Noninvasive Quantitative Plaque Analysis Identifies Hemodynamically Significant Coronary Arteries Disease
Peiyan Yin1,2, Guanhua Dou1, Xia Yang1
1Department of Cardiology, Chinese PLA General Hospital, Beijing.
Insights
Automated coronary computed tomography angiography (CCTA) analysis shows maximum area stenosis (MAS%) and lipid plaque burden (LPB) can accurately identify hemodynamic abnormalities. Combining MAS% and LPB improves diagnostic accuracy for lesion-specific hemodynamic abnormalities.
Area of Science:
- Cardiovascular Imaging
- Interventional Cardiology
- Radiology
Background:
- Coronary artery disease diagnosis relies on assessing lesion-specific hemodynamic abnormalities.
- Fractional flow reserve (FFR) is the gold standard for evaluating hemodynamic significance.
- Non-invasive methods like CCTA are increasingly used for coronary artery assessment.
Purpose of the Study:
- To evaluate the diagnostic performance of automated quantitative analysis by coronary computed tomography angiography (CCTA) in identifying lesion-specific hemodynamic abnormality.
- To compare the accuracy of various CCTA-derived indices in predicting hemodynamic significance.
Main Methods:
- 132 patients with 169 vessels (30%-90% stenosis) underwent CCTA and invasive FFR.
- Automated CCTA software quantified plaque characteristics: maximum diameter stenosis (MDS%), maximum area stenosis (MAS%), lipid plaque volume (LPV), and lipid plaque burden (LPB).
- Logistic regression and ROC analysis determined diagnostic performance for hemodynamic abnormalities (FFR ≤0.80).
Main Results:
- Hemodynamically significant lesions (FFR ≤0.80) were present in 33.73% of vessels.
- MAS% and LPV were significantly higher in vessels with hemodynamic significance.
- Multivariable analysis identified MAS% >68% and LPB >10.03% as significant predictors.
- The area under the curve (AUC) for predicting hemodynamic abnormalities was 0.77 for MAS% and 0.71 for MDS%.
- Combining MAS% and LPB (MAS%+LPB) yielded a significantly higher AUC (0.83) compared to MAS% alone (0.77).
Conclusions:
- Automated CCTA quantitative analysis, particularly MAS%, demonstrates high diagnostic accuracy for coronary hemodynamic abnormalities.
- Lipid plaque burden (LPB) also contributes to identifying significant lesions.
- The combined index of MAS%+LPB offers improved diagnostic accuracy over MAS% alone for predicting lesion-specific hemodynamic abnormalities.
Objective:
To evaluate the diagnostic performance of automated quantitative analysis by coronary computed tomography angiography (CCTA) in identifying lesion-specific hemodynamic abnormality.
Methods:
A total of 132 patients (mean age, 61 y; 86 men) with 169 vessels (with 30% to 90% diameter stenosis), who successively underwent invasive coronary angiography with evaluation of fractional flow reserve (values ≤0.8 were defined as lesion-specific hemodynamic abnormalities), were analyzed by CCTA. CCTA images were quantitatively analyzed using automated software to obtain the following index: maximum diameter stenosis (MDS%); maximum area stenosis (MAS%); lesion length (LL); volume and burden (plaque volume×100 per vessel volume) of total plaque (total plaque volume [TPV], total plaque burden [TPB]), calcified plaque (calcified plaque volume [CPV], calcified plaque volume burden [CPB]), noncalcified plaque (noncalcified plaque volume [NCPV], noncalcified plaque volume burden [NCPB]), lipid plaque (lipid plaque volume [LPV], lipid plaque burden [LPB]), and fibrous plaque (fibrotic plaque volume [FPV], fibrotic plaque burden [FPB]); napkin-ring sign (NRS); remodeling index (RI); and eccentric index (EI). Logistic regression and area under the receiver operating characteristics (AUC) were used for statistical analysis.
Results:
Fractional flow reserve ≤0.80 was found in 57 (33.73%) of the 169 vessels. Vessels with hemodynamic significance had greater MDS% (64.43%±8.69% vs. 57.33%±9.95%, P<0.001), MAS% (73.18%±8.56% vs. 64.66%±8.95%, P<0.001), and lipid plaque burden (12.75% [9.73%, 19.56%] vs. 9.41% [4.10%, 15.70%], P=0.01) compared with vessels with normal hemodynamics. In multivariable logistic regression analysis, MAS% >68% (odds ratio: 7.20, 95% confidence interval [CI]=2.89-17.91, P<0.001) and LPB >10.03% (odds ratio=4.32, 95% CI=1.36-13.66, P=0.01) were significant predictors of hemodynamic abnormalities. In predicting lesion-specific hemodynamic abnormalities, the AUC was 0.77 (95% CI=0.70-0.85) for MAS% versus 0.71 (95% CI=0.63-0.79) for MDS% (P<0.05), 0.66 (95% CI=0.58-0.74) for LPV (P<0.05), 0.66 (95% CI=0.58-0.74) for LPB (P<0.05), and 0.63 (95% CI=0.54-0.71) for TPB (P<0.05). The AUC of MAS%+LPB (0.83, 95% CI=0.76-0.89) was significantly improved compared with that of MAS% (0.77, 95% CI=0.70-0.85, P<0.05).
Conclusions:
Compared with MDS% and the volume burdens of plaque compositions, MAS% has a higher diagnostic accuracy for coronary hemodynamic abnormalities in the precise quantitative analysis of coronary plaques on the basis of CT. Furthermore, MAS%+LPB might improve the diagnostic accuracy beyond MAS% alone.
More Related Videos
13:07Optical Coherence Tomography Based Biomechanical Fluid-Structure Interaction Analysis of Coronary Atherosclerosis Progression
Published on: January 15, 2022
09:43In vivo Near Infrared Fluorescence NIRF Intravascular Molecular Imaging of Inflammatory Plaque, a Multimodal Approach to Imaging of Atherosclerosis
Published on: August 4, 2011
Related Concept Videos
01:25Imaging Studies for Cardiovascular System VI: Calcium -Scoring CT
01:30Acute Coronary Syndrome III: Diagnostic Studies
01:30Coronary Artery Disease I: Introduction
01:27Atherosclerosis II: Clinical Manifestations and Diagnostic Tests