A Study Of The Influence Of Coronary CTA-based Fractional Flow Reserve On Clinical Management Decisions And Outcomes Of Coronary Heart Disease

Part 1.Impact of Machine Learning Based Coronary Computed Tomography Angiography Derived Fractional Flow Reserve on Treatment Decision Making and Clinical Outcome in Patients with Suspected Coronary Disease Objective: To investigate the impact of coronary computed tomography angiography(CCTA)-derived machine learning(ML)-based fractional flow reserve(CT-FFR)compared to invasive coronary angiography(ICA)for therapeutic decision-making and clinical outcome in patients with suspected coronary artery disease.Methods:1121 consecutive patients with stable chest pain who underwent CCTA followed by ICA within 90 days over a ten-year period between January 2007 and December 2016 were included in this retrospective study.Patient follow-up for major adverse cardiac events(MACE)was performed.CT-FFR values were calculated using an artificial intelligence(AI)ML platform.Discordant results between severe stenosis via CT-FFR and severe stenosis on qualitative CCTA and ICA were also evaluated.The primary aim of the study was to assess the difference in trea CT-FFR,as a non-invasive diagnostic tool for assessing lesion-specific ischemia,directs therapeutic decision making with the potential to rationalize diagnostic workflows in patients with suspected CAD.tment strategy as directed by ICA alone versus CCTA with subsequent CT-FFR analysis.Results: CT-FFR was discordant with stenosis in 20.4%(229/1121)of patients for CCTA and 16.4%(184/1121)for ICA.After CT-FFR was revealed,ICA-based treatment regime change was seen in 167 patients(14.9%).Reserving ICA and revascularization for vessels with positive CT-FFR could reduce 54.5% ICA and lead to 4.4% fewer stent implantations.During median follow-up 26 months,positive CT-FFR was associated with MACE(HR:6.84,p<0.001),with superior prognostic value compared to severe stenosis on ICA(HR:1.84,p=0.002)and CCTA(HR:1.47,p=0.045).Conclusions: ML-based CT-FFR shows excellent performance in identifying patients with and without the need for invasive evaluation by ICA and better outcome prediction than severe anatomic stenosis on CCTA.CT-FFR,as a non-invasive diagnostic tool for assessing lesion-specific ischemia,directs therapeutic decision making with the potential to rationalize diagnostic workflows in patients with suspected CAD.Part 2.Prognostic Implication of CT-FFR Based Functional SYNTAX Score in Patients with Three-Vessel DiseaseObjective: The SYNTAX score(SS)is a pure anatomic score based on invasive coronary angiogram(ICA)and predicts outcome in patients with 3-vessel coronary artery disease(CAD).The feasibility and prognostic implication of “Functional SS(FSS_CTA)” using a machine learning(ML)based CCTA derived fractional flow reserve(CT-FFR)in patients with three-vessel CAD have not yet been investigated.This study was aimed at investigating whether a ML based FSS_CTA would predict clinical outcome in patients with three-vessel CAD.Methods: The SS based on CTA(SS_CTA)and ICA(SS_CTA)were retrospectively collected in 227 patients with three-vessel CAD.FSS_CTA was derived from a ML based CT-FFR assessment.The ability of each score system to predict major adverse cardiac events(MACE)was compared.The difference between revascularization strategies directed by anatomical SS and FSS_CTA was also assessed.Results:227 patients were divided into two groups according to the SS_CTA cut-off value of 22.After determining FSS_CTA for each patient,22.9% of patients(52/227)were reclassified to a low-risk group(FSS_CTA?22).In the low vs.intermediate-to-high(>22)FSS_CTA group,MACE occurred in 3.2%(4/125)vs.34.3%(35/102)respectively(p<0.001).The independent predictor of MACE was FSS_CTA(OR=1.21,p=0.001)and diabetes(OR=2.3,p=0.048).FSS_CTA demonstrated a better predictive accuracy for MACE compared with SS_CTA(AUC:0.81 vs.0.75,p=0.01)and SSICA(0.81 vs.0.75,p<0.001).After FSS_CTA was revealed,52 patients initially referred for CABG based on SS_CTA would have been changed to PCI.Conclusions: Recalculating SS by incorporating lesion-specific ischemia as determined by ML based CT-FFR is a better predictor of MACE in patients with three-vessel CAD.Additionally,the use of FSS_CTA may alter selected revascularization strategies in these patients.Part 3.Cinical Outcomes of Anatomical versus Functional Coronary CT Angiography for Coronary Artery DiseaseObjective: This study compared the downstream care and clinical outcomes of a machine learning(ML)-based fractional flow reserve derived from computed tomography(CT-FFR),“functional CCTA” compared with anatomical CCTA in patients with intermediate stenosis.Methods: Patients suspected coronary artery disease(CAD)with intermediate stenosis undergoing CCTA were included in this prospective study.Eligible patients were assigned to anatomical(CCTA)or functional CCTA(CT-FFR)group.The primary end point was the normalcy rate of invasive coronary angiography(ICA)within 90 days that showed non-obstructive stenosis(luminal stenosis?50%).Secondary end points are coronary revascularization and major adverse cardiovascular events(MACE).Results:533 subjects were allocated to the CT-FFR group and 532 to the anatomical CCTA group.At 90 days' follow-up,the rate of ICA demonstrating non-obstructive disease was higher in the anatomical CCTA group(28.8%,23/90)compared with that(2.1%,11/81)in the CT-FFR group(risk difference [RD]=15.2%,p=0.036).The referred ICA rate was significantly higher in the CCTA group(24.2%)than CT-FFR group(18.8%)(RD=5.4%,p=0.029).The revascularization(REV)-to-ICA ratio was30.2%(39/90)for those in the CCTA group,which was lower than the CT-FFR group(63.0%,51/81)(RD=19.7%,p<0.001).MACE was significantly more common among patients in the CCTA group compared with patients in the CT-FFR group(HR:1.76;95% CI: 1.02 to 3.31,p=0.046).Conclusions: In stable patients with intermediate stenosis,the CT-FFR strategy was associated with a lower rate referral for ICA,a normalcy rate of ICA demonstrating non-obstructive disease,and better clinical outcome than the anatomical CCTA strategy.This supports the usefulness of functional CCTA as an efficient method to guide patient management.