Affiliated Hospital of Shanghai Jiao Tong University, Suzhou, Jiangsu, 215006, China
| | - Lihe Liu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China
| | - Jiaxi Lin
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China
| | - Minyue Yin
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China
- National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, State Key Laboratory of Digestive Health, Beijing, 100050, China
| | - Jingwen Gao
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China
| | - Shiqi Zhu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China
| | - Qi Yin
- Department of Anesthesiology, Jintan Affiliated Hospital of Jiangsu University, Changzhou, Jiangsu, 213200, China
| | - Jinzhou Zhu
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China.
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China.
- Key Laboratory of Hepatosplenic Surgery, Ministry of Education, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
| | - Rui Li
- Department of Gastroenterology, The First Affiliated Hospital of Soochow University, # 899 Pinghai St., Suzhou, Jiangsu, 215006, China.
- Suzhou Clinical Center of Digestive Disease, Suzhou, Jiangsu, 215006, China.
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11
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Lopes SR, Martins C, Santos IC, Teixeira M, Gamito É, Alves AL. Colorectal cancer screening: A review of current knowledge and progress in research. World J Gastrointest Oncol 2024; 16:1119-1133. [PMID: 38660635 PMCID: PMC11037045 DOI: 10.4251/wjgo.v16.i4.1119] [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: 12/28/2023] [Revised: 01/16/2024] [Accepted: 02/18/2024] [Indexed: 04/10/2024] Open
Abstract
Colorectal cancer (CRC) is one of the most prevalent malignancies worldwide, being the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths globally. Despite the progress in screening, early diagnosis, and treatment, approximately 20%-25% of CRC patients still present with metastatic disease at the time of their initial diagnosis. Furthermore, the burden of disease is still expected to increase, especially in individuals younger than 50 years old, among whom early-onset CRC incidence has been increasing. Screening and early detection are pivotal to improve CRC-related outcomes. It is well established that CRC screening not only reduces incidence, but also decreases deaths from CRC. Diverse screening strategies have proven effective in decreasing both CRC incidence and mortality, though variations in efficacy have been reported across the literature. However, uncertainties persist regarding the optimal screening method, age intervals and periodicity. Moreover, adherence to CRC screening remains globally low. In recent years, emerging technologies, notably artificial intelligence, and non-invasive biomarkers, have been developed to overcome these barriers. However, controversy exists over the actual impact of some of the new discoveries on CRC-related outcomes and how to effectively integrate them into daily practice. In this review, we aim to cover the current evidence surrounding CRC screening. We will further critically assess novel approaches under investigation, in an effort to differentiate promising innovations from mere novelties.
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Affiliation(s)
- Sara Ramos Lopes
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
| | - Claudio Martins
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
| | - Inês Costa Santos
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
| | - Madalena Teixeira
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
| | - Élia Gamito
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
| | - Ana Luisa Alves
- Department of Gastroenterology, Centro Hospitalar de Setúbal, Setúbal 2910-446, Portugal
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12
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van der Zander QEW, Schreuder RM, Thijssen A, Kusters CHJ, Dehghani N, Scheeve T, Winkens B, van der Ende - van Loon MCM, de With PHN, van der Sommen F, Masclee AAM, Schoon EJ. Artificial intelligence for characterization of diminutive colorectal polyps: A feasibility study comparing two computer-aided diagnosis systems. Artif Intell Gastrointest Endosc 2024; 5:90574. [DOI: 10.37126/aige.v5.i1.90574] [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: 12/07/2023] [Revised: 01/11/2024] [Accepted: 02/02/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND Artificial intelligence (AI) has potential in the optical diagnosis of colorectal polyps.
AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system (CADx) AI for ColoRectal Polyps (AI4CRP) for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYETM (Fujifilm, Tokyo, Japan). CADx influence on the optical diagnosis of an expert endoscopist was also investigated.
METHODS AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm. Both CADx-systems exploit convolutional neural networks. Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard. AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value (range 0.0-1.0). A predefined cut-off value of 0.6 was set with values < 0.6 indicating benign and values ≥ 0.6 indicating premalignant colorectal polyps. Low confidence characterizations were defined as values 40% around the cut-off value of 0.6 (< 0.36 and > 0.76). Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.
RESULTS AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps. Self-critical AI4CRP, excluding 14 low confidence characterizations [27.5% (14/51)], had a diagnostic accuracy of 89.2%, sensitivity of 89.7%, and specificity of 87.5%, which was higher compared to AI4CRP. CAD EYE had a 83.7% diagnostic accuracy, 74.2% sensitivity, and 100.0% specificity. Diagnostic performances of the endoscopist alone (before AI) increased non-significantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE (AI-assisted endoscopist). Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems, except for specificity for which CAD EYE performed best.
CONCLUSION Real-time use of AI4CRP was feasible. Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP.
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Affiliation(s)
- Quirine Eunice Wennie van der Zander
- Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht 6202 AZ, Netherlands
- GROW, School for Oncology and Reproduction, Maastricht University, Maastricht 6200 MD, Netherlands
| | - Ramon M Schreuder
- Division of Gastroenterology and Hepatology, Catharina Hospital Eindhoven, Eindhoven 5602 ZA, Netherlands
| | - Ayla Thijssen
- Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht 6202 AZ, Netherlands
- GROW, School for Oncology and Reproduction, Maastricht University, Maastricht 6200 MD, Netherlands
| | - Carolus H J Kusters
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
| | - Nikoo Dehghani
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
| | - Thom Scheeve
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
| | - Bjorn Winkens
- Department of Methodology and Statistics, Maastricht University, Postbus 616, 6200 MD Maastricht, Netherlands
- School for Public Health and Primary Care, Maastricht University, Maastricht 6200 MD, Netherlands
| | | | - Peter H N de With
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
| | - Fons van der Sommen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven 5600 MB, Netherlands
| | - Ad A M Masclee
- Department of Gastroenterology and Hepatology, Maastricht University Medical Center, Maastricht 6202 AZ, Netherlands
| | - Erik J Schoon
- GROW, School for Oncology and Reproduction, Maastricht University, Maastricht 6200 MD, Netherlands
- Division of Gastroenterology and Hepatology, Catharina Hospital Eindhoven, Eindhoven 5602 ZA, Netherlands
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13
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Kato S, Kudo SE, Minegishi Y, Miyata Y, Maeda Y, Kuroki T, Takashina Y, Mochizuki K, Tamura E, Abe M, Sato Y, Sakurai T, Kouyama Y, Tanaka K, Ogawa Y, Nakamura H, Ichimasa K, Ogata N, Hisayuki T, Hayashi T, Wakamura K, Miyachi H, Baba T, Ishida F, Nemoto T, Misawa M. Impact of computer-aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study. Dig Endosc 2024; 36:341-350. [PMID: 37937532 DOI: 10.1111/den.14612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/06/2023] [Indexed: 11/09/2023]
Abstract
OBJECTIVES Computer-aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps. METHODS This was a single-center, multicase, multireader, image-reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two-tier classification (neoplastic or nonneoplastic) by analyzing narrow-band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer-based, image-reading test. The test was conducted twice with a 4-week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared. RESULTS Five hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high-confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%). CONCLUSIONS Computer-aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high-confidence diagnosis rate.
