Pre-PCI CT-FFR Predicts Target Vessel Failure After Stent Implantation

Author:

Wang Zewen1,Tang Chunxiang2,Zuo Rui2,Zhou Aiming3,Xu Wei1,Zhong Jian2,Xu Zhihan4,Zhang Longjiang12

Affiliation:

1. Department of Radiology, Jinling Hospital, Nanjing Medical University

2. Department of Radiology, Jinling Hospital, Medical School of Nanjing University, Nanjing

3. Department of Radiology, Hai’an Hospital of Traditional Chinese Medicine, Nantong, Jiangsu

4. CT Collaboration, Siemens Healthineers, Shanghai, China

Abstract

Objectives: To investigate the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) before percutaneous coronary intervention (PCI) to predict target vessel failure (TVF) after stent implantation. Methods: This retrospective study included 429 patients (429 vessels) who underwent PCI and stent implantation after CCTA within 3 months. All patients underwent coronary stent implantation between January 2012 and December 2019. A dedicated workstation (Syngo Via, Siemens) was used to analyze and measure the CT-FFR value. The cut-off values of pre-PCI CT-FFR for predicting TVF were defined as 0.80 and the value using the log-rank maximization method, respectively. The primary outcome was TVF, defined as a composite of cardiac death, target vessel myocardial infarction, and clinically driven target vessel revascularization (TVR), which was a secondary outcome. Results: During a median 64.0 months follow-up, the cumulative incidence of TVF was 7.9% (34/429). The cutoff value of pre-PCI CT-FFR based on the log-rank maximization method was 0.74, which was the independent predictor for TVF [hazard ratio (HR): 2.61 (95% CI: 1.13, 6.02); P=0.024] and TVR [HR: 3.63 (95%CI: 1.25, 10.51); P=0.018]. Compared with the clinical risk factor model, pre-PCI CT-FFR significantly improved the reclassification ability for TVF [net reclassification improvement (NRI), 0.424, P<0.001; integrative discrimination index (IDI), 0.011, P=0.022]. Adding stent information to the prediction model resulted in an improvement in reclassification for the TVF (C statistics: 0.711, P=0.001; NRI: 0.494, P<0.001; IDI: 0.020, P=0.028). Conclusions: Pre-PCI CT-FFR ≤0.74 was an independent predictor for TVF or TVR, and integration of clinical, pre-PCI CT-FFR, and stent information models can provide a better risk stratification model in patients with stent implantation.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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