title: Computational fluid dynamics modelling in cardiovascular medicine.
abstract: This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Morris
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Narracott
authors.affiliation: University Institute for Diagnostic, Interventional and Pediatric Radiology, University Hospital of Bern, Inselspital, Bern, Switzerland.
authors.forename: Hendrik
authors.initials: H
authors.lastname: von Tengg-Kobligk
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: Daniel Alejandro
authors.initials: DA
authors.lastname: Silva Soto
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK.
authors.forename: Sarah
authors.initials: S
authors.lastname: Hsiao
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: Angela
authors.initials: A
authors.lastname: Lungu
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: Paul
authors.initials: P
authors.lastname: Evans
authors.affiliation: Faculty of Engineering & the Environment, University of Southampton, Southampton, UK.
authors.forename: Neil W
authors.initials: NW
authors.lastname: Bressloff
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: Patricia V
authors.initials: PV
authors.lastname: Lawford
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK.
authors.forename: D Rodney
authors.initials: DR
authors.lastname: Hose
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, Sheffield, UK Insigneo Institute for In Silico Medicine, Sheffield, UK Department of Cardiology, Sheffield Teaching Hospitals NHS Trust, Sheffield, UK.
authors.forename: Julian P
authors.initials: JP
authors.lastname: Gunn
mesh_terms: D000818:Animals; D006348:Cardiac Surgical Procedures / Q000295:instrumentation; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000503:physiopathology* / Q000628:therapy; D002319:Cardiovascular System / Q000473:pathology / Q000503:physiopathology*; D003198:Computer Simulation; D017076:Computer-Aided Design; D003952:Diagnostic Imaging / Q000379:methods; D006439:Hemodynamics; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008955:Models, Cardiovascular; D011237:Predictive Value of Tests; D011474:Prosthesis Design; D019919:Prosthesis Implantation / Q000295:instrumentation