TY - JOUR T1 - Computational fluid dynamics modelling in cardiovascular medicine JF - Heart JO - Heart SP - 18 LP - 28 DO - 10.1136/heartjnl-2015-308044 VL - 102 IS - 1 AU - Paul D Morris AU - Andrew Narracott AU - Hendrik von Tengg-Kobligk AU - Daniel Alejandro Silva Soto AU - Sarah Hsiao AU - Angela Lungu AU - Paul Evans AU - Neil W Bressloff AU - Patricia V Lawford AU - D Rodney Hose AU - Julian P Gunn Y1 - 2016/01/01 UR - http://heart.bmj.com/content/102/1/18.abstract N2 - 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. ER -