Abstract
Computations of fractional flow reserve, based on CT coronary angiography and computational fluid dynamics (CT-based FFR) to assess the severity of coronary artery stenosis, was introduced around a decade ago and is now one of the most successful applications of computational fluid dynamic modelling in clinical practice. Although the mathematical modelling framework behind this approach and the clinical operational model vary, its clinical efficacy has been demonstrated well in general. In this review, technical elements behind CT-based FFR computation are summarised with some key assumptions and challenges. Examples of these challenges include the complexity of the model (such as blood viscosity and vessel wall compliance modelling), whose impact has been debated in the research. Efforts made to address the practical challenge of processing time are also reviewed. Then, further application areas—myocardial bridge, renal stenosis and lower limb stenosis—are discussed along with specific challenges expected in these areas.
Highlights
Computationally-derived fractional flow reserve (FFR) is one of the most promising non-invasive tools ready for expanded use in clinical cardiology
3.1 Analysis platform and speed In the previous section, we described that CT-based FFR computation has successfully been applied in various clinical scenarios, with some technical challenges associated with assumptions in the model
Overall, lower limb ischaemic disease is a promising application of CT-based FFR technology because this routine clinical diagnosis involves many haemodynamic measurements that can be used for boundary conditions of computational fluid dynamics (CFD) modelling[63], among which duplex ultrasound and extremity segmental pressures are useful source of information
Summary
Computationally-derived fractional flow reserve (FFR) is one of the most promising non-invasive tools ready for expanded use in clinical cardiology. The use of FFR during coronary angiography has been successful in improving patient selection for revascularization[1]. This method is invasive and cannot be repeated readily with follow-up of patients with coronary disease. This highlights the need for developing reliable non-invasive methods for measuring FFR. We here review the development and potential applications of CT-based measurements of FFR (CT-FFR)
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