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Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett's esophagus: a tandem randomized and video trial.
Meinikheim, Michael; Mendel, Robert; Palm, Christoph; Probst, Andreas; Muzalyova, Anna; Scheppach, Markus W; Nagl, Sandra; Schnoy, Elisabeth; Römmele, Christoph; Schulz, Dominik A H; Schlottmann, Jakob; Prinz, Friederike; Rauber, David; Rückert, Tobias; Matsumura, Tomoaki; Fernández-Esparrach, Glòria; Parsa, Nasim; Byrne, Michael F; Messmann, Helmut; Ebigbo, Alanna.
Afiliación
  • Meinikheim M; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Mendel R; Regensburg Medical Image Computing, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.
  • Palm C; Regensburg Medical Image Computing, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.
  • Probst A; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Muzalyova A; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Scheppach MW; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Nagl S; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Schnoy E; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Römmele C; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Schulz DAH; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Schlottmann J; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Prinz F; Department of Gastroenterology, University Hospital Augsburg, Augsburg, Germany.
  • Rauber D; Regensburg Medical Image Computing, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.
  • Rückert T; Regensburg Medical Image Computing, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.
  • Matsumura T; Department of Gastroenterology, Chiba University Graduate School of Medicine, Chiba, Japan.
  • Fernández-Esparrach G; Endoscopy Unit, Gastroenterology Department, ICMDM, Hospital Clínic de Barcelona, Barcelona, Spain.
  • Parsa N; Faculty of Medicine, University of Barcelona, Barcelona, Spain.
  • Byrne MF; Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.
  • Messmann H; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Barcelona, Spain.
  • Ebigbo A; Division of Gastroenterology and Hepatology, Mayo Clinic, Scottsdale, United States.
Endoscopy ; 56(9): 641-649, 2024 Sep.
Article en En | MEDLINE | ID: mdl-38547927
ABSTRACT

BACKGROUND:

This study evaluated the effect of an artificial intelligence (AI)-based clinical decision support system on the performance and diagnostic confidence of endoscopists in their assessment of Barrett's esophagus (BE).

METHODS:

96 standardized endoscopy videos were assessed by 22 endoscopists with varying degrees of BE experience from 12 centers. Assessment was randomized into two video sets group A (review first without AI and second with AI) and group B (review first with AI and second without AI). Endoscopists were required to evaluate each video for the presence of Barrett's esophagus-related neoplasia (BERN) and then decide on a spot for a targeted biopsy. After the second assessment, they were allowed to change their clinical decision and confidence level.

RESULTS:

AI had a stand-alone sensitivity, specificity, and accuracy of 92.2%, 68.9%, and 81.3%, respectively. Without AI, BE experts had an overall sensitivity, specificity, and accuracy of 83.3%, 58.1%, and 71.5%, respectively. With AI, BE nonexperts showed a significant improvement in sensitivity and specificity when videos were assessed a second time with AI (sensitivity 69.8% [95%CI 65.2%-74.2%] to 78.0% [95%CI 74.0%-82.0%]; specificity 67.3% [95%CI 62.5%-72.2%] to 72.7% [95%CI 68.2%-77.3%]). In addition, the diagnostic confidence of BE nonexperts improved significantly with AI.

CONCLUSION:

BE nonexperts benefitted significantly from additional AI. BE experts and nonexperts remained significantly below the stand-alone performance of AI, suggesting that there may be other factors influencing endoscopists' decisions to follow or discard AI advice.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Esófago de Barrett / Neoplasias Esofágicas / Inteligencia Artificial / Esofagoscopía / Sistemas de Apoyo a Decisiones Clínicas Idioma: En Revista: Endoscopy Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Esófago de Barrett / Neoplasias Esofágicas / Inteligencia Artificial / Esofagoscopía / Sistemas de Apoyo a Decisiones Clínicas Idioma: En Revista: Endoscopy Año: 2024 Tipo del documento: Article