Literature DB >> 32150486

Evaluation of the sensitivity of the Express View function in the Mirocam® capsule endoscopy software.

C Gomes1, R Pinho1, A Ponte1, A Rodrigues1, M Sousa1, J C Silva1, E Afecto1, J Carvalho1.   

Abstract

Background: A new computer algorithm called Express-View has recently been introduced by Mirocam, but data concerning its application and efficacy are scarce.Objective: To evaluate the lesion detection rate, per-patient sensitivity and the diagnostic accuracy using Express-View.
Methods: All patients who performed CE between January 2018 and June 2019, whose indication was obscure gastrointestinal bleeding (OGIB) and with findings on CE, were included. Lesions identified in conventional reading were selected and considered as reference.
Results: Eighty-nine patients were included, 50.6% male, with a mean age of 68.4 years-old (±12.3). The Express-View mode detected 85.5% of lesions previously detected by conventional reading (524 out of 613). There were 89 missed lesions, mainly erosions or ulcers (44.9%) and angioectasias (38.2%). The lesion detection rate was found to be lower in the jejunum and ileum compared to extra-small bowel locations and duodenum (p = .04). Although Express-View had a per-patient sensitivity for all lesions of 56.2% and a per-patient sensitivity for all clinically significant lesions of 83.1%, it achieved a diagnostic accuracy of 91%.Conclusions: The per-patient sensitivity for all lesions was shown to be below expectations, although the lesion detection rate, the per-patient sensitivity for all clinically significant lesions, and the diagnostic accuracy were shown to be higher.

Entities:  

Keywords:  Capsule endoscopy; Express-View; diagnostic accuracy; lesion detection; per patient sensitivity; reading time

Mesh:

Year:  2020        PMID: 32150486     DOI: 10.1080/00365521.2020.1734650

Source DB:  PubMed          Journal:  Scand J Gastroenterol        ISSN: 0036-5521            Impact factor:   2.423


  2 in total

1.  New Generation Express View: An Artificial Intelligence Software Effectively Reduces Capsule Endoscopy Reading Times.

Authors:  Stefania Piccirelli; Alessandro Mussetto; Angelo Bellumat; Renato Cannizzaro; Marco Pennazio; Alessandro Pezzoli; Alessandra Bizzotto; Nadia Fusetti; Flavio Valiante; Cesare Hassan; Silvia Pecere; Anastasios Koulaouzidis; Cristiano Spada
Journal:  Diagnostics (Basel)       Date:  2022-07-22

Review 2.  Artificial intelligence in small intestinal diseases: Application and prospects.

Authors:  Yu Yang; Yu-Xuan Li; Ren-Qi Yao; Xiao-Hui Du; Chao Ren
Journal:  World J Gastroenterol       Date:  2021-07-07       Impact factor: 5.742

  2 in total

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