The usefulness of cardiac CT integrated with FFRCT for planning myocardial revascularization in complex coronary artery disease: a lesson from SYNTAX studies

Favorable impact of FFRCT on myocardial revascularization outcomes: Results from an observational real-world registry

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFRCT) strategy significantly decreases unnecessary invasive coronary angiography and refines the appropriateness of revascularization decision. The present study aimed to evaluate how FFRCT guided - strategy impacts outcomes postrevascularization.

METHODS

We included patients with suspected obstructive coronary artery disease (OCAD in a registry from 2013 to 2021. FFRCT entered Heart-Team decision from 2017. Propensity score adjusted Cox - and logistic - regression analyzed FFRCT's impact on post- revascularization major adverse cardiovascular events (MACE) and myocardial injury (PMI).

RESULTS

Among 7541 patients, 1601 had suspected OCAD. 559 patients underwent revascularization: 69.0 % PCI, 29.7 % CABG and 1.2 % both. 252(45.1 %) patients underwent FFRCT. Over 4.4 ± 2.2 years, 137(24.5 %) patients experienced MACE. FFRCT was associated with a trend toward reduced MACE (HR 0.736, 95 % CI 0.513-1.055, p = 0.095) and significantly reduced all-cause mortality (HR 0.476, 95 % CI 0.230-0.985, p = 0.046). In the post-2017 cohort (413 patients, follow-up 3.7 ± 1.5 years), FFRCT significantly reduced MACE (HR 0.610, 95 % CI 0.390-0.954, P = 0.030) and all-cause mortality (HR 0.285, 95 % CI 0.104-0.779, P = 0.014). In CABG patients, FFRCT was associated with lower PMI incidence (5.3 % vs. 15.6 %, p = 0.044). Multivariable analysis revealed no significant association between FFRCT use and PMI.

CONCLUSIONS

Revascularization decision-making with FFRCT translates into better post-revascularization outcomes, primarily by reducing MACE through lower mortality. There was no clear impact on PMI. These findings suggests that FFRCT's value lies indeed in improving patient selection for revascularization, but warrants further confirmation in randomized clinical trials.

A nomogram model for predicting intramyocardial hemorrhage post-PCI based on SYNTAX score and clinical features

OBJECTIVE

The aim of this study is to develop a nomogram model for predicting the occurrence of intramyocardial hemorrhage (IMH) in patients with Acute Myocardial Infarction (AMI) following Percutaneous Coronary Intervention (PCI). The model is constructed utilizing clinical data and the SYNTAX Score (SS), and its predictive value is thoroughly evaluated.

