scholarly journals Non-invasive fractional flow reserve (FFRCT) in the evaluation of acute chest pain – Concepts and first experiences

2021 ◽  
Vol 138 ◽  
pp. 109633
Author(s):  
Andreas M. Fischer ◽  
Marly van Assen ◽  
U. Joseph Schoepf ◽  
Andrew J. Matuskowitz ◽  
Akos Varga-Szemes ◽  
...  
Keyword(s):  
Chest Pain ◽  
Fractional Flow Reserve ◽  
Acute Chest Pain ◽  
Fractional Flow ◽  
Non Invasive ◽  
Flow Reserve

scholarly journals Machine learning-based CT fractional flow reserve assessment in acute chest pain: first experience

2020 ◽  
Vol 10 (4) ◽  
pp. 820-830
Author(s):  
Matthias Eberhard ◽  
Tin Nadarevic ◽  
Andrej Cousin ◽  
Jochen von Spiczak ◽  
Ricarda Hinzpeter ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chest Pain ◽  
Fractional Flow Reserve ◽  
Acute Chest Pain ◽  
Fractional Flow ◽  
Flow Reserve

scholarly journals Value of Machine Learning–based Coronary CT Fractional Flow Reserve Applied to Triple-Rule-Out CT Angiography in Acute Chest Pain

2020 ◽  
Vol 2 (3) ◽  
pp. e190137 ◽  
Author(s):  
Simon S. Martin ◽  
Domenico Mastrodicasa ◽  
Marly van Assen ◽  
Carlo N. De Cecco ◽  
Richard R. Bayer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chest Pain ◽  
Ct Angiography ◽  
Fractional Flow Reserve ◽  
Acute Chest Pain ◽  
Fractional Flow ◽  
Coronary Ct ◽  
Flow Reserve ◽  
Triple Rule Out ◽  
Rule Out

Fractional Flow Reserve: Does a Cut-off Value add Value?

2016 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Shah R Mohdnazri ◽  
◽  
◽  
◽  
Thomas R Keeble ◽  
...  
Keyword(s):  
Fractional Flow Reserve ◽  
Coronary Intervention ◽  
Grey Zone ◽  
Fractional Flow ◽  
Non Invasive ◽  
Invasive Test ◽  
Flow Reserve ◽  
A Value ◽  
Percutaneous Coronary ◽  
Value Add

Fractional flow reserve (FFR) has been shown to improve outcomes when used to guide percutaneous coronary intervention (PCI). There have been two proposed cut-off points for FFR. The first was derived by comparing FFR against a series of non-invasive tests, with a value of ≤0.75 shown to predict a positive ischaemia test. It was then shown in the DEFER study that a vessel FFR value of ≥0.75 was associated with safe deferral of PCI. During the validation phase, a ‘grey zone’ for FFR values of between 0.76 and 0.80 was demonstrated, where a positive non-invasive test may still occur, but sensitivity and specificity were sub-optimal. Clinical judgement was therefore advised for values in this range. The FAME studies then moved the FFR cut-off point to ≤0.80, with a view to predicting outcomes. The ≤0.80 cut-off point has been adopted into clinical practice guidelines, whereas the lower value of ≤0.75 is no longer widely used. Here, the authors discuss the data underpinning these cut-off values and the practical implications for their use when using FFR guidance in PCI.

P6175Prediction of coronary revascularization by coronary computed tomography angiography derived fractional flow reserve - different algorithms for interpretation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
K T Madsen ◽  
K T Veien ◽  
B L Noergaard ◽  
P Larsen ◽  
L Deibjerg ◽  
...  
Keyword(s):  
Chest Pain ◽  
Fractional Flow Reserve ◽  
Predictive Value ◽  
Diagnostic Performance ◽  
Coronary Revascularization ◽  
Standard Of Care ◽  
Fractional Flow ◽  
Coronary Cta ◽  
Flow Reserve ◽  
Stable Chest Pain

Abstract Introduction Coronary CT angiography (CTA) derived fractional flow reserve (FFRct) is increasingly used for guiding referral to invasive procedures in patients with stable chest pain. However, optimal interpretation of FFRct-analysis in terms of location and threshold of applied FFRct-values is unclear. Purpose To evaluate the clinical performance of various vessel-specific physiological FFRct derived measures of ischemia for prediction of standard of care guided coronary revascularization in patients with stable chest pain and coronary artery disease as determined by coronary CTA. Methods Retrospective study in patients with stable chest pain referred for coronary angiography based on coronary CTA. Standard acquired coronary CTA data sets were transmitted for core-laboratory analysis at HeartFlow. Any FFRct value in the major coronary arteries ≥1.8 mm in diameter, including side branches, were registered. Lesions were categorized as positive for ischemia using 6 different algorithms: Lowest in vessel FFRct-value (1) ≤0.75 or (2) ≤0.80; 2 cm distal-to-lesion FFRct-value (3) ≤0.75 or (4) ≤0.80; ΔFFRct (5) ≥0.06 or a combination of 2 and 5. The personnel responsible for downstream patient management had no information regarding FFRct test results. Results A total of 172 patients were included. Revascularization was performed in 62 (35%) patients. The diagnostic performance of different FFRct algorithms for predicting standard of care guided coronary revascularization is shown in the Table. Revascularization Predictions by FFRct N=172 Diagnostic performance FFRCT false negative FFRCT false positive Values given as (%) No. of revasc vessels No. of abnormal vessels FFRCT Algorithm Sens Spec PPV NPV Acc 1 2 3 1 2 3 Distal FFRCT ≤0.75 77 68 58 84 72 12 2 0 29 5 1 Distal FFRCT ≤0.80 92 43 48 90 61 5 0 0 40 20 3 Lesion-specific FFRCT ≤0.75 68 86 74 83 80 17 3 0 12 3 0 Lesion-specific FFRCT ≤0.80 82 78 68 89 80 10 2 0 21 3 1 ΔFFRCT ≥0.06 98 36 47 98 59 1 0 0 51 19 0 Combinationa 92 54 53 92 67 5 0 0 39 12 0 aDistal FFRCT ≤0.80 and ΔFFRCT ≥0.06. Sens = sensitivity; Spec = specificity; PPV = positive predictive value; NPV = negative predictive value; Acc = accuracy; FFRCT = fractional flow reserve derived from coronary CTA; ΔFFRCT = difference between FFRCT-value immediately proximal and distal to lesion; Revasc = revascularized. Conclusion The diagnostic performance of FFRct in terms of predicting standard of care guided coronary revascularization is dependent on the applied algorithm for interpretation of the FFRct-analysis.

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