title: "Virtual" (Computed) Fractional Flow Reserve: Current Challenges and Limitations.
abstract: Fractional flow reserve (FFR) is the "gold standard" for assessing the physiological significance of coronary artery disease during invasive coronary angiography. FFR-guided percutaneous coronary intervention improves patient outcomes and reduces stent insertion and cost; yet, due to several practical and operator related factors, it is used in <10% of percutaneous coronary intervention procedures. Virtual fractional flow reserve (vFFR) is computed using coronary imaging and computational fluid dynamics modeling. vFFR has emerged as an attractive alternative to invasive FFR by delivering physiological assessment without the factors that limit the invasive technique. vFFR may offer further diagnostic and planning benefits, including virtual pullback and virtual stenting facilities. However, there are key challenges that need to be overcome before vFFR can be translated into routine clinical practice. These span a spectrum of scientific, logistic, commercial, and political areas. The method used to generate 3-dimensional geometric arterial models (segmentation) and selection of appropriate, patient-specific boundary conditions represent the primary scientific limitations. Many conflicting priorities and design features must be carefully considered for vFFR models to be sufficiently accurate, fast, and intuitive for physicians to use. Consistency is needed in how accuracy is defined and reported. Furthermore, appropriate regulatory and industry standards need to be in place, and cohesive approaches to intellectual property management, reimbursement, and clinician training are required. Assuming successful development continues in these key areas, vFFR is likely to become a desirable tool in the functional assessment of coronary artery disease.
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, and Insigneo Institute for In Silico Medicine, Sheffield, United Kingdom; Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom. Electronic address: paul.morris@sheffield.ac.uk.
authors.forename: Paul D
authors.initials: PD
authors.lastname: Morris
authors.affiliation: Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.
authors.forename: Frans N
authors.initials: FN
authors.lastname: van de Vosse
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, and Insigneo Institute for In Silico Medicine, Sheffield, United Kingdom.
authors.forename: Patricia V
authors.initials: PV
authors.lastname: Lawford
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, and Insigneo Institute for In Silico Medicine, Sheffield, United Kingdom.
authors.forename: D Rodney
authors.initials: DR
authors.lastname: Hose
authors.affiliation: Department of Cardiovascular Science, University of Sheffield, and Insigneo Institute for In Silico Medicine, Sheffield, United Kingdom; Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom.
authors.forename: Julian P
authors.initials: JP
authors.lastname: Gunn
mesh_terms: D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging* / Q000503:physiopathology / Q000628:therapy; D003331:Coronary Vessels / Q000000981:diagnostic imaging* / Q000503:physiopathology; D053805:Fractional Flow Reserve, Myocardial; D006801:Humans; D021621:Imaging, Three-Dimensional; D008955:Models, Cardiovascular; D011237:Predictive Value of Tests; D011857:Radiographic Image Interpretation, Computer-Assisted; D015203:Reproducibility of Results; D012720:Severity of Illness Index
keywords: computational fluid dynamics; computational modeling; coronary angiography; fractional flow reserve; percutaneous coronary intervention; virtual fractional flow reserve