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Affiliation(s)
- Shun Kato
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Shin-Ei Kudo
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yosuke Minegishi
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yuki Miyata
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yasuharu Maeda
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Takanori Kuroki
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yuki Takashina
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Kenichi Mochizuki
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Eri Tamura
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Masahiro Abe
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yuta Sato
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Tatsuya Sakurai
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yuta Kouyama
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Kenta Tanaka
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Yushi Ogawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Hiroki Nakamura
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Katsuro Ichimasa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
- Department of Gastroenterology and Hepatology, National University Hospital, Singapore City, Singapore
| | - Noriyuki Ogata
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Tomokazu Hisayuki
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Takemasa Hayashi
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Kunihiko Wakamura
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Hideyuki Miyachi
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Toshiyuki Baba
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Fumio Ishida
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Tetsuo Nemoto
- Department of Diagnostic Pathology and Laboratory Medicine, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Masashi Misawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
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14
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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.
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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
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15
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Halvorsen N, Mori Y. Computer-aided polyp characterization in colonoscopy: sufficient performance or not? Clin Endosc 2024; 57:18-23. [PMID: 38178329 PMCID: PMC10834281 DOI: 10.5946/ce.2023.092] [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: 03/23/2023] [Revised: 05/03/2023] [Accepted: 05/24/2023] [Indexed: 01/06/2024] Open
Abstract
Computer-assisted polyp characterization (computer-aided diagnosis, CADx) facilitates optical diagnosis during colonoscopy. Several studies have demonstrated high sensitivity and specificity of CADx tools in identifying neoplastic changes in colorectal polyps. To implement CADx tools in colonoscopy, there is a need to confirm whether these tools satisfy the threshold levels that are required to introduce optical diagnosis strategies such as "diagnose-and-leave," "resect-and-discard" or "DISCARD-lite." In this article, we review the available data from prospective trials regarding the effect of multiple CADx tools and discuss whether they meet these thresholds.
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Affiliation(s)
- Natalie Halvorsen
- Clinical Effectiveness Research Group, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Yuichi Mori
- Clinical Effectiveness Research Group, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
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16
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Cassinotti A, Parravicini M, Chapman TP, Balzarini M, Canova L, Segato S, Zadro V, Travis S, Segato S. Endoscopic characterization of neoplastic and non-neoplastic lesions in inflammatory bowel disease: systematic review in the era of advanced endoscopic imaging. Therap Adv Gastroenterol 2023; 16:17562848231208667. [PMID: 37954537 PMCID: PMC10638882 DOI: 10.1177/17562848231208667] [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: 05/14/2023] [Accepted: 10/03/2023] [Indexed: 11/14/2023] Open
Abstract
Background Current guidelines strongly recommend the use of validated classifications to support optical diagnosis of lesions with advanced endoscopic imaging in the lower gastrointestinal tract. However, the optimal strategy in inflammatory bowel disease (IBD) is still a matter of debate. Objectives To analyze the accuracy of endoscopic classifications or single predictors for in vivo lesion characterization during endoscopic surveillance of IBD with advanced endoscopic imaging. Design Systematic review. Data sources and methods Medline and PubMed were used to extract all studies which focused on lesion characterization of neoplastic and non-neoplastic lesions in IBD. The diagnostic accuracy of endoscopic classifications and single endoscopic predictors for lesion characterization were analyzed according to type of patients, lesions, and technology used. When available, the rates of true and false positives or negatives for neoplasia were pooled and the sensitivity (SE), specificity (SP), positive predictive value, and negative predictive value (NPV) were calculated. Results We included 35 studies (2789 patients; 5925 lesions - 1149 neoplastic). Advanced endoscopic imaging included dye-based chromoendoscopy, virtual chromoendoscopy (VCE), magnification and high-definition endoscopy, confocal laser endomicroscopy (CLE), endocytoscopy, and autofluorescence imaging. The Kudo classification of pit patterns was most frequently used, with pooled SE 83%, SP 83%, and NPV 95%. The endoscopic criteria with the highest accuracy, with minimum SE ⩾ 90%, SP ⩾ 80%, and NPV ⩾ 90% were: the Kudo-IBD classification used with VCE (Fuji Intelligent Color Enhancement and i-SCAN); combined irregular surface and vascular patterns used with narrow band imaging; the Mainz classification used with CLE. Multiple clinical and technical factors were found to influence the accuracy of optical diagnosis in IBD. Conclusion No single endoscopic factor has yet shown sufficient accuracy for lesion characterization in IBD surveillance. Conventional classifications developed in the non-IBD setting have lower accuracy in IBD. The use of new classifications adapted for IBD (Kudo-IBD), and new technologies based on in vivo microscopic analysis show promise.
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Affiliation(s)
- Andrea Cassinotti
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, viale Borri 57, 21100 Varese, Italy
| | - Marco Parravicini
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
| | - Thomas P. Chapman
- Department of Gastroenterology, St Richard’s and Worthing Hospitals, University Hospitals Sussex NHS Foundation Trust, West Sussex, UK
| | - Marco Balzarini
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
| | - Lorenzo Canova
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
| | - Simone Segato
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
| | - Valentina Zadro
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
| | - Simon Travis
- Translational Gastroenterology Unit, Nuffield Department of Medicine, and Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Biomedical Research Centre, Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Sergio Segato
- Gastroenterology and Digestive Endoscopy Unit, Ospedale di Circolo and Fondazione Macchi University Hospital, ASST Sette Laghi, Varese, Italy
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17
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Ding M, Yan J, Chao G, Zhang S. Application of artificial intelligence in colorectal cancer screening by colonoscopy: Future prospects (Review). Oncol Rep 2023; 50:199. [PMID: 37772392 DOI: 10.3892/or.2023.8636] [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: 02/21/2023] [Accepted: 07/07/2023] [Indexed: 09/30/2023] Open
Abstract
Colorectal cancer (CRC) has become a severe global health concern, with the third‑high incidence and second‑high mortality rate of all cancers. The burden of CRC is expected to surge to 60% by 2030. Fortunately, effective early evidence‑based screening could significantly reduce the incidence and mortality of CRC. Colonoscopy is the core screening method for CRC with high popularity and accuracy. Yet, the accuracy of colonoscopy in CRC screening is related to the experience and state of operating physicians. It is challenging to maintain the high CRC diagnostic rate of colonoscopy. Artificial intelligence (AI)‑assisted colonoscopy will compensate for the above shortcomings and improve the accuracy, efficiency, and quality of colonoscopy screening. The unique advantages of AI, such as the continuous advancement of high‑performance computing capabilities and innovative deep‑learning architectures, which hugely impact the control of colorectal cancer morbidity and mortality expectancy, highlight its role in colonoscopy screening.
