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Young E, Edwards L, Singh R. The Role of Artificial Intelligence in Colorectal Cancer Screening: Lesion Detection and Lesion Characterization. Cancers (Basel) 2023; 15:5126. [PMID: 37958301 PMCID: PMC10647850 DOI: 10.3390/cancers15215126] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/14/2023] [Accepted: 10/14/2023] [Indexed: 11/15/2023] Open
Abstract
Colorectal cancer remains a leading cause of cancer-related morbidity and mortality worldwide, despite the widespread uptake of population surveillance strategies. This is in part due to the persistent development of 'interval colorectal cancers', where patients develop colorectal cancer despite appropriate surveillance intervals, implying pre-malignant polyps were not resected at a prior colonoscopy. Multiple techniques have been developed to improve the sensitivity and accuracy of lesion detection and characterisation in an effort to improve the efficacy of colorectal cancer screening, thereby reducing the incidence of interval colorectal cancers. This article presents a comprehensive review of the transformative role of artificial intelligence (AI), which has recently emerged as one such solution for improving the quality of screening and surveillance colonoscopy. Firstly, AI-driven algorithms demonstrate remarkable potential in addressing the challenge of overlooked polyps, particularly polyp subtypes infamous for escaping human detection because of their inconspicuous appearance. Secondly, AI empowers gastroenterologists without exhaustive training in advanced mucosal imaging to characterise polyps with accuracy similar to that of expert interventionalists, reducing the dependence on pathologic evaluation and guiding appropriate resection techniques or referrals for more complex resections. AI in colonoscopy holds the potential to advance the detection and characterisation of polyps, addressing current limitations and improving patient outcomes. The integration of AI technologies into routine colonoscopy represents a promising step towards more effective colorectal cancer screening and prevention.
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Affiliation(s)
- Edward Young
- Faculty of Health and Medical Sciences, University of Adelaide, Lyell McEwin Hospital, Haydown Rd, Elizabeth Vale, SA 5112, Australia
| | - Louisa Edwards
- Faculty of Health and Medical Sciences, University of Adelaide, Queen Elizabeth Hospital, Port Rd, Woodville South, SA 5011, Australia
| | - Rajvinder Singh
- Faculty of Health and Medical Sciences, University of Adelaide, Lyell McEwin Hospital, Haydown Rd, Elizabeth Vale, SA 5112, Australia
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Young EJ, Rajandran A, Philpott HL, Sathananthan D, Hoile SF, Singh R. Mucosal imaging in colon polyps: New advances and what the future may hold. World J Gastroenterol 2022; 28:6632-6661. [PMID: 36620337 PMCID: PMC9813932 DOI: 10.3748/wjg.v28.i47.6632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 10/23/2022] [Accepted: 11/23/2022] [Indexed: 12/19/2022] Open
Abstract
An expanding range of advanced mucosal imaging technologies have been developed with the goal of improving the detection and characterization of lesions in the gastrointestinal tract. Many technologies have targeted colorectal neoplasia given the potential for intervention prior to the development of invasive cancer in the setting of widespread surveillance programs. Improvement in adenoma detection reduces miss rates and prevents interval cancer development. Advanced imaging technologies aim to enhance detection without significantly increasing procedural time. Accurate polyp characterisation guides resection techniques for larger polyps, as well as providing the platform for the “resect and discard” and “do not resect” strategies for small and diminutive polyps. This review aims to collate and summarise the evidence regarding these technologies to guide colonoscopic practice in both interventional and non-interventional endoscopists.
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Affiliation(s)
- Edward John Young
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide 5000, South Australia, Australia
| | - Arvinf Rajandran
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
| | - Hamish Lachlan Philpott
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide 5000, South Australia, Australia
| | - Dharshan Sathananthan
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide 5000, South Australia, Australia
| | - Sophie Fenella Hoile
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide 5000, South Australia, Australia
| | - Rajvinder Singh
- Department of Gastroenterology, Lyell McEwin Hospital, Northern Adelaide Local Health Network, Elizabeth Vale 5031, South Australia, Australia
- Faculty of Health and Medical Sciences, University of Adelaide, Adelaide 5000, South Australia, Australia
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Hussein M, González-Bueno Puyal J, Mountney P, Lovat LB, Haidry R. Role of artificial intelligence in the diagnosis of oesophageal neoplasia: 2020 an endoscopic odyssey. World J Gastroenterol 2020; 26:5784-5796. [PMID: 33132634 PMCID: PMC7579761 DOI: 10.3748/wjg.v26.i38.5784] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 08/12/2020] [Accepted: 09/12/2020] [Indexed: 02/06/2023] Open
Abstract
The past decade has seen significant advances in endoscopic imaging and optical enhancements to aid early diagnosis. There is still a treatment gap due to the underdiagnosis of lesions of the oesophagus. Computer aided diagnosis may play an important role in the coming years in providing an adjunct to endoscopists in the early detection and diagnosis of early oesophageal cancers, therefore curative endoscopic therapy can be offered. Research in this area of artificial intelligence is expanding and the future looks promising. In this review article we will review current advances in artificial intelligence in the oesophagus and future directions for development.
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Affiliation(s)
- Mohamed Hussein
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Division of Surgery and Interventional Sciences, University College London, London W1W 7TY, United Kingdom
| | - Juana González-Bueno Puyal
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, United Kingdom and Odin Vision, London W1W 7TS, United Kingdom
| | | | - Laurence B Lovat
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Division of Surgery and Interventional Sciences, University College London, London W1W 7TY, United Kingdom
| | - Rehan Haidry
- Department of GI Services, University College London Hospital, London NW1 2BU, United Kingdom
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Beintaris I, Rutter M. Advanced imaging in colonoscopy: contemporary approach to dysplasia surveillance in inflammatory bowel disease. Frontline Gastroenterol 2016; 7:308-315. [PMID: 28839872 PMCID: PMC5369495 DOI: 10.1136/flgastro-2016-100735] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Accepted: 07/19/2016] [Indexed: 02/04/2023] Open
Abstract
Inflammatory bowel disease (IBD) (ulcerative colitis (UC) and Crohn's disease (CD)) is a chronic relapsing/remitting condition characterised by intestinal inflammation. One of the main concerns in patients with longstanding ulcerative and Crohn's colitis is development of colonic dysplasia and colorectal cancer (CRC), a risk higher than that of the general population. Colonoscopy surveillance programmes have been developed by major societies worldwide to improve early dysplasia detection and treatment, thus preventing progression to colorectal cancer. Colonoscopy is an imperfect tool as lesions can be missed, an issue even more relevant to colitic patients, where mucosal inspection and lesion recognition may prove challenging. Extensive research has been undertaken on performance improvement in this area while technical advances in optical imaging, such as high-definition, have made their way into modern endoscopy units. Techniques and technologies available to enhance optical diagnosis of dysplasia in inflammatory bowel disease are reviewed in this paper, focusing on those that are realistic, widely available and feasible for everyday practice.
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Affiliation(s)
| | - Matt Rutter
- University Hospital of North Tees, Cleveland, UK
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Forgione A, Guraya S. Advanced endoscopic imaging technologies for in vivo cytological examination of gastrointestinal tract lesions: State of the art and proposal for proper clinical application. J Microsc Ultrastruct 2013. [DOI: 10.1016/j.jmau.2013.11.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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