Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/71680

TitleClinical performance of new software to automatically detect angioectasias in small bowel capsule endoscopy
Other titlesPerformance clínica de um novo software para detetar automaticamente angiectasias na endoscopia por cápsula
Author(s)Costa, Dalila Amélia Amorim
Vieira, Pedro Miguel
Pinto, Catarina
Arroja, Bruno
Leal, Tiago
Mendes, Sofia Silva
Gonçalves, Raquel
Lima, C. S.
Rolanda, Carla
KeywordsVideo capsule endoscopy
Angioectasias
Automatic detection
Algorithm
Issue date2021
PublisherKarger Publishers
JournalGE Portuguese Journal of Gastroenterology
Abstract(s)Background: Video capsule endoscopy (VCE) revolutionized the diagnosis and management of obscure gastrointestinal bleeding, though the rate of detection of small bowel lesions by the physician is still disappointing. Our group developed a novel algorithm (CMEMS-Uminho) to automatically detect angioectasias which display greater accuracy in VCE static frames than other methods previously published. We aimed to evaluate the algorithm overall performance and assess its diagnostic yield and usability in clinical practice. Methods: Algorithm overall performance was determined using 54 full-length VCE recordings. To assess its diagnostic yield and usability in clinical practice, 38 VCE examinations with the clinical diagnosis of angioectasias consecutively performed (2017-2018) were evaluated by three physicians with different experiences. The CMEMS-Uminho algorithm was also applied. The performance of the CMEMS-Uminho algorithm was defined by a positive concordance between a frame automatically selected by the software and a study independent capsule endoscopist. Results: Overall performance in complete VCE recordings was 77.7%, and diagnostic yield was 94.7%. There were significant differences between physicians in regard to global detection rate (p < 0.001), detection rate per capsule (p < 0.001), diagnostic yield (p = 0.007), true positive rate (p < 0.001), time (p < 0.001), and speed viewing (p < 0.001). The application of CMEMS-Uminho algorithm significantly enhanced all readers' global detection rate (p < 0.001) and the differences between them were no longer observed. Conclusion: The CMEMS-Uminho algorithm detained a good overall performance and was able to enhance physicians' performance, suggesting a potential usability of this tool in clinical practice.
TypeArticle
URIhttps://hdl.handle.net/1822/71680
DOI10.1159/000510024
ISSN2341-4545
e-ISSN2387-1954
Publisher versionhttps://www.karger.com/Article/FullText/510024
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMEMS - Artigos em revistas nacionais/Papers in national journals

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