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Affiliation(s)
- Menglu Ding
- The Second Affiliated Hospital of Zhejiang Chinese Medical University (The Xin Hua Hospital of Zhejiang Province), Hangzhou, Zhejiang 310000, P.R. China
| | - Junbin Yan
- The Second Affiliated Hospital of Zhejiang Chinese Medical University (The Xin Hua Hospital of Zhejiang Province), Hangzhou, Zhejiang 310000, P.R. China
| | - Guanqun Chao
- Department of General Practice, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, Zhejiang 310000, P.R. China
| | - Shuo Zhang
- The Second Affiliated Hospital of Zhejiang Chinese Medical University (The Xin Hua Hospital of Zhejiang Province), Hangzhou, Zhejiang 310000, P.R. China
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18
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Kim J, Lim SH, Kang HY, Song JH, Yang SY, Chung GE, Jin EH, Choi JM, Bae JH. Impact of 3-second rule for high confidence assignment on the performance of endoscopists for the real-time optical diagnosis of colorectal polyps. Endoscopy 2023; 55:945-951. [PMID: 37172938 DOI: 10.1055/a-2073-3411] [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: 05/15/2023]
Abstract
BACKGROUND Confusion between high and low confidence decisions in optical diagnosis hinders the implementation of real-time optical diagnosis in clinical practice. We evaluated the effect of a 3-second rule (decision time limited to 3 seconds for a high confidence assignment) in expert and nonexpert endoscopists. METHODS This single-center prospective study included eight board-certified gastroenterologists. A 2-month baseline phase used standard real-time optical diagnosis for colorectal polyps < 10 mm and was followed by a 6-month intervention phase using optical diagnosis with the 3-second rule. Performance, including high confidence accuracy, and Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) and Simple Optical Diagnosis Accuracy (SODA) thresholds, was measured. RESULTS Real-time optical diagnosis was performed on 1793 patients with 3694 polyps. There was significant improvement in high confidence accuracy between baseline and intervention phases in the nonexpert group (79.2 % vs. 86.3 %; P = 0.01) but not in the expert group (85.3 % vs. 87.5 %; P = 0.53). Using the 3-second rule improved the overall performance of PIVI and SODA in both groups. CONCLUSIONS The 3-second rule was effective in improving real-time optical diagnosis performance, especially in nonexperts.
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Affiliation(s)
- Jung Kim
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Seon Hee Lim
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Hae Yeon Kang
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Ji Hyun Song
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Sun Young Yang
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Goh Eun Chung
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Eun Hyo Jin
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Ji Min Choi
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
| | - Jung Ho Bae
- Department of Internal Medicine and Healthcare Research Institute, Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, Korea
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19
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Baumer S, Streicher K, Alqahtani SA, Brookman-Amissah D, Brunner M, Federle C, Muehlenberg K, Pfeifer L, Salzberger A, Schorr W, Zustin J, Pech O. Accuracy of polyp characterization by artificial intelligence and endoscopists: a prospective, non-randomized study in a tertiary endoscopy center. Endosc Int Open 2023; 11:E818-E828. [PMID: 37727511 PMCID: PMC10506867 DOI: 10.1055/a-2096-2960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 05/08/2023] [Indexed: 09/21/2023] Open
Abstract
Background and study aims Artificial intelligence (AI) in gastrointestinal endoscopy is developing very fast. Computer-aided detection of polyps and computer-aided diagnosis (CADx) for polyp characterization are available now. This study was performed to evaluate the diagnostic performance of a new commercially available CADx system in clinical practice. Patients and methods This prospective, non-randomized study was performed at a tertiary academic endoscopy center from March to August 2022. We included patients receiving a colonoscopy. Polypectomy had to be performed in all polyps. Every patient was examined concurrently by an endoscopist and AI using two opposing screens. The AI system, overseen by a second observer, was not visible to the endoscopist. The primary outcome was accuracy of the AI classifying the polyps into "neoplastic" and "non-neoplastic." The secondary outcome was accuracy of the classification by the endoscopists. Sessile serrated lesions were classified as neoplastic. Results We included 156 patients (mean age 65; 57 women) with 262 polyps ≤10 mm. Eighty-four were hyperplastic polyps (32.1%), 158 adenomas (60.3%), seven sessile serrated lesions (2.7%) and 13 other entities (normal/inflammatory colonmucosa, lymphoidic polyp) (4.9%) on histological diagnosis. Sensitivity, specificity and accuracy of AI were 89.70% (95% confidence interval [CI]: 84.02%-93.88%), 75.26% (95% CI: 65.46%-83.46%) and 84.35% (95% CI:79.38%-88.53%), respectively. Sensitivity, specificity and accuracy for less experienced endoscopists (2-5 years of endoscopy) were 95.56% (95% CI: 84.85%-99.46%), 61.54% (95% CI: 40.57%-79.77%) and 83.10% (95% CI: 72.34%-90.95%) and for experienced endoscopists 90.83% (95% CI: 84.19%-95.33%), 71.83% (95% CI: 59.90%-81.87%) and 83.77% (95% CI: 77.76%-88.70%), respectively. Conclusion Accuracy for polyp characterization by a new commercially available AI system is high, but does not fulfill the criteria for a "resect-and-discard" strategy.
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Affiliation(s)
- Sebastian Baumer
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Kilian Streicher
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Saleh A. Alqahtani
- Department of Gastroenterology and Hepatology, Johns Hopkins Hospital, Baltimore, United States
- Liver Transplant Center, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Dominic Brookman-Amissah
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Monika Brunner
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Christoph Federle
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Klaus Muehlenberg
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Lukas Pfeifer
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Andrea Salzberger
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Wolfgang Schorr
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
| | - Jozef Zustin
- Private Practice, Histopathology Service Private Practice, Regensburg, Germany
- Gerhard-Domagk-Institute of Pathology, Universitätsklinikum Münster, Munster, Germany
| | - Oliver Pech
- Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany
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20
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van Bokhorst QNE, Houwen BBSL, Hazewinkel Y, Fockens P, Dekker E. Advances in artificial intelligence and computer science for computer-aided diagnosis of colorectal polyps: current status. Endosc Int Open 2023; 11:E752-E767. [PMID: 37593158 PMCID: PMC10431975 DOI: 10.1055/a-2098-1999] [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: 02/04/2023] [Accepted: 05/08/2023] [Indexed: 08/19/2023] Open
Affiliation(s)
- Querijn N E van Bokhorst
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, the Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands
| | - Britt B S L Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, the Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands
| | - Yark Hazewinkel
- Department of Gastroenterology and Hepatology, Tergooi Medical Center, Hilversum, the Netherlands
| | - Paul Fockens
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, the Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, location Academic Medical Center, Amsterdam, the Netherlands
- Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, the Netherlands
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21
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Houwen BBSL, Hazewinkel Y, Giotis I, Vleugels JLA, Mostafavi NS, van Putten P, Fockens P, Dekker E. Computer-aided diagnosis for optical diagnosis of diminutive colorectal polyps including sessile serrated lesions: a real-time comparison with screening endoscopists. Endoscopy 2023; 55:756-765. [PMID: 36623839 PMCID: PMC10374350 DOI: 10.1055/a-2009-3990] [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] [Received: 07/13/2022] [Accepted: 01/09/2023] [Indexed: 01/11/2023]
Abstract
BACKGROUND : We aimed to compare the accuracy of the optical diagnosis of diminutive colorectal polyps, including sessile serrated lesions (SSLs), between a computer-aided diagnosis (CADx) system and endoscopists during real-time colonoscopy. METHODS : We developed the POLyp Artificial Recognition (POLAR) system, which was capable of performing real-time characterization of diminutive colorectal polyps. For pretraining, the Microsoft-COCO dataset with over 300 000 nonpolyp object images was used. For training, eight hospitals prospectively collected 2637 annotated images from 1339 polyps (i. e. publicly available online POLAR database). For clinical validation, POLAR was tested during colonoscopy in patients with a positive fecal immunochemical test (FIT), and compared with the performance of 20 endoscopists from eight hospitals. Endoscopists were blinded to the POLAR output. Primary outcome was the comparison of accuracy of the optical diagnosis of diminutive colorectal polyps between POLAR and endoscopists (neoplastic [adenomas and SSLs] versus non-neoplastic [hyperplastic polyps]). Histopathology served as the reference standard. RESULTS : During clinical validation, 423 diminutive polyps detected in 194 FIT-positive individuals were included for analysis (300 adenomas, 41 SSLs, 82 hyperplastic polyps). POLAR distinguished neoplastic from non-neoplastic lesions with 79 % accuracy, 89 % sensitivity, and 38 % specificity. The endoscopists achieved 83 % accuracy, 92 % sensitivity, and 44 % specificity. The optical diagnosis accuracy between POLAR and endoscopists was not significantly different (P = 0.10). The proportion of polyps in which POLAR was able to provide an optical diagnosis was 98 % (i. e. success rate). CONCLUSIONS : We developed a CADx system that differentiated neoplastic from non-neoplastic diminutive polyps during endoscopy, with an accuracy comparable to that of screening endoscopists and near-perfect success rate.
