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Coronary CT Angiography in the Cath Lab: Leveraging Artificial Intelligence to Plan and Guide Percutaneous Coronary Intervention.
Ohashi, Hirofumi; Bouisset, Frédéric; Buytaert, Dimitri; Seki, Ruiko; Sonck, Jeroen; Sakai, Koshiro; Belmonte, Marta; Kitslaar, Pieter; Updegrove, Adam; Amano, Tetsuya; Andreini, Daniele; De Bruyne, Bernard; Collet, Carlos.
Afiliação
  • Ohashi H; Cardiovascular Center OLV Aalst, Belgium.
  • Bouisset F; Department of Cardiology, Aichi Medical University Aichi, Japan.
  • Buytaert D; Cardiovascular Center OLV Aalst, Belgium.
  • Seki R; Department of Cardiology, Toulouse University Hospital Toulouse, France.
  • Sonck J; Cardiovascular Center OLV Aalst, Belgium.
  • Sakai K; Cardiovascular Center OLV Aalst, Belgium.
  • Belmonte M; Cardiovascular Center OLV Aalst, Belgium.
  • Kitslaar P; Cardiovascular Center OLV Aalst, Belgium.
  • Updegrove A; Department of Cardiology, Showa University Hospital Tokyo, Japan.
  • Amano T; Cardiovascular Center OLV Aalst, Belgium.
  • Andreini D; Department of Advanced Biomedical Sciences, University Federico II Naples, Italy.
  • De Bruyne B; Medis Medical Imaging Systems Leiden the Netherlands.
  • Collet C; HeartFlow Inc. Redwood City CA, US.
Interv Cardiol ; 18: e26, 2023.
Article em En | MEDLINE | ID: mdl-38125928
ABSTRACT
The role of coronary CT angiography for the diagnosis and risk stratification of coronary artery disease is well established. However, its potential beyond the diagnostic phase remains to be determined. The current review focuses on the insights that coronary CT angiography can provide when planning and performing percutaneous coronary interventions. We describe a novel approach incorporating anatomical and functional pre-procedural planning enhanced by artificial intelligence, computational physiology and online 3D CT guidance for percutaneous coronary interventions. This strategy allows the individualisation of patient selection, optimisation of the revascularisation strategy and effective use of resources.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article