Author + information
- 1Nhs, Swansea, United Kingdom
- 2Heart Research, Clinical Sciences, Murdoch Childrens Research Institute, Melbourne, Western Australia, Australia
- 3Department of Cardiology, Swansea, United Kingdom
- 4Institute of Life Sciences, Swansea University, Swansea, United Kingdom
- 5Abertawe Bro Morgannwg University health board, Swansea, United Kingdom
Fractional flow reserve (FFR) improves the assessment of the physiological significance of coronary lesions compared with conventional angiography. However, it requires additional interventional techniques and equipment to perform. Recently proposed virtual functional indices are derived from coronary imaging alone but require complex computational fluid dynamics modelling which is time-consuming and hence cannot influence immediate clinical management. We tested the diagnostic performance of a virtual FFR (vFFR) using routine angiographic images and a rapidly performed reduced order computational model.
Quantitative coronary angiography (QCA) was performed in 102 vessels (85 patients) with coronary lesions assessed by invasive FFR. A vFFR for each lesion was created using reduced order computational flow modelling based on parameters derived from conventional angiographic images and patient specific estimates of coronary flow then weighted for myocardial mass using a previously validated Myocardial Jeopardy Score. The diagnostic accuracy of vFFR and diameter stenosis (graded by QCA) was compared against the gold standard of FFR.
The 85 patients included 62 males with mean age of 64 ± 9 years old. QCA revealed mean coronary stenosis area was 54% ± 16% and lesion length 13 ± 7 mm. Once angiographic analysis of the coronary artery had been performed, calculation of the vFFR took less than 1 minute. Coronary stenosis (QCA) had a statistically significant but weak correlation with FFR (-0.2, p= 0.04) and poor diagnostic performance to determine lesions causing significant reductions in FFR (<0.80), (area under the receiver operator characteristic curve (AUC) 0.60, p= 0.11); sensitivity (stenosis 50%) was 24% and specificity 44%. In contrast, vFFR had a stronger correlation with FFR (r=0.45, p<0.0001) and significantly better diagnostic performance (AUC 0.76, p<0.001), sensitivity (vFFR = 0.75) 42% and specificity 90%.
Virtual FFR improves determination of the functional significance of coronary lesions compared with conventional angiography. It is derived using routine angiographic data and does not require a pressure-wire or hyperaemia induction. It is fast enough to influence immediate clinical decision making and may potentially rule out significant lesions with high sensitivity but requires further clinical evaluation.
IMAGING: FFR and Physiologic Lesion Assessment