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Affiliation(s)
- Britt B. S. L. Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Yark Hazewinkel
- Department of Gastroenterology and Hepatology, Radboud University Nijmegen Medical Center, Radboud University of Nijmegen, Nijmegen, The Netherlands
| | | | - Jasper L. A. Vleugels
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Nahid S. Mostafavi
- Department of Gastroenterology and Hepatology, Subdivision Statistics, Amsterdam University Medical Center, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Paul van Putten
- Department of Gastroenterology and Hepatology, Medical Center Leeuwarden, Leeuwarden, The Netherlands
| | - Paul Fockens
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
- Bergman Clinics Maag and Darm Amsterdam, Amsterdam, The Netherlands
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22
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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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23
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Thijssen A, Schreuder RMR, Fonollà R, van der Zander Q, Scheeve T, Winkens B, Subramaniam S, Bhandari P, de With P, Masclee A, van der Sommen F, Schoon E. Automatic textual description of colorectal polyp features: explainable artificial intelligence. Endosc Int Open 2023; 11:E513-E518. [PMID: 37206697 PMCID: PMC10191733 DOI: 10.1055/a-2071-6652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/06/2023] [Indexed: 05/21/2023] Open
Abstract
Computer-aided diagnosis systems (CADx) can improve colorectal polyp (CRP) optical diagnosis. For integration into clinical practice, better understanding of artificial intelligence (AI) by endoscopists is needed. We aimed to develop an explainable AI CADx capable of automatically generating textual descriptions of CRPs. For training and testing of this CADx, textual descriptions of CRP size and features according to the Blue Light Imaging (BLI) Adenoma Serrated International Classification (BASIC) were used, describing CRP surface, pit pattern, and vessels. CADx was tested using BLI images of 55 CRPs. Reference descriptions with agreement by at least five out of six expert endoscopists were used as gold standard. CADx performance was analyzed by calculating agreement between the CADx generated descriptions and reference descriptions. CADx development for automatic textual description of CRP features succeeded. Gwet's AC1 values comparing the reference and generated descriptions per CRP feature were: size 0.496, surface-mucus 0.930, surface-regularity 0.926, surface-depression 0.940, pits-features 0.921, pits-type 0.957, pits-distribution 0.167, and vessels 0.778. CADx performance differed per CRP feature and was particularly high for surface descriptors while size and pits-distribution description need improvement. Explainable AI can help comprehend reasoning behind CADx diagnoses and therefore facilitate integration into clinical practice and increase trust in AI.
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Affiliation(s)
- Ayla Thijssen
- Maastricht University Medical Center, Division of Gastroenterology and Hepatology, Maastricht, Netherlands
- Maastricht University, GROW School for Oncology and Reproduction, Maastricht, Netherlands
| | | | - Roger Fonollà
- Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, Netherlands
| | - Quirine van der Zander
- Maastricht University Medical Center, Division of Gastroenterology and Hepatology, Maastricht, Netherlands
- Maastricht University, GROW School for Oncology and Reproduction, Maastricht, Netherlands
| | - Thom Scheeve
- Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, Netherlands
| | - Bjorn Winkens
- Maastricht University, Department of Methodology and Statistics, Maastricht, Netherlands
- Maastricht University, CAPHRI, Care and Public Health Research Institute
| | - Sharmila Subramaniam
- Portsmouth Hospitals University NHS Trust, Division of Gastroenterology and Hepatology, Portsmouth, United Kingdom
| | - Pradeep Bhandari
- Portsmouth Hospitals University NHS Trust, Division of Gastroenterology and Hepatology, Portsmouth, United Kingdom
| | - Peter de With
- Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, Netherlands
| | - Ad Masclee
- Maastricht University Medical Center, Division of Gastroenterology and Hepatology, Maastricht, Netherlands
| | - Fons van der Sommen
- Eindhoven University of Technology, Department of Electrical Engineering, Eindhoven, Netherlands
| | - Erik Schoon
- Maastricht University, GROW School for Oncology and Reproduction, Maastricht, Netherlands
- Catharina Hospital, Division of Gastroenterology and Hepatology, Eindhoven, Netherlands
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24
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Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening. Diagnostics (Basel) 2023; 13:diagnostics13061102. [PMID: 36980409 PMCID: PMC10047293 DOI: 10.3390/diagnostics13061102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 02/19/2023] [Accepted: 03/11/2023] [Indexed: 03/17/2023] Open
Abstract
Colorectal cancer (CRC) is the third most common cancer worldwide, with the highest incidence reported in high-income countries. However, because of the slow progression of neoplastic precursors, along with the opportunity for their endoscopic detection and resection, a well-designed endoscopic screening program is expected to strongly decrease colorectal cancer incidence and mortality. In this regard, quality of colonoscopy has been clearly related with the risk of post-colonoscopy colorectal cancer. Recently, the development of artificial intelligence (AI) applications in the medical field has been growing in interest. Through machine learning processes, and, more recently, deep learning, if a very high numbers of learning samples are available, AI systems may automatically extract specific features from endoscopic images/videos without human intervention, helping the endoscopists in different aspects of their daily practice. The aim of this review is to summarize the current knowledge on AI-aided endoscopy, and to outline its potential role in colorectal cancer prevention.
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25
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Mori Y, East JE, Hassan C, Halvorsen N, Berzin TM, Byrne M, von Renteln D, Hewett DG, Repici A, Ramchandani M, Al Khatry M, Kudo SE, Wang P, Yu H, Saito Y, Misawa M, Parasa S, Matsubayashi CO, Ogata H, Tajiri H, Pausawasdi N, Dekker E, Ahmad OF, Sharma P, Rex DK. Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement. Dig Endosc 2023; 35:422-429. [PMID: 36749036 DOI: 10.1111/den.14531] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/06/2023] [Indexed: 02/08/2023]
Abstract
The number of artificial intelligence (AI) tools for colonoscopy on the market is increasing with supporting clinical evidence. Nevertheless, their implementation is not going smoothly for a variety of reasons, including lack of data on clinical benefits and cost-effectiveness, lack of trustworthy guidelines, uncertain indications, and cost for implementation. To address this issue and better guide practitioners, the World Endoscopy Organization (WEO) has provided its perspective about the status of AI in colonoscopy as the position statement. WEO Position Statement: Statement 1.1: Computer-aided detection (CADe) for colorectal polyps is likely to improve colonoscopy effectiveness by reducing adenoma miss rates and thus increase adenoma detection; Statement 1.2: In the short term, use of CADe is likely to increase health-care costs by detecting more adenomas; Statement 1.3: In the long term, the increased cost by CADe could be balanced by savings in costs related to cancer treatment (surgery, chemotherapy, palliative care) due to CADe-related cancer prevention; Statement 1.4: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADe to support its use in clinical practice; Statement 2.1: Computer-aided diagnosis (CADx) for diminutive polyps (≤5 mm), when it has sufficient accuracy, is expected to reduce health-care costs by reducing polypectomies, pathological examinations, or both; Statement 2.2: Health-care delivery systems and authorities should evaluate the cost-effectiveness of CADx to support its use in clinical practice; Statement 3: We recommend that a broad range of high-quality cost-effectiveness research should be undertaken to understand whether AI implementation benefits populations and societies in different health-care systems.
