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Automated polyp detection in the colorectum: a prospective study (with videos).
Gastrointest Endosc. 2019 03; 89(3):576-582.e1.GE

Abstract

BACKGROUND AND AIMS

Adenoma detection is a highly personalized task that differs markedly among endoscopists. Technical advances are therefore desirable for the improvement of the adenoma detection rate (ADR). An automated computer-driven technology would offer the chance to objectively assess the presence of colorectal polyps during colonoscopy. We present here the application of a real-time automated polyp detection software (APDS) under routine colonoscopy conditions.

METHODS

This was a prospective study at a university hospital in Germany. A prototype of a novel APDS ("KoloPol," Fraunhofer IIS, Erlangen, Germany) was used for automated image-based polyp detection. The software functions by highlighting structures of possible polyp lesions in a color-coded manner during real-time colonoscopy procedures. Testing the feasibility of APDS deployment under real-time conditions was the primary goal of the study. APDS polyp detection rates (PDRs) were defined as secondary endpoints provided that endoscopists' detection served as criterion standard.

RESULTS

The APDS was applied in 55 routine colonoscopies without the occurrence of any clinically relevant adverse events. Endoscopists' PDRs and ADRs were 56.4% and 30.9%, respectively. The PDRs and ADRs of the APDS were 50.9% and 29.1%, respectively. The APDS detected 55 of 73 polyps (75.3%). Smaller polyp size and flat polyp morphology were correlated with insufficient polyp detection by the APDS.

CONCLUSION

Computer-assisted automated low-delay polyp detection is feasible during real-time colonoscopy. Efforts should be undertaken to improve the APDS with respect to smaller and flat shaped polyps. (Clinical trial registration number: NCT02838888.).

Authors+Show Affiliations

Klinik für Innere Medizin II, Munich, Germany.Klinik für Innere Medizin II, Munich, Germany.Fraunhofer-Institut für Integrierte Schaltungen IIS, Erlangen, Germany.Institut für Medizinische Informatik, Statistik und Epidemiologie, Munich, Germany.Fraunhofer-Institut für Integrierte Schaltungen IIS, Erlangen, Germany.Klinik für Innere Medizin II, Munich, Germany.Klinik für Innere Medizin II, Munich, Germany.Klinik für Innere Medizin II, Munich, Germany.MITI Forschungsgruppe am Klinikum rechts der Isar der Technischen Universität München, Munich, Germany.Klinik für Innere Medizin II, Munich, Germany.Medizinische Klinik II, RoMed Klinikum Rosenheim, Rosenheim, Germany.Fraunhofer-Institut für Integrierte Schaltungen IIS, Erlangen, Germany.

Pub Type(s)

Journal Article
Observational Study
Video-Audio Media

Language

eng

PubMed ID

30342029

Citation

Klare, Peter, et al. "Automated Polyp Detection in the Colorectum: a Prospective Study (with Videos)." Gastrointestinal Endoscopy, vol. 89, no. 3, 2019, pp. 576-582.e1.
Klare P, Sander C, Prinzen M, et al. Automated polyp detection in the colorectum: a prospective study (with videos). Gastrointest Endosc. 2019;89(3):576-582.e1.
Klare, P., Sander, C., Prinzen, M., Haller, B., Nowack, S., Abdelhafez, M., Poszler, A., Brown, H., Wilhelm, D., Schmid, R. M., von Delius, S., & Wittenberg, T. (2019). Automated polyp detection in the colorectum: a prospective study (with videos). Gastrointestinal Endoscopy, 89(3), 576-e1. https://doi.org/10.1016/j.gie.2018.09.042
Klare P, et al. Automated Polyp Detection in the Colorectum: a Prospective Study (with Videos). Gastrointest Endosc. 2019;89(3):576-582.e1. PubMed PMID: 30342029.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Automated polyp detection in the colorectum: a prospective study (with videos). AU - Klare,Peter, AU - Sander,Christoph, AU - Prinzen,Martin, AU - Haller,Bernhard, AU - Nowack,Sebastian, AU - Abdelhafez,Mohamed, AU - Poszler,Alexander, AU - Brown,Hayley, AU - Wilhelm,Dirk, AU - Schmid,Roland M, AU - von Delius,Stefan, AU - Wittenberg,Thomas, Y1 - 2018/10/17/ PY - 2018/05/25/received PY - 2018/09/30/accepted PY - 2018/10/21/pubmed PY - 2019/6/14/medline PY - 2018/10/21/entrez SP - 576 EP - 582.e1 JF - Gastrointestinal endoscopy JO - Gastrointest. Endosc. VL - 89 IS - 3 N2 - BACKGROUND AND AIMS: Adenoma detection is a highly personalized task that differs markedly among endoscopists. Technical advances are therefore desirable for the improvement of the adenoma detection rate (ADR). An automated computer-driven technology would offer the chance to objectively assess the presence of colorectal polyps during colonoscopy. We present here the application of a real-time automated polyp detection software (APDS) under routine colonoscopy conditions. METHODS: This was a prospective study at a university hospital in Germany. A prototype of a novel APDS ("KoloPol," Fraunhofer IIS, Erlangen, Germany) was used for automated image-based polyp detection. The software functions by highlighting structures of possible polyp lesions in a color-coded manner during real-time colonoscopy procedures. Testing the feasibility of APDS deployment under real-time conditions was the primary goal of the study. APDS polyp detection rates (PDRs) were defined as secondary endpoints provided that endoscopists' detection served as criterion standard. RESULTS: The APDS was applied in 55 routine colonoscopies without the occurrence of any clinically relevant adverse events. Endoscopists' PDRs and ADRs were 56.4% and 30.9%, respectively. The PDRs and ADRs of the APDS were 50.9% and 29.1%, respectively. The APDS detected 55 of 73 polyps (75.3%). Smaller polyp size and flat polyp morphology were correlated with insufficient polyp detection by the APDS. CONCLUSION: Computer-assisted automated low-delay polyp detection is feasible during real-time colonoscopy. Efforts should be undertaken to improve the APDS with respect to smaller and flat shaped polyps. (Clinical trial registration number: NCT02838888.). SN - 1097-6779 UR - https://www.unboundmedicine.com/medline/citation/30342029/Automated_polyp_detection_in_the_colorectum:_a_prospective_study__with_videos__ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0016-5107(18)33175-4 DB - PRIME DP - Unbound Medicine ER -