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Artificial intelligence facilitates measuring reflux episodes and postreflux swallow-induced peristaltic wave index from impedance-pH studies in patients with reflux disease.
Wong, Ming-Wun; Liu, Min-Xiang; Lei, Wei-Yi; Liu, Tso-Tsai; Yi, Chih-Hsun; Hung, Jui-Sheng; Liang, Shu-Wei; Lin, Lin; Tseng, Chiu-Wang; Wang, Jen-Hung; Wu, Ping-An; Chen, Chien-Lin.
Afiliación
  • Wong MW; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Liu MX; School of Post-Baccalaureate Chinese Medicine, Tzu Chi University, Hualien, Taiwan.
  • Lei WY; AI Innovation Research Center, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Huealien, Taiwan.
  • Liu TT; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Yi CH; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Hung JS; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Liang SW; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Lin L; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Tseng CW; Department of Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation and Tzu Chi University, Hualien, Taiwan.
  • Wang JH; NVIDIA AI Technology Center, NVIDIA, Taipei, Taiwan.
  • Wu PA; Department of Medical Research, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
  • Chen CL; AI Innovation Research Center, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Huealien, Taiwan.
Neurogastroenterol Motil ; 35(3): e14506, 2023 03.
Article en En | MEDLINE | ID: mdl-36458529
BACKGROUND/AIM: Reflux episodes and postreflux swallow-induced peristaltic wave (PSPW) index are useful impedance parameters that can augment the diagnosis of gastroesophageal reflux disease (GERD). However, manual analysis of pH-impedance tracings is time consuming, resulting in limited use of these novel impedance metrics. This study aims to evaluate whether a supervised learning artificial intelligence (AI) model is useful to identify reflux episodes and PSPW index. METHODS: Consecutive patients underwent 24-h impedance-pH monitoring were enrolled for analysis. Multiple AI and machine learning with a deep residual net model for image recognition were explored based on manual interpretation of reflux episodes and PSPW according to criteria from the Wingate Consensus. Intraclass correlation coefficients (ICCs) were used to measure the strength of inter-rater agreement of data between manual and AI interpretations. RESULTS: We analyzed 106 eligible patients with 7939 impedance events, of whom 38 patients with pathological acid exposure time (AET) and 68 patients with physiological AET. On the manual interpretation, patients with pathological AET had more reflux episodes and lower PSPW index than those with physiological AET. Overall accuracy of AI identification for reflux episodes and PSPW achieved 87% and 82%, respectively. Inter-rater agreements between AI and manual interpretations achieved excellent for individual numbers of reflux episodes and PSPW index (ICC = 0.965 and ICC = 0.921). CONCLUSIONS: AI has the potential to accurately and efficiently measure impedance metrics including reflux episodes and PSPW index. AI can be a reliable adjunct for measuring novel impedance metrics for GERD in the near future.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reflujo Gastroesofágico / Monitorización del pH Esofágico Tipo de estudio: Guideline / Prognostic_studies Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Neurogastroenterol Motil Asunto de la revista: GASTROENTEROLOGIA / NEUROLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Reflujo Gastroesofágico / Monitorización del pH Esofágico Tipo de estudio: Guideline / Prognostic_studies Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Neurogastroenterol Motil Asunto de la revista: GASTROENTEROLOGIA / NEUROLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Taiwán Pais de publicación: Reino Unido