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Affiliation(s)
- Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway.,Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway.,Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - James E East
- Translational Gastroenterology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK.,NIHR Oxford Biomedical Research Centre, Oxford, UK.,Division of Gastroenterology and Hepatology, Mayo Clinic Healthcare, London, UK
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.,Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | - Natalie Halvorsen
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
| | - Tyler M Berzin
- Division of Gastroenterology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, USA
| | - Michael Byrne
- Department of Medicine, The University of British Columbia, Vancouver, Canada
| | - Daniel von Renteln
- Division of Gastroenterology, University of Montreal Medical Center (CHUM) and Research Center (CRCHUM), Montreal, Canada
| | - David G Hewett
- School of Medicine, The University of Queensland, Brisbane, Australia
| | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.,Endoscopy Unit, Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy
| | | | - Maryam Al Khatry
- Department of Gastroenterology, Obaidulla Hospital, Ras Al Khaimah, United Arab Emirates
| | - Shin-Ei Kudo
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | - Pu Wang
- Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, Chengdu, China
| | - Honggang Yu
- Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yutaka Saito
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan
| | - Masashi Misawa
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan
| | | | - Carolina Ogawa Matsubayashi
- Gastrointestinal Endoscopy Unit, Gastroenterology Department, University of São Paulo Medical School, São Paulo, Brazil
| | - Haruhiko Ogata
- Center for Diagnostic and Therapeutic Endoscopy, School of Medicine, Keio University, Tokyo, Japan
| | - Hisao Tajiri
- Jikei University School of Medicine, Tokyo, Japan
| | - Nonthalee Pausawasdi
- Vikit Viranuvatti Siriraj GI Endoscopy Center,, Mahidol University, Bangkok, Thailand.,Division of Gastroenterology, Department of Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | | | - Prateek Sharma
- Division of Gastroenterology and Hepatology, University of Kansas School of Medicine and VA Medical Center, Kansas City, USA
| | - Douglas K Rex
- Division of Gastroenterology, Indiana University School of Medicine, Indianapolis, USA
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26
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Artificial intelligence-assisted optical diagnosis for the resect-and-discard strategy in clinical practice: the Artificial intelligence BLI Characterization (ABC) study. Endoscopy 2023; 55:14-22. [PMID: 35562098 DOI: 10.1055/a-1852-0330] [Citation(s) in RCA: 41] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Optical diagnosis of colonic polyps is poorly reproducible outside of high volume referral centers. The present study aimed to assess whether real-time artificial intelligence (AI)-assisted optical diagnosis is accurate enough to implement the leave-in-situ strategy for diminutive (≤ 5 mm) rectosigmoid polyps (DRSPs). METHODS Consecutive colonoscopy outpatients with ≥ 1 DRSP were included. DRSPs were categorized as adenomas or nonadenomas by the endoscopists, who had differing expertise in optical diagnosis, with the assistance of a real-time AI system (CAD-EYE). The primary end point was ≥ 90 % negative predictive value (NPV) for adenomatous histology in high confidence AI-assisted optical diagnosis of DRSPs (Preservation and Incorporation of Valuable endoscopic Innovations [PIVI-1] threshold), with histopathology as the reference standard. The agreement between optical- and histology-based post-polypectomy surveillance intervals (≥ 90 %; PIVI-2 threshold) was also calculated according to European Society of Gastrointestinal Endoscopy (ESGE) and United States Multi-Society Task Force (USMSTF) guidelines. RESULTS Overall 596 DRSPs were retrieved for histology in 389 patients; an AI-assisted high confidence optical diagnosis was made in 92.3 %. The NPV of AI-assisted optical diagnosis for DRSPs (PIVI-1) was 91.0 % (95 %CI 87.1 %-93.9 %). The PIVI-2 threshold was met with 97.4 % (95 %CI 95.7 %-98.9 %) and 92.6 % (95 %CI 90.0 %-95.2 %) of patients according to ESGE and USMSTF, respectively. AI-assisted optical diagnosis accuracy was significantly lower for nonexperts (82.3 %, 95 %CI 76.4 %-87.3 %) than for experts (91.9 %, 95 %CI 88.5 %-94.5 %); however, nonexperts quickly approached the performance levels of experts over time. CONCLUSION AI-assisted optical diagnosis matches the required PIVI thresholds. This does not however offset the need for endoscopists' high level confidence and expertise. The AI system seems to be useful, especially for nonexperts.
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27
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NBI International Colorectal Endoscopic-derived high-confidence optical diagnosis of small polyps compared with histology: understanding errors to improve diagnostic accuracy. Gastrointest Endosc 2023; 97:78-88. [PMID: 36029884 DOI: 10.1016/j.gie.2022.08.032] [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: 03/10/2022] [Revised: 08/05/2022] [Accepted: 08/19/2022] [Indexed: 01/20/2023]
Abstract
BACKGROUND AND AIMS Developments in image-enhancing endoscopy and polyp classification systems have led to a number of gastroenterology societies endorsing an optical diagnosis (OD) approach for small polyps at colonoscopy. In this study we performed a root-cause analysis of ODs to determine the most likely causes of OD error. METHODS As part of a prospective feasibility study, DISCARD3 (Detect InSpect ChAracterise Resect and Discard 3), evaluating implementation and quality assurance of a "resect and discard" strategy for consecutive small polyps <10 mm, a root-cause analysis of 184 cases of high-confidence OD error was performed. In all cases, histopathology underwent a second blinded review and, where discrepancy persisted, further review with deeper levels. RESULTS After a root-cause analysis, 133 of 184 true OD errors were identified and classified into 4 types: A (OD, adenoma; histology, serrated), 45/133 (33.8%); B (OD, serrated; histology, adenoma), 55/133 (41.4%); C (OD, adenoma; histology, normal), 19/133 (14.3%); and D (OD, serrated; histology, normal), 14/133 (10.5%). The remaining 51 of 184 errors were because of a pathology error requiring deeper levels (43/184), pathology observer or laboratory error (7/184), or other error (1/184). CONCLUSIONS OD errors can be related to endoscopist-related factors such as poor photodocumentation, failures of current classification systems, and incomplete histology. We identified a subset of serrated polyps frequently misdiagnosed as adenomas ("pseudoadenomas") using the NBI International Colorectal Endoscopic (NICE) classification. An enhanced algorithm for OD is proposed based on the NICE classification including morphologic and adjunct polyp features.
