Computer Assisted Detection & Selection of Serrated Adenomas and Neoplastic Polyps - a New Clinical DRAft
NCT ID: NCT03601065
Last Updated: 2018-07-26
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
250 participants
OBSERVATIONAL
2018-08-31
2019-10-31
Brief Summary
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In the validation phase of the study a computer program will be established which aims to distinguish between adenomas, serrated adenomas and hyperplastic polyps on the basis of optical features derived from the videos. A deep learning approach will be used for programming. Afterwards, in the testing phase of the study, videos of 100 polyps (not used in the validation phase) will be presented to the computer program. The establishment of a well- functioning computer program is the primary aim of the study.
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Detailed Description
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The implementation of screening programs has led to increasing numbers of colonoscopies in the last years \[3\]. This approach naturally implies higher amounts of detected polyps. The removal of these polyps and consultation of a pathologist in order to make a diagnosis is time consuming and expensive. An optical- based prediction of polyp histology (adenomatous versus non- adenomatous) would enable endoscopists to save money and to inform patients faster about examination results. The approach of predicting polyp histology on the basis of optical features is called the "optical biopsy" method. The prediction is made by the endoscopists during real-time colonoscopy. The aim of this strategy is to make an optical diagnosis which enables users to resect polyps without sending the specimen to pathology. Narrow Band Imaging (NBI) is a light-filter device which can be switched on during colonoscopy. NBI is useful to better display vascular patterns of the colon mucosa. It has been shown that the use of NBI can facilitate optical classification of colorectal polyps \[5\]. A NBI- based classification schemes exists which can be used to assign polyps into specific polyp categories (adenomatous versus non- adenomatous) \[6\].
Prior to the implementation of the optical classification approach for routine use in endoscopy it is necessary to proof its feasibility and accuracy \[7\]. Otherwise the approach would entail the risk of wrong diagnoses which could lead to wrong recommendations on further diagnostic or therapeutic steps.
Until now, some clinical trials have shown good accuracy for the optical biopsy method \[5\]. However, there is growing evidence that optical biopsy does not yet meet demanded accuracy thresholds \[8\]. The aim of our study is to create a computer program that is able to distinguish between adenomas, serrated adenomas and hyperplastic polyps. Video sequences of colorectal polyps will be used for machine learning (validation phase). Afterwards a set of 100 videos will be used to test whether the computer program is able to distinguish between adenomatous and non- adenomatous polyps (primary endpoint). Statistical measures (accuracy, sensitivity, specificity) will be calculated. The 100 videos will also be presented to human experts who will also predict polyp diagnoses based on optical features. Comparing the accuracy of optical predictions made by the computer and by human experts will be another endpoint of the study.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Routine colonoscopy Cohort
Videos of polyps, resection of polyps
Ther is no study specific intervention. Video sequences will be taken if polyps are found in the colon. Polyps will then be resected routinely.
Interventions
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Videos of polyps, resection of polyps
Ther is no study specific intervention. Video sequences will be taken if polyps are found in the colon. Polyps will then be resected routinely.
Eligibility Criteria
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Inclusion Criteria
* patients \>= 18 years
Exclusion Criteria
* indication for colonoscopy: inflammatory bowel disease
* indication for colonoscopy: emergency colonoscopy e.g. acute bleeding
* contraindication for polyp resection e.g. patients on warfarin
18 Years
ALL
No
Sponsors
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Chair of Computer Aided Medical Procedures & Augmented Reality; Institut für Informatik I16 Technische Universität München
UNKNOWN
Technical University of Munich
OTHER
Responsible Party
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Dr. Peter Klare
Dr. med. Peter Klare
Locations
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Klinik für Innere Medizin II am Klinikum rechts der Isar der Technischen Universität München München, Deutschland Germany
Munich, , Germany
Countries
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Central Contacts
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Facility Contacts
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References
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Vogelstein B, Fearon ER, Hamilton SR, Kern SE, Preisinger AC, Leppert M, Nakamura Y, White R, Smits AM, Bos JL. Genetic alterations during colorectal-tumor development. N Engl J Med. 1988 Sep 1;319(9):525-32. doi: 10.1056/NEJM198809013190901.
Brenner H, Altenhofen L, Stock C, Hoffmeister M. Prevention, early detection, and overdiagnosis of colorectal cancer within 10 years of screening colonoscopy in Germany. Clin Gastroenterol Hepatol. 2015 Apr;13(4):717-23. doi: 10.1016/j.cgh.2014.08.036. Epub 2014 Sep 15.
Stock C, Haug U, Brenner H. Population-based prevalence estimates of history of colonoscopy or sigmoidoscopy: review and analysis of recent trends. Gastrointest Endosc. 2010 Feb;71(2):366-381.e2. doi: 10.1016/j.gie.2009.06.018. Epub 2009 Oct 20.
Lopez-Ceron M, Sanabria E, Pellise M. Colonic polyps: is it useful to characterize them with advanced endoscopy? World J Gastroenterol. 2014 Jul 14;20(26):8449-57. doi: 10.3748/wjg.v20.i26.8449.
ASGE Technology Committee; Abu Dayyeh BK, Thosani N, Konda V, Wallace MB, Rex DK, Chauhan SS, Hwang JH, Komanduri S, Manfredi M, Maple JT, Murad FM, Siddiqui UD, Banerjee S. ASGE Technology Committee systematic review and meta-analysis assessing the ASGE PIVI thresholds for adopting real-time endoscopic assessment of the histology of diminutive colorectal polyps. Gastrointest Endosc. 2015 Mar;81(3):502.e1-502.e16. doi: 10.1016/j.gie.2014.12.022. Epub 2015 Jan 16.
Hewett DG, Kaltenbach T, Sano Y, Tanaka S, Saunders BP, Ponchon T, Soetikno R, Rex DK. Validation of a simple classification system for endoscopic diagnosis of small colorectal polyps using narrow-band imaging. Gastroenterology. 2012 Sep;143(3):599-607.e1. doi: 10.1053/j.gastro.2012.05.006. Epub 2012 May 15.
Kaminski MF, Hassan C, Bisschops R, Pohl J, Pellise M, Dekker E, Ignjatovic-Wilson A, Hoffman A, Longcroft-Wheaton G, Heresbach D, Dumonceau JM, East JE. Advanced imaging for detection and differentiation of colorectal neoplasia: European Society of Gastrointestinal Endoscopy (ESGE) Guideline. Endoscopy. 2014 May;46(5):435-49. doi: 10.1055/s-0034-1365348. Epub 2014 Mar 17.
Kang HY, Kim YS, Kang SJ, Chung GE, Song JH, Yang SY, Lim SH, Kim D, Kim JS. Comparison of Narrow Band Imaging and Fujinon Intelligent Color Enhancement in Predicting Small Colorectal Polyp Histology. Dig Dis Sci. 2015 Sep;60(9):2777-84. doi: 10.1007/s10620-015-3661-5. Epub 2015 Apr 14.
Other Identifiers
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CASSANDRA II
Identifier Type: -
Identifier Source: org_study_id
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