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      Frontiers of Robotic Colonoscopy: A Comprehensive Review of Robotic Colonoscopes and Technologies

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Flexible colonoscopy remains the prime mean of screening for colorectal cancer (CRC) and the gold standard of all population-based screening pathways around the world. Almost 60% of CRC deaths could be prevented with screening. However, colonoscopy attendance rates are affected by discomfort, fear of pain and embarrassment or loss of control during the procedure. Moreover, the emergence and global thread of new communicable diseases might seriously affect the functioning of contemporary centres performing gastrointestinal endoscopy. Innovative solutions are needed: artificial intelligence (AI) and physical robotics will drastically contribute for the future of the healthcare services. The translation of robotic technologies from traditional surgery to minimally invasive endoscopic interventions is an emerging field, mainly challenged by the tough requirements for miniaturization. Pioneering approaches for robotic colonoscopy have been reported in the nineties, with the appearance of inchworm-like devices. Since then, robotic colonoscopes with assistive functionalities have become commercially available. Research prototypes promise enhanced accessibility and flexibility for future therapeutic interventions, even via autonomous or robotic-assisted agents, such as robotic capsules. Furthermore, the pairing of such endoscopic systems with AI-enabled image analysis and recognition methods promises enhanced diagnostic yield. By assembling a multidisciplinary team of engineers and endoscopists, the paper aims to provide a contemporary and highly-pictorial critical review for robotic colonoscopes, hence providing clinicians and researchers with a glimpse of the major changes and challenges that lie ahead.

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          Most cited references 173

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

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            Wireless capsule endoscopy.

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              Polyp miss rate determined by tandem colonoscopy: a systematic review.

              Colonoscopy is the best available method to detect and remove colonic polyps and therefore serves as the gold standard for less invasive tests such as virtual colonoscopy. Although gastroenterologists agree that colonoscopy is not infallible, there is no clarity on the numbers and rates of missed polyps. The purpose of this systematic review was to obtain summary estimates of the polyp miss rate as determined by tandem colonoscopy. An extensive search was performed within PUBMED, EMBASE, and the Cochrane Library databases to identify studies in which patients had undergone two same-day colonoscopies with polypectomy. Random effects models based on the binomial distribution were used to calculate pooled estimates of miss rates. Six studies with a total of 465 patients could be included. The pooled miss rate for polyps of any size was 22% (95% CI: 19-26%; 370/1,650 polyps). Adenoma miss rate by size was, respectively, 2.1% (95% CI: 0.3-7.3%; 2/96 adenomas > or =10 mm), 13% (95% CI: 8.0-18%; 16/124 adenomas 5-10 mm), and 26% (95% CI: 27-35%; 151/587 adenomas 1-5 mm). Three studies reported data on nonadenomatous polyps: zero of eight nonadenomatous polyps > or =10 mm were missed (0%; 95% CI: 0-36.9%) and 83 of 384 nonadenomatous polyps or =10 mm, but the miss rate increases significantly in smaller sized polyps. The available evidence is based on a small number of studies with heterogeneous study designs and inclusion criteria.
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                Author and article information

                Journal
                J Clin Med
                J Clin Med
                jcm
                Journal of Clinical Medicine
                MDPI
                2077-0383
                31 May 2020
                June 2020
                : 9
                : 6
                Affiliations
                [1 ]The BioRobotics Institute, Scuola Superiore Sant’Anna, 56025 Pisa, Italy; veronica.iacovacci@ 123456santannapisa.it (V.I.); marcello.chiurazzi@ 123456santannapisa.it (M.C.); paolo.dario@ 123456santannapisa.it (P.D.)
                [2 ]Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
                [3 ]Department of Human Nutrition and Metabolomics, Pomeranian Medical University in Szczecin, 71-460 Szczecin, Poland; karzyd@ 123456pum.edu.pl
                [4 ]Department of Gastroenterology, Pomeranian Medical University in Szczecin, 71-252 Szczecin, Poland; marlicz@ 123456hotmail.com
                [5 ]Endoklinika sp. z o.o., 70-535 Szczecin, Poland
                [6 ]School of Biomedical Engineering & Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London SE1 7EH, UK; hongbin.liu@ 123456kcl.ac.uk
                [7 ]Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London W1W 7TY, UK; danail.stoyanov@ 123456ucl.ac.uk
                [8 ]Department of Surgical Sciences, University of Torino, 10126 Torino, Italy; alberto.arezzo@ 123456unito.it
                [9 ]Department of Gastroenterology, Skåne University Hospital, Lund University, 20502 Malmö, Sweden; ervin.toth@ 123456med.lu.se
                [10 ]Department of Clinical Sciences, Section of Surgery, Lund University, 20502 Malmö, Sweden; henrik.thorlacius@ 123456med.lu.se
                [11 ]Endoscopy Unit, The Royal Infirmary of Edinburgh, Edinburgh EH16 4SA, UK; akoulaouzidis@ 123456hotmail.com
                Author notes
                [* ]Correspondence: gastone.ciuti@ 123456santannapisa.it ; Tel.: +39-348-0015616
                [†]

                These authors equally contributed to this work.

                Article
                jcm-09-01648
                10.3390/jcm9061648
                7356873
                32486374
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

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