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28
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Bronswijk M. Transnasal Endoscopy: Seeing is Believing. Clin Gastroenterol Hepatol 2023; 21:240-241. [PMID: 35276330 DOI: 10.1016/j.cgh.2022.02.054] [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: 02/24/2022] [Accepted: 02/27/2022] [Indexed: 02/07/2023]
Affiliation(s)
- Michiel Bronswijk
- Department of Gastroenterology and Hepatology, Imelda Hospital, Bonheiden, Belgium; Department of Gastroenterology and Hepatology, University Hospitals Leuven, KU Leuven, Belgium; Imelda GI Research Center, Bonheiden, Belgium
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29
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Messmann H, Bisschops R, Antonelli G, Libânio D, Sinonquel P, Abdelrahim M, Ahmad OF, Areia M, Bergman JJGHM, Bhandari P, Boskoski I, Dekker E, Domagk D, Ebigbo A, Eelbode T, Eliakim R, Häfner M, Haidry RJ, Jover R, Kaminski MF, Kuvaev R, Mori Y, Palazzo M, Repici A, Rondonotti E, Rutter MD, Saito Y, Sharma P, Spada C, Spadaccini M, Veitch A, Gralnek IM, Hassan C, Dinis-Ribeiro M. Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy 2022; 54:1211-1231. [PMID: 36270318 DOI: 10.1055/a-1950-5694] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the diagnosis and management of gastrointestinal neoplasia within the framework of the performance measures already defined by ESGE. This is based on the clinical relevance of the expected task and the preliminary evidence regarding artificial intelligence in artificial or clinical settings. MAIN RECOMMENDATIONS:: (1) For acceptance of AI in assessment of completeness of upper GI endoscopy, the adequate level of mucosal inspection with AI should be comparable to that assessed by experienced endoscopists. (2) For acceptance of AI in assessment of completeness of upper GI endoscopy, automated recognition and photodocumentation of relevant anatomical landmarks should be obtained in ≥90% of the procedures. (3) For acceptance of AI in the detection of Barrett's high grade intraepithelial neoplasia or cancer, the AI-assisted detection rate for suspicious lesions for targeted biopsies should be comparable to that of experienced endoscopists with or without advanced imaging techniques. (4) For acceptance of AI in the management of Barrett's neoplasia, AI-assisted selection of lesions amenable to endoscopic resection should be comparable to that of experienced endoscopists. (5) For acceptance of AI in the diagnosis of gastric precancerous conditions, AI-assisted diagnosis of atrophy and intestinal metaplasia should be comparable to that provided by the established biopsy protocol, including the estimation of extent, and consequent allocation to the correct endoscopic surveillance interval. (6) For acceptance of artificial intelligence for automated lesion detection in small-bowel capsule endoscopy (SBCE), the performance of AI-assisted reading should be comparable to that of experienced endoscopists for lesion detection, without increasing but possibly reducing the reading time of the operator. (7) For acceptance of AI in the detection of colorectal polyps, the AI-assisted adenoma detection rate should be comparable to that of experienced endoscopists. (8) For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (≤5 mm), AI-assisted characterization should match performance standards for implementing resect-and-discard and diagnose-and-leave strategies. (9) For acceptance of AI in the management of polyps ≥ 6 mm, AI-assisted characterization should be comparable to that of experienced endoscopists in selecting lesions amenable to endoscopic resection.
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Affiliation(s)
- Helmut Messmann
- III Medizinische Klinik, Universitatsklinikum Augsburg, Augsburg, Germany
| | - Raf Bisschops
- Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospital Leuven, Leuven, Belgium
| | - Giulio Antonelli
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli Hospital, Ariccia, Rome, Italy
- Department of Anatomical, Histological, Forensic Medicine and Orthopedics Sciences, Sapienza University of Rome, Italy
| | - Diogo Libânio
- Department of Gastroenterology, Porto Comprehensive Cancer Center, and RISE@CI-IPOP (Health Research Network), Porto, Portugal
- MEDCIDS, Faculty of Medicine, University of Porto, Porto, Portugal
| | - Pieter Sinonquel
- Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospital Leuven, Leuven, Belgium
| | - Mohamed Abdelrahim
- Endoscopy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
| | - Omer F Ahmad
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London Hospital, London, UK
- Division of Surgery and Interventional Sciences, University College London Hospital, London, UK
- Gastrointestinal Services, University College London Hospital, London, UK
| | - Miguel Areia
- Gastroenterology Department, Portuguese Oncology Institute of Coimbra, Coimbra, Portugal
| | | | - Pradeep Bhandari
- Endoscopy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
| | - Ivo Boskoski
- Digestive Endoscopy Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam UMC, Amsterdam, The Netherlands
| | - Dirk Domagk
- Department of Medicine I, Josephs-Hospital Warendorf, Academic Teaching Hospital, University of Muenster, Warendorf, Germany
| | - Alanna Ebigbo
- III Medizinische Klinik, Universitatsklinikum Augsburg, Augsburg, Germany
| | - Tom Eelbode
- Department of Electrical Engineering (ESAT/PSI), Medical Imaging Research Center, KU Leuven, Leuven, Belgium
| | - Rami Eliakim
- Department of Gastroenterology, Sheba Medical Center Tel Hashomer & Sackler School of Medicine, Tel-Aviv University, Ramat Gan, Israel
| | - Michael Häfner
- 2nd Medical Department, Barmherzige Schwestern Krankenhaus, Vienna, Austria
| | - Rehan J Haidry
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London Hospital, London, UK
- Division of Surgery and Interventional Sciences, University College London Hospital, London, UK
| | - Rodrigo Jover
- Servicio de Gastroenterología, Hospital General Universitario Dr. Balmis, Instituto de Investigación Biomédica de Alicante ISABIAL, Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain
| | - Michal F Kaminski
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Department of Gastroenterology, Hepatology and Clinical Oncology, Centre of Postgraduate Medical Education, Warsaw, Poland
- Department of Oncological Gastroenterology and Department of Cancer Prevention, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland
| | - Roman Kuvaev
- Endoscopy Department, Yaroslavl Regional Cancer Hospital, Yaroslavl, Russian Federation
- Department of Gastroenterology, Faculty of Additional Professional Education, N.A. Pirogov Russian National Research Medical University, Moscow, Russian Federation
| | - Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
- Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan
| | | | - Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
- IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | | | - Matthew D Rutter
- North Tees and Hartlepool NHS Foundation Trust, Stockton-on-Tees, UK
- Population Health Sciences Institute, Newcastle University, Newcastle, UK
| | - Yutaka Saito
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan
| | - Prateek Sharma
- Gastroenterology and Hepatology Division, University of Kansas School of Medicine, Kansas, USA
- Kansas City VA Medical Center, Kansas City, USA
| | - Cristiano Spada
- Digestive Endoscopy Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Digestive Endoscopy, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy
| | - Marco Spadaccini
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
- IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Andrew Veitch
- Department of Gastroenterology, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
| | - Ian M Gralnek
- Ellen and Pinchas Mamber Institute of Gastroenterology and Hepatology, Emek Medical Center, Afula, Israel
- Rappaport Faculty of Medicine, Technion Israel Institute of Technology, Haifa, Israel
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
- IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Mario Dinis-Ribeiro
- Department of Gastroenterology, Porto Comprehensive Cancer Center, and RISE@CI-IPOP (Health Research Network), Porto, Portugal
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30
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Kawamura T, Sekiguchi M, Takamaru H, Mizuguchi Y, Horiguchi G, Kato M, Kobayashi K, Sada M, Oda Y, Yokoyama A, Utsumi T, Tsuji Y, Ohki D, Takeuchi Y, Shichijo S, Ikematsu H, Matsuda K, Teramukai S, Kobayashi N, Matsuda T, Saito Y, Tanaka K. "Endoscopic" adenoma detection rate as a quality indicator of colonoscopy: First report from the J-SCOUT study. Dig Endosc 2022. [PMID: 36434769 DOI: 10.1111/den.14483] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022]
Abstract
OBJECTIVES To examine whether reasonable detection rate of endoscopically diagnosed lesions as adenoma ("endoscopic" adenoma detection rate [ADR]) could be calculated with a database generated from colonoscopy reports and whether it could be used as a surrogate colonoscopy quality indicator of "pathological" ADR. METHODS A lesion-by-lesion database of colonoscopies performed between 2010 and 2020 at eight Japanese endoscopy centers and corresponding pathology database were integrated. Differences in numbers of detected polyps, "endoscopic" and "pathological" adenomas, and what these differences could be attributed to were examined. Polyp detection rate (PDR), "endoscopic" and "pathological" ADRs, and correlation coefficients between "pathological" ADR and PDR or "endoscopic" ADR by each endoscopist were calculated. RESULTS Overall, 129,065 colonoscopy reports were analyzed. Among a total of 146,854 polyps, more "endoscopic" adenomas (n = 117,359) were observed than "pathological" adenomas (n = 70,076), primarily because adenomas were not resected on site, rather than because of a misdiagnosis. In all patients analyzed, PDR, "endoscopic" and "pathological" ADRs were 56.4% (95% confidence interval [CI] 56.2-56.7), 48.0% (95% CI 47.7-48.3), and 32.7% (95% CI 32.5-33.0), respectively. "Endoscopic" and "pathological" ADRs from each endoscopist showed a high correlation in hospitals where adenomas were usually resected at the time of examination. CONCLUSIONS By appropriately describing endoscopically diagnosed lesions as "adenomas" in endoscopy reports, "endoscopic" ADR might be used as a surrogate colonoscopy quality indicator of "pathological" ADR (UMIN000040690).
