CT-FFR vs a model of combined plaque characteristics for identifying ischemia: Results from CT-FFR CHINA trial

Association of the triglyceride glucose index with myocardial ischemia in patients with minimal to moderate coronary artery disease

The triglyceride glucose (TyG) index has been suggested as a reliable substitute to indicate insulin resistance. Several studies have identified the association between the TyG index and cardiovascular disease. However, the association between the TyG index and the incidence of myocardial ischemia in patients with minimal to moderate coronary artery disease (CAD) has not been clearly assessed. We aimed to investigate the association between the TyG index and the incidence of myocardial ischemia in patients with minimal to moderate CAD. A total of 1,697 patients who underwent coronary computed tomography angiography (CTA) examinations and had minimal to moderate CAD were retrospectively included in the study. The TyG index and computed tomography-derived fractional flow reserve (CT-FFR) were used to assess insulin resistance (IR) and myocardial ischemia, respectively. Myocardial ischemia was defined as a CT-FFR value ≤ 0.80. Logistic regression models were used to explore the associations between the TyG index and myocardial ischemia. The incidence of myocardial ischemia was higher in the highest TyG index tertile (T3) group than in the lowest TyG index tertile (T1) group. After adjusting for other variables, the T3 group remained associated with a higher risk of myocardial ischemia than the T1 group did (OR, 1.43; 95% CI, 1.01-2.04; p = 0.047). A 1- standard deviation (SD) increase in the TyG index was correlated with a 19-24% elevated risk of myocardial ischemia when regarding the TyG index was considered as a continuous variable. Subgroup analysis revealed similar effects. A TyG index is associated with a higher risk of myocardial ischemia detected by CT-FFR in patients with minimal to moderate CAD.

Coronary computed tomography angiography imaging features combined with computed tomography-fractional flow reserve, pericoronary fat attenuation index, and radiomics for the prediction of myocardial ischemia

BACKGROUND

This study aimed to predict myocardial ischemia (MIS) by constructing models with imaging features, CT-fractional flow reserve (CT-FFR), pericoronary fat attenuation index (pFAI), and radiomics based on coronary computed tomography angiography (CCTA).

METHODS AND RESULTS

This study included 96 patients who underwent CCTA and single photon emission computed tomography-myocardial perfusion imaging (SPECT-MPI). According to SPECT-MPI results, there were 72 vessels with MIS in corresponding supply area and 105 vessels with no-MIS. The conventional model [lesion length (LL), MDS (maximum stenosis diameter × 100% / reference vessel diameter), MAS (maximum stenosis area × 100% / reference vessel area) and CT value], radiomics model (radiomics features), and multi-faceted model (all features) were constructed using support vector machine. Conventional and radiomics models showed similar predictive efficacy [AUC: 0.76, CI 0.62-0.90 vs. 0.74, CI 0.61-0.88; p > 0.05]. Adding pFAI to the conventional model showed better predictive efficacy than adding CT-FFR (AUC: 0.88, CI 0.79-0.97 vs. 0.80, CI 0.68-0.92; p < 0.05). Compared with conventional and radiomics model, the multi-faceted model showed the highest predictive efficacy (AUC: 0.92, CI 0.82-0.98, p < 0.05).

CONCLUSION

pFAI is more effective for predicting MIS than CT-FFR. A multi-faceted model combining imaging features, CT-FFR, pFAI, and radiomics is a potential diagnostic tool for MIS.

Angiographic Lesion Morphology Provides Incremental Value to Generalize Quantitative Flow Ratio for Predicting Myocardial Ischemia

Aim

The quantitative flow ratio (QFR) is favorable for functional assessment of coronary artery stenosis without pressure wires and induction of hyperemia. The aim of this study was to explore whether angiographic lesion morphology provides incremental value to generalize QFR for predicting myocardial ischemia in unselected patients.

Methods

This study was a substudy to the CT-FFR CHINA trial, referring 345 participants from five centers with suspected coronary artery disease on coronary CT angiography for diagnostic invasive coronary angiography (ICA). Fractional flow reserve (FFR) was measured in all vessels with 30–90% diameter stenosis. QFR was calculated in 186 lesions from 159 participants in a blinded manner. In addition, parameters to characterize lesion features were recorded or measured, including left anterior descending arteries (LADs)-involved lesions, side branch located at stenotic lesion (BL), multiple lesions (ML), minimal lumen diameter (MLD), reference lumen diameter (RLD), percent diameter stenosis (%DS), lesion length (LL), and LL/MLD4. Logistic regression was used to construct two kinds of models by combining single or two lesion parameters with the QFR. The performances of these models were compared with that of QFR on a per-vessel level.

Results

A total of 148 participants (mean age: 59.5 years; 101 men) with 175 coronary arteries were included for final analysis. In total, 81 (46%) vessels were considered hemodynamically significant. QFR correctly classified 82.29% of the vessels using FFR with a cutoff of 0.80 as reference standard. The area under the receiver operating characteristic curve (AUC) of QFR was 0.86 with a sensitivity, specificity, positive predictive value, and negative predictive value of 80.25, 84.04, 81.25, and 83.16%, respectively. The combined models (QFR + LAD + MLD, QFR + LAD + %DS, QFR + BL + MLD, and QFR + BL + %DS) outperformed QFR with higher AUCs (0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.90 vs. 0.86, P = 0.03, respectively). Compared with QFR, the sensitivity of the combined models (QFR + BL and QFR + MLD) was improved (91.36 vs. 80.25%, 91.36 vs. 80.25%, respectively, both P &lt; 0.05) without compromised specificity or accuracy.

