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CT-FFR vs a model of combined plaque characteristics for identifying ischemia: Results from CT-FFR CHINA trial
1Department of Radiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 167 North Lishi Road, Xicheng District, Beijing, China.
Insights
Fractional flow reserve (FFR) derived from coronary computed tomography angiography (CT-FFR) effectively assesses obstructive coronary artery disease. For nonobstructive disease, plaque characteristics offer a viable alternative to CT-FFR.
Area of Science:
- Cardiovascular Imaging
- Interventional Cardiology
- Diagnostic Accuracy
Background:
- Coronary computed tomography angiography (CCTA) visualizes coronary anatomy but assessing functional significance of stenosis remains challenging.
- Fractional flow reserve (FFR) is the gold standard for determining ischemia, but invasive FFR is resource-intensive.
- CT-derived FFR (CT-FFR) offers a non-invasive method to assess lesion-specific ischemia.
Purpose of the Study:
- To evaluate the diagnostic performance of CT-FFR and plaque characteristics in identifying ischemia across varying CCTA stenosis levels.
- To compare the accuracy of CT-FFR against invasive FFR in patients with coronary artery disease (CAD).
- To identify specific plaque features predictive of ischemia in both obstructive and nonobstructive coronary lesions.
Main Methods:
- A clinical trial involving 317 patients and 366 vessels with 30%-90% coronary stenosis was conducted across 5 centers.
- Vessels were categorized into nonobstructive (<50% stenosis) and obstructive (≥50% stenosis) groups.
- Analysis included lesion length, plaque burden, diameter stenosis, volume ratio of plaque subcomponents <30 HU, and high-risk features. Logistic regression and ROC curve analysis were used to assess diagnostic performance.
Main Results:
- In obstructive lesions (≥50% stenosis), CT-FFR demonstrated high diagnostic accuracy (AUC=0.90) for ischemia, significantly outperforming plaque characteristics (AUC=0.67).
- In nonobstructive lesions (<50% stenosis), a combination of plaque characteristics (volume ratio <30 HU and diameter stenosis) showed diagnostic performance (AUC=0.88) comparable to CT-FFR (AUC=0.88).
- Plaque burden, lesion length, and diameter stenosis were independent predictors of ischemia in nonobstructive lesions.
Conclusions:
- CT-FFR is a powerful non-invasive tool for assessing functional significance in both obstructive and nonobstructive coronary artery disease.
- For nonobstructive CAD visualized by CCTA, a model combining specific plaque characteristics can serve as a valuable alternative to CT-FFR.
- This study highlights the complementary roles of anatomical and functional assessments in managing coronary artery disease.
Objectives:
To evaluate the diagnostic performance of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA; CT-FFR) and combined plaque characteristics for ischemia in different CCTA stenosis levels.
Methods:
This clinical trial analyzed 317 patients with 30 %-90 % coronary stenosis in 366 vessels from 5 centers undergoing CCTA and invasive FFR. 366 vessels were assigned into < 50 % (nonobstructive) and ≥ 50 % (obstructive) stenosis groups. Lesion length (LL), plaque burden (PB), diameter stenosis (DS), volume ratio of plaque subcomponents < 30 HU (VR < 30HU), and high-risk features were analyzed. Logistic regression models were used to identify plaque characteristic predictors for lesion-specific ischemia in different stenosis grades. The area under receiver operating characteristics curve (AUC) of integrated plaque characteristics and CT-FFR were calculated and compared.
Results:
In < 50 % stenosis lesions, PB (OR: 1.296, p = 0.002), LL (OR:1.075, p = 0.020), and DS (OR:1.085, p = 0.031) were independent predictors of ischemia. In ≥ 50 % stenosis lesions, VR < 30HU (OR:1.031, p = 0.005) and DS (OR: 1.020, p = 0.044) were independent predictors for ischemia. AUC of plaque characteristic (VR < 30HU plus DS) for ischemia was 0.67 (95 % CI: 0.61-0.72) in ≥ 50 % stenosis level, which was significantly lower than CT-FFR (AUC=0.90; 95 % CI: 0.86-0.93) (p < 0.001). For lesions causing < 50 % stenosis, AUC of combined plaque model (VR < 30HU plus DS) was 0.88 (95 % CI: 0.80-0.95), equivalent to AUC of CT-FFR (AUC = 0.88; 95 % CI: 0.80-0.96; p = 0.957).
Conclusion:
CT-FFR is a powerful functional assessment tool for both obstructive and nonobstructive diseases. However, for nonobstructive CAD confirmed by CCTA, a model of a combination of plaque characteristics could be a valuable alternative to CT-FFR.
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