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Affiliation(s)
- Takuji Kawamura
- Department of Gastroenterology, Kyoto Second Red Cross Hospital, Kyoto, Japan
| | - Masau Sekiguchi
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.,Cancer Screening Center, National Cancer Center Hospital, Tokyo, Japan
| | | | | | - Go Horiguchi
- Department of Biostatistics, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Masayuki Kato
- Department of Endoscopy, The Jikei University Katsushika Medical Center, Tokyo, Japan
| | | | - Miwa Sada
- Department of Gastroenterology, Kitasato University, Kanagawa, Japan
| | - Yasushi Oda
- Oda GI Endoscopy and Gastroenterology Clinic, Kumamoto, Japan
| | - Akira Yokoyama
- Department of Therapeutic Oncology, Kyoto University, Kyoto, Japan
| | - Takahiro Utsumi
- Department of Gastroenterology and Hepatology, Kyoto University, Kyoto, Japan
| | - Yosuke Tsuji
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Daisuke Ohki
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yoji Takeuchi
- Department of Gastrointestinal Oncology, Osaka International Cancer Institute, Osaka, Japan.,Department of Genetic Oncology, Division of Hereditary Tumors, Osaka International Cancer Institute, Osaka, Japan
| | - Satoki Shichijo
- Department of Gastrointestinal Oncology, Osaka International Cancer Institute, Osaka, Japan
| | - Hiroaki Ikematsu
- Department of Gastroenterology and Endoscopy, National Cancer Center Hospital East, Chiba, Japan
| | - Koji Matsuda
- Department of Gastroenterology, Shizuoka Medical Center, Shizuoka, Japan
| | - Satoshi Teramukai
- Department of Biostatistics, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Nozomu Kobayashi
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.,Cancer Screening Center, National Cancer Center Hospital, Tokyo, Japan
| | - Takahisa Matsuda
- Division of Gastroenterology and Hepatology, Toho University Omori Medical Center, Tokyo, Japan
| | - Yutaka Saito
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan
| | - Kiyohito Tanaka
- Department of Gastroenterology, Kyoto Second Red Cross Hospital, Kyoto, Japan
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31
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Hossain E, Abdelrahim M, Tanasescu A, Yamada M, Kondo H, Yamada S, Hamamoto R, Marugame A, Saito Y, Bhandari P. Performance of a novel computer-aided diagnosis system in the characterization of colorectal polyps, and its role in meeting Preservation and Incorporation of Valuable Endoscopic Innovations standards set by the American Society of Gastrointestinal Endoscopy. DEN OPEN 2022; 3:e178. [PMID: 36320934 PMCID: PMC9614381 DOI: 10.1002/deo2.178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/27/2022] [Accepted: 10/02/2022] [Indexed: 11/06/2022]
Abstract
Background and aims There has been an increasing role of artificial intelligence (AI) in the characterization of colorectal polyps. Recently, a novel AI algorithm for the characterization of polyps was developed by NEC Corporation (Japan). The aim of our study is to perform an external validation of this algorithm. Methods The study was a video-based evaluation of the computer-aided diagnosis (CADx) system. Patients undergoing colonoscopy were recruited to record videos of colonic polyps. The frozen polyp images extracted from these videos were used for real-time histological prediction by the endoscopists and by the CADx system, and the results were compared. Results A total of 115 polyp images were extracted from 66 patients. Sensitivity, negative predictive value and accuracy for diminutive polyps on white light imaging (WLI) and image-enhanced endoscopy (IEE) when assessed by CADx was 90.9% [95% confidence interval (CI) 77.3-100] and 95.8% [95% CI 87.5-100], 80% [95% CI 44.4-97.5] and 90.9% [95% CI 58.7-99.8], 84.8% [95% CI 72.7-97] and 84.6% [95%CI 71.8-94.9], respectively, compared to 48.1% [95%CI 37.7-59.1] and 72% [95% CI 62.5-81], 37.5% [95% CI 28.8-46.8] and 55% [95% CI 44.7-65.0], 53.7% [95% CI 44.2-63.2] and 66.7% [95% CI 59.7-73.3] when assessed by endoscopists. Concordance between histology and CADx-based post-polypectomy surveillance intervals was 93.02% on WLI and 96% on IEE. Conclusion AI-based optical diagnosis is promising and has the potential to be better than the performance of general endoscopists. We believe that AI can help make real-time optical diagnoses of polyps meeting the Preservation and Incorporation of Valuable endoscopic Innovations standards set by the American Society of Gastrointestinal Endoscopy.
