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Opportunities and challenges of implementing computed tomography fractional flow reserve into clinical practice.

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Nazir, Muhummad Sohaib  ORCID logo
Mittal, Tarun K 
Weir-McCall, Jonathan  ORCID logo
Nieman, Koen 
Channon, Keith 


CT-derived fractional flow reserve (CT-FFR) uses computational fluid dynamics to derive non-invasive FFR to determine the haemodynamic significance of coronary artery lesions. Studies have demonstrated good diagnostic accuracy of CT-FFR and reassuring short-term clinical outcome data.As a prerequisite, high-quality CT coronary angiography (CTCA) images are required with good heart rate control and pre-treatment with glyceryl trinitrate, which would otherwise render CTCA as unsuitable for CT-FFR. CT-FFR can determine the functional significance of CAD lesions, and there are supportive data for its use in clinical decision-making. However, the downstream impact on myocardial ischaemic burden or viability cannot be obtained.Several challenges remain with implementation of CT-FFR, including interpretation, training, availability, resource utilisation and funding. Further research is required to determine which cases should be considered for clinical CT-FFR analysis, with additional practical guidance on how to implement this emerging technique in clinical practice. Furthermore, long-term prognostic data are required before widespread clinical implementation of CT-FFR can be recommended.While there are several potential opportunities for CT-FFR, at present there remain important systemic and technical limitations and challenges that need to be overcome prior to routine integration of CT-FFR into clinical practice.



advanced cardiac imaging, cardiac computer tomographic (CT) imaging, chronic coronary disease, coronary artery disease, Clinical Decision-Making, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Vessels, Fractional Flow Reserve, Myocardial, Humans, Hydrodynamics, Models, Cardiovascular, Predictive Value of Tests, Prognosis, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results, Severity of Illness Index

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