Myocardial perfusion distribution and coronary arterial pressure and flow signals: clinical relevance in relation to multiscale modeling, a review

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• 作者：Froukje Nolte (1)
  Eoin R. Hyde (2)
  Cristina Rolandi (1)
  Jack Lee (2)
  Pepijn van Horssen (1)
  Kal Asrress (3)
  Jeroen P. H. M. van den Wijngaard (1)
  Andrew N. Cookson (2)
  Tim van de Hoef (1) (4)
  Radomir Chabiniok (2)
  Reza Razavi (3)
  Christian Michler (2)
  Gilion L. T. F. Hautvast (5) (6)
  Jan J. Piek (4)
  Marcel Breeuwer (5) (7)
  Maria Siebes (1)
  Eike Nagel (3)
  Nic P. Smith (2)
  Jos A. E. Spaan (1)
  
• 关键词：Multi scale modeling ; Coronary disease ; Coronary stenosis evaluation ; Magnetic resonance imaging ; Perfusion distribution
• 刊名：Medical and Biological Engineering and Computing
• 出版年：2013
• 出版时间：November 2013
• 年：2013
• 卷：51
• 期：11
• 页码：1271-1286
• 全文大小：
• 作者单位：Froukje Nolte (1)
  Eoin R. Hyde (2)
  Cristina Rolandi (1)
  Jack Lee (2)
  Pepijn van Horssen (1)
  Kal Asrress (3)
  Jeroen P. H. M. van den Wijngaard (1)
  Andrew N. Cookson (2)
  Tim van de Hoef (1) (4)
  Radomir Chabiniok (2)
  Reza Razavi (3)
  Christian Michler (2)
  Gilion L. T. F. Hautvast (5) (6)
  Jan J. Piek (4)
  Marcel Breeuwer (5) (7)
  Maria Siebes (1)
  Eike Nagel (3)
  Nic P. Smith (2)
  Jos A. E. Spaan (1)
  
  1. Department of Biomedical Engineering and Physics, Academic Medical Center, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands
  2. Imaging Sciences and Biomedical Engineering Division, St Thomas’ Hospital, King’s College London, London, SE17EH, UK
  3. Division of Imaging Sciences, BHF Centre of Research Excellence, The Rayne Institute, St. Thomas’ Hospital, London, UK
  4. Department of Cardiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
  5. Philips Research, Eindhoven, The Netherlands
  6. Philips Healthcare, Imaging Systems, MR Clinical Science, Best, The Netherlands
  7. Eindhoven University of Technology, Biomedical Engineering, Biomedical Image Analysis, Eindhoven, The Netherlands
  
• ISSN：1741-0444

文摘

Coronary artery disease, CAD, is associated with both narrowing of the epicardial coronary arteries and microvascular disease, thereby limiting coronary flow and myocardial perfusion. CAD accounts for almost 2 million deaths within the European Union on an annual basis. In this paper, we review the physiological and pathophysiological processes underlying clinical decision making in coronary disease as well as the models for interpretation of the underlying physiological mechanisms. Presently, clinical decision making is based on non-invasive magnetic resonance imaging, MRI, of myocardial perfusion and invasive coronary hemodynamic measurements of coronary pressure and Doppler flow velocity signals obtained during catheterization. Within the euHeart project, several innovations have been developed and applied to improve diagnosis-based understanding of the underlying biophysical processes. Specifically, MRI perfusion data interpretation has been advanced by the gradientogram, a novel graphical representation of the spatiotemporal myocardial perfusion gradient. For hemodynamic data, functional indices of coronary stenosis severity that do not depend on maximal vasodilation are proposed and the Valsalva maneuver for indicating the extravascular resistance component of the coronary circulation has been introduced. Complementary to these advances, model innovation has been directed to the porous elastic model coupled to a one-dimensional model of the epicardial arteries. The importance of model development is related to the integration of information from different modalities, which in isolation often result in conflicting treatment recommendations.