Conclusion

Combined with angiographic lesion parameters, QFR can be optimized for predicting myocardial ischemia in unselected patients.

Quantitative assessment of atherosclerotic plaque, recent progress and current limitations

An important advantage of computed tomography coronary angiography (CCTA) is its ability to visualize the presence and severity of atherosclerotic plaque, rather than just assessing coronary artery stenoses. Until recently, assessment of plaque subtypes on CCTA relied on visual assessment of the extent of calcified/non-calcified plaque, or visually identifying high-risk plaque characteristics. Recent software developments facilitate the quantitative assessment of plaque volume or burden on CCTA, and the identification of subtypes of plaque based on their attenuation density. These techniques have shown promise in single and multicenter studies, demonstrating that the amount and type of plaque are associated with subsequent cardiac events. However, there are a number of limitations to the application of these techniques, including the limitations imposed by the spatial resolution of current CT scanners, challenges from variations between reconstruction algorithms, and the additional time to perform these assessments. At present, these are a valuable research technique, but not yet part of routine clinical practice. Future advances that improve CT resolution, standardize acquisition techniques and reconstruction algorithms and automate image analysis will improve the clinical utility of these techniques. This review will discuss the technical aspects of quantitative plaque analysis and present pro and con arguments for the routine use of quantitative plaque analysis on CCTA.

Effect of Coronary Calcification Severity on Measurements and Diagnostic Performance of CT-FFR With Computational Fluid Dynamics: Results From CT-FFR CHINA Trial

Aims: To explore the effect of coronary calcification severity on the measurements and diagnostic performance of computed tomography-derived fractional flow reserve (FFR; CT-FFR).

Methods: This study included 305 patients (348 target vessels) with evaluable coronary calcification (CAC) scores from CT-FFR CHINA clinical trial. The enrolled patients all received coronary CT angiography (CCTA), CT-FFR, and invasive FFR examinations within 7 days. On both per-patient and per-vessel levels, the measured values, accuracy, and diagnostic performance of CT-FFR in identifying hemodynamically significant lesions were analyzed in all CAC score groups (CAC = 0, > 0 to <100, ≥ 100 to <400, and ≥ 400), with FFR as reference standard.

Results: In total, the sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under receiver operating characteristics curve (AUC) of CT-FFR were 85.8, 88.7, 86.9, 87.8, 87.1%, 0.90 on a per-patient level and 88.3, 89.3, 89.5, 88.2, 88.9%, 0.88 on a per-vessel level, respectively. Absolute difference of CT-FFR and FFR values tended to elevate with increased CAC scores (CAC = 0: 0.09 ± 0.10; CAC > 0 to <100: 0.06 ± 0.06; CAC ≥ 100 to <400: 0.09 ± 0.10; CAC ≥ 400: 0.11 ± 0.13; p = 0.246). However, no statistically significant difference was found in patient-based and vessel-based diagnostic performance of CT-FFR among all CAC score groups.

Conclusion: This prospective multicenter trial supported CT-FFR as a viable tool in assessing coronary calcified lesions. Although large deviation of CT-FFR has a tendency to correlate with severe calcification, coronary calcification has no significant influence on CT-FFR diagnostic performance using the widely-recognized cut-off value of 0.8.

Diastolic versus systolic coronary computed tomography angiography derived fractional flow reserve for the identification of lesion-specific ischemia

OBJECTIVES

To investigate the measurement discrepancy of coronary computed tomography angiography (CTA)-derived fractional flow reserve (FFR) between diastolic (CT-FFR-D) and systolic (CT-FFR-S) phases using FFR as the reference standard.

METHODS

Participants, suspected of coronary artery disease and indicated for invasive coronary angiography (ICA) and FFR and coronary CTA and CT-FFR, were enrolled in this study (Clinicaltrials.gov:NCT03692936) from September 2018 to October 2019. For every participant, coronary CTA of both systolic and diastolic phases was postprocessed to calculate CT-FFR-S and CT-FFR-D, respectively. Diagnostic sensitivity, specificity, accuracy, and the area under the receiver operating characteristic (ROC) curve were compared.

RESULTS

A total of 181 lesions from 151 participants (mean age 54.5 ± 7.8 years, 113 males) were analyzed. Of these, 129 lesions from 110 participants were successfully measured both in diastolic and systolic phases. Sensitivity, specificity, and accuracy of CT-FFR-D and CT-FFR-S on per-patient level were 88.9%, 91.3%, 90.1% and 66.7%, 87.7%, 76.7%, on per-vessel level were 89.5%, 91.5%, 90.6% and 66.7%, 87.0%, 77.9%, respectively. The ROC curve of CT-FFR-D was significantly higher than that of CT-FFR-S on both per-patient and per-vessel levels (0.938 vs. 0.771, 0.935 vs. 0.772, both p < 0.0001). In severe hemodynamic lesions (FFR ≤ 0.7), the absolute difference between CT-FFR-S and FFR was significantly higher than that between CT-FFR-D and FFR [0.1636, inter-quartile range (IQR): 0.0662-0.2586 vs. 0.0953, IQR: 0.0496-0.1702, p = 0.035].

CONCLUSION

CT-FFR derived in diastole was superior to that derived in systole in detecting coronary ischemic lesions. For lesions with FFR < 0.7, CT-FFR measured in the diastolic phase was noted to be more closely approximated to FFR.