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Affiliation(s)
| | | | | | - Masayoshi Yamada
- National Cancer Center HospitalEndoscopy DivisionTokyoJapan,National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan
| | - Hiroko Kondo
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | - Shijemi Yamada
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | - Ryuji Hamamoto
- National Cancer Center Research InstituteDivision of Molecular Modification and Cancer BiologyTokyoJapan,RIKEN Center for Advanced Intelligence ProjectTokyoJapan
| | | | | | - Pradeep Bhandari
- Portsmouth Hospitals NHS TrustPortsmouthUK,University of Portsmouth, University HousePortsmouthUK
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32
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Ortiz Zúñiga O, Fernández Esparrach MG, Daca M, Pellisé M. Artificial intelligence in gastrointestinal endoscopy - Evolution to a new era. REVISTA ESPANOLA DE ENFERMEDADES DIGESTIVAS 2022; 114:605-615. [PMID: 35770604 DOI: 10.17235/reed.2022.8961/2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Artificial intelligence (AI) systems based on machine learning have evolved in the last few years with an increasing applicability in gastrointestinal endoscopy. Thanks to AI, an image (input) can be transformed into a clinical decision (output). Although AI systems have been initially studied to improve detection (CADe) and characterization of colorectal lesions (CADx), other indications are being currently investigated as detection of blind spots, scope guidance, or delineation/measurement of lesions. The objective of these review is to summarize the current evidence on applicability of AI systems in gastrointestinal endoscopy, highlight strengths and limitations of the technology and review regulatory and ethical aspects for its general implementation in gastrointestinal endoscopy.
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Affiliation(s)
| | | | - María Daca
- Gastroenterología, Hospital Clínic Barcelona, España
| | - María Pellisé
- Gastroenterología, Hospital Clínic Barcelona, España
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33
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García-Rodríguez A, Tudela Y, Córdova H, Carballal S, Ordás I, Moreira L, Vaquero E, Ortiz O, Rivero L, Sánchez FJ, Cuatrecasas M, Pellisé M, Bernal J, Fernández-Esparrach G. In vivo computer-aided diagnosis of colorectal polyps using white light endoscopy. Endosc Int Open 2022; 10:E1201-E1207. [PMID: 36118638 PMCID: PMC9473851 DOI: 10.1055/a-1881-3178] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 06/10/2022] [Indexed: 12/24/2022] Open
Abstract
Background and study aims Artificial intelligence is currently able to accurately predict the histology of colorectal polyps. However, systems developed to date use complex optical technologies and have not been tested in vivo. The objective of this study was to evaluate the efficacy of a new deep learning-based optical diagnosis system, ATENEA, in a real clinical setting using only high-definition white light endoscopy (WLE) and to compare its performance with endoscopists. Methods ATENEA was prospectively tested in real life on consecutive polyps detected in colorectal cancer screening colonoscopies at Hospital Clínic. No images were discarded, and only WLE was used. The in vivo ATENEA's prediction (adenoma vs non-adenoma) was compared with the prediction of four staff endoscopists without specific training in optical diagnosis for the study purposes. Endoscopists were blind to the ATENEA output. Histology was the gold standard. Results Ninety polyps (median size: 5 mm, range: 2-25) from 31 patients were included of which 69 (76.7 %) were adenomas. ATENEA correctly predicted the histology in 63 of 69 (91.3 %, 95 % CI: 82 %-97 %) adenomas and 12 of 21 (57.1 %, 95 % CI: 34 %-78 %) non-adenomas while endoscopists made correct predictions in 52 of 69 (75.4 %, 95 % CI: 60 %-85 %) and 20 of 21 (95.2 %, 95 % CI: 76 %-100 %), respectively. The global accuracy was 83.3 % (95 % CI: 74%-90 %) and 80 % (95 % CI: 70 %-88 %) for ATENEA and endoscopists, respectively. Conclusion ATENEA can accurately be used for in vivo characterization of colorectal polyps, enabling the endoscopist to make direct decisions. ATENEA showed a global accuracy similar to that of endoscopists despite an unsatisfactory performance for non-adenomatous lesions.
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Affiliation(s)
- Ana García-Rodríguez
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain
| | - Yael Tudela
- Computer Science Department. Autonomous University of Barcelona and Computer Vision Center, Barcelona, Catalonia, Spain
| | - Henry Córdova
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Sabela Carballal
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Ingrid Ordás
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Leticia Moreira
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Eva Vaquero
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Oswaldo Ortiz
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain
| | - Liseth Rivero
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - F. Javier Sánchez
- Computer Science Department. Autonomous University of Barcelona and Computer Vision Center, Barcelona, Catalonia, Spain
| | - Miriam Cuatrecasas
- IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain,Pathology Department. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain
| | - Maria Pellisé
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
| | - Jorge Bernal
- Computer Science Department. Autonomous University of Barcelona and Computer Vision Center, Barcelona, Catalonia, Spain
| | - Glòria Fernández-Esparrach
- Endoscopy Unit. Gastroenterology Department. ICMDiM. Hospital Clínic of Barcelona. University of Barcelona, Barcelona, Catalonia, Spain,IDIBAPS, Barcelona, Catalonia, Spain,CIBEREHD, Spain
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34
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Vulpoi RA, Luca M, Ciobanu A, Olteanu A, Barboi OB, Drug VL. Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? Diagnostics (Basel) 2022; 12:diagnostics12040927. [PMID: 35453975 PMCID: PMC9029251 DOI: 10.3390/diagnostics12040927] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/30/2022] [Accepted: 04/06/2022] [Indexed: 02/04/2023] Open
Abstract
Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy.
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Affiliation(s)
- Radu-Alexandru Vulpoi
- Institute of Gastroenterology and Hepatology, Saint Spiridon Hospital, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iași, Romania; (R.-A.V.); (A.O.); (V.L.D.)
| | - Mihaela Luca
- Institute of Computer Science, Romanian Academy—Iași Branch, 700481 Iași, Romania; (M.L.); (A.C.)
| | - Adrian Ciobanu
- Institute of Computer Science, Romanian Academy—Iași Branch, 700481 Iași, Romania; (M.L.); (A.C.)
| | - Andrei Olteanu
- Institute of Gastroenterology and Hepatology, Saint Spiridon Hospital, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iași, Romania; (R.-A.V.); (A.O.); (V.L.D.)
| | - Oana-Bogdana Barboi
- Institute of Gastroenterology and Hepatology, Saint Spiridon Hospital, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iași, Romania; (R.-A.V.); (A.O.); (V.L.D.)
- Correspondence: ; Tel.: +40-74-345-5012
| | - Vasile Liviu Drug
- Institute of Gastroenterology and Hepatology, Saint Spiridon Hospital, “Grigore T. Popa” University of Medicine and Pharmacy, 700111 Iași, Romania; (R.-A.V.); (A.O.); (V.L.D.)
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Houwen BBSL, Hassan C, Hazewinkel Y, Vleugels JLA, Dinis-Ribeiro M, Greuter MJE, Coupé VMH, Dekker E, Bisschops R. Methodological framework for development of competence standards for optical diagnosis in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy 2022; 54:84-87. [PMID: 34861702 DOI: 10.1055/a-1689-5615] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Britt B S L Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.,Endoscopy Unit, IRCCS Humanitas Clinical and Research Center, Rozzano, Milan, Italy
| | - Yark Hazewinkel
- Department of Gastroenterology and Hepatology, Radboud University Medical Center, Radboud University, Nijmegen, The Netherlands
| | - Jasper L A Vleugels
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Mario Dinis-Ribeiro
- Porto Comprehensive Cancer Center (Porto.CCC), Porto, Portugal.,RISE@CI-IPOP (Health Research Network), Porto, Portugal
| | - Marjolein J E Greuter
- Department of Epidemiology and Data Science, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands
| | - Veerle M H Coupé
- Department of Epidemiology and Data Science, Amsterdam University Medical Center, location VUmc, Amsterdam, The Netherlands
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, location AMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Raf Bisschops
- Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospital Leuven, Leuven, Belgium
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