Lots of interesting abstracts and cases were submitted for TCTAP 2023. Below are the accepted ones after a thorough review by our official reviewers. Don’t miss the opportunity to expand your knowledge and interact with authors as well as virtual participants by sharing your opinion in the comment section!


Consistency of Quantitative Flow Ratio and Fractional Flow Reserve Evaluation in Patients With Coronary Artery Tortuosity

By Zhenjun Ji, Renhua Sun, Wenjie Zuo, Genshan Ma


Zhenjun Ji


Zhenjun Ji1, Renhua Sun2, Wenjie Zuo1, Genshan Ma1


Southeast University, China1, Tancheng No.1 People's Hospital, Yancheng, China2
View Study Report
Physiologic Lesion Assessment

Consistency of Quantitative Flow Ratio and Fractional Flow Reserve Evaluation in Patients With Coronary Artery Tortuosity

Zhenjun Ji1, Renhua Sun2, Wenjie Zuo1, Genshan Ma1

Southeast University, China1, Tancheng No.1 People's Hospital, Yancheng, China2


Coronary artery tortuosity is a common phenomenon in patients with coronary artery disease (CAD). Severe tortuosity may increase the risk of acute postoperative complications (such as recurrent myocardial infarction in target vessels) in patients receiving percutaneous coronary intervention (PCI). Tortuosity was defined as the presence of ≥3 consecutive curvatures of 90° to 180° in a major epicardial coronary artery ≥2 mm in diameter, measured at the end of diastole. Invasive flow reserve fraction (FFR) examination based on pressure guide wire and adenosine-induced congestion is considered a standard method for functional measurement of coronary stenosis severity. However, the application of FFR is limited because of the defects of pressure wire, the inconvenience and side effects of adenosine, and the increase in operation time and cost. Contrast quantitative flow ratio (cQFR) is a new method for evaluating coronary function based on angiography. We aimed to compare the ability of QFR and fractional flow reserve (FFR) in assessing the severity of tortuosity.


The study was approved by the Ethics Committee of Zhongda Hospital, Southeast University. From 2013.07 to 2019.12, 460 CAD patients receiving FFR examination were enrolled from Zhongda Hospital, Southeast University. The inclusion criteria were: (1) Willingness to participate in the research and sign informed consent; (2) 18-80 years old male or non-pregnant female; (3) Patients with CAD who received coronary angiography and FFR examination. Exclusion criteria: (1) Previous coronary artery bypass surgery history; (2) Chronic coronary artery occlusion; (3) Ostial lesions ofmain coronary arteries; (4) The bifurcation lesions classified as 1,1,1 by Medina; (5) Donor collateral artery; (6) Poor imaging quality not enough to meet the QFR measurement. Experienced cardiologists used the Phillips AlluraXperFD20 digital subtraction angiography machine to perform angiography. It was required that multiple positions were clear, target lesions exposed, and at least two orthogonal positions were used for angiography to evaluate target vessel conditions and provide image support for subsequent analysis. Then, The pressure wire (Abbott, Minnesota) was used for FFR measurement. Quantitative coronary angiography (QCA) and QFR calculation were performed offline by two certified technicians using QFR workstations (AngioPlus, Pulse Medical Imaging Technology, Shanghai Co., Ltd., Shanghai, China), and patient data were blinded to the technicians. All QCA and QFR analyses were based on previously recorded angiography. The data were analyzed by SPSS 23.0 and GraphPad Prism 8. For continuous variables conforming to normality, independent sample T-test was used for comparison between two groups, and one-way ANOVA was used for comparison between multiple groups. The Chi-square test or Fisher’s exact test were used to compare binary variables. Pearson analysis was used for correlation analysis. The receiver operating characteristic curve (ROC) was analyzed to determine the predictive ability of QFR for FFR<0.80 of target vessels. 


(1) 460 CAD patients with 497 target vessels were divided into “no tortuosity group” (n=374), “mild tortuosity group”(n=29), and “severe tortuosity group” (n=94). There were no significant differences in age (P=0.881), stent implantation history of target vessels(P=0.108), and tandem lesion (P=0.454) among these three groups, although there was a significant gender difference among the three groups (P=0.008). (2) There were no significant differences in FFR (P=0.113) and cQFR (P=0.075) values among the three groups. FFR values in the no tortuosity group, mild tortuosity group, and severe tortuosity group were 0.856±0.0780, 0.862±0.061, and 0.838±0.076, respectively, and cQFR values were 0.864±0.083, 0.852±0.071, and 0.843±0.087, respectively. There was also no significant difference in minimal luminal diameter (MLD) (P=0.598), percent area stenosis (%DS) (P=0.685), and lesion length (P=0.653) among the different groups. (3) Correlation analysis showed that cQFR was positively associated with FFR value (P<0.001) in total patients. There were also positive associations in the total tortuosity group (r=0.790, P<0.001), mild tortuosity group (r=0.699, P<0.001), and severe tortuosity group (r=0.810, P<0.001). (4) ROC analysis showed that cQFR showed a significantly better ability to predict FFR<0.80 of target vessels than that of %DS (P<0.001) among all patients. The AUC of cQFR and %DS were 0.903 and 0.748, respectively. The AUC of cQFR and %DS was (0.880 vs. 0.760, P=0.0013) in total tortuosity group, (0.891 vs. 0.609, P=0.0085) in the mild tortuosity group, and (0.878 vs.0.800, P=0.0383) in severe tortuosity group.


cQFR and FFR had similar abilities in assessing the severity of myocardial ischemia in patients with coronary artery tortuosity, which still remained to be validated by larger samples.

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