ArticleGE Portuguese journal of gastroenterology2021
Clinical Performance of New Software to Automatically Detect Angioectasias in Small Bowel Capsule Endoscopy.
Article in GE Portuguese journal of gastroenterology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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9 authors at 2 institutions in 1 country.
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Abstract
backgroundVideo 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.
methodsAlgorithm 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.
resultsOverall 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 (
conclusionThe 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.
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