The diagnostic study of second-generation motion correction algorithm in improving the accuracy of CT-derived fractional flow reserve calculations
10.3760/cma.j.cn112149-20230904-00157
- VernacularTitle:第二代追踪冻结技术提高CT冠状动脉血流储备分数计算准确度的诊断研究
- Author:
Wenli YANG
1
;
Ziting LAN
;
Lihua YU
;
Yarong YU
;
Xu DAI
;
Shuai ZHANG
;
Nianyun LI
;
Jiayin ZHANG
Author Information
1. 上海交通大学医学院附属第一人民医院放射科，上海 200080
- Keywords:
Coronary artery disease;
Fractional flow reserve;
Coronary computed tomographic angiography;
Motion correction;
Image quality
- From:
Chinese Journal of Radiology
2024;58(7):721-728
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the diagnostic performance of CT-derived fractional flow reserve (CT-FFR) derived from standard images (STD), images processed by first-generation (SSF1) and second-generation (SSF2) whole-heart motion correction algorithm, respectively.Methods:Patients who underwent both coronary CT angiography (CCTA) and invasive coronary angiography (ICA) with FFR examination within 3 months in Shanghai General Hospital, Shanghai Jiao Tong Univerisity School of Medicine from January 2020 to December 2022 were screened in this retrospective study. Totally of 121 patients (134 lesions) were finally included in the study. CCTA images were reconstructed using iterative reconstruction, iterative reconstruction plus SSF1 and SSF2 algorithms. All images were divided into three groups: STD group, SSF1 group, and SSF2 group. The image quality of the CCTA images was assessed using the Likert scale, and differences between the two groups were compared using the Mann-Whitney U and Kruskal-Wallis test. The correlation and consistency between CT-FFR and FFR were evaluated using Spearman correlation coefficient and Bland-Altman plots. The diagnostic performance of CCTA and CT-FFR from three groups was compared by receiver operating characteristic (ROC) curves. The area under the curve (AUC) was compared using the DeLong test. Results:Compared to the STD group and SSF1 group, the SSF2 group showed the best performance in image quality score (median=3.7). Best correlation ( r=0.652, P<0.001) and consistency (mean difference=0.03) between CT-FFR and FFR were observed in SSF2 group. ROC analysis results revealed that, at the per-lesion level, in the diagnosis of ischemic lesions, the diagnostic performance of CT-FFR in the SSF2 group was significantly better than that of the SSF1 group (AUC=0.88 vs. 0.76, P=0.003), while no significant difference was observed between STD group and SSF1 group ( P=0.125). At the per-patient level, the SSF2 group also demonstrated the highest diagnostic performance. Conclusion:The SSF2 algorithm significantly improved CCTA image quality and enhanced its diagnostic performance for evaluating stenosis severity and CT-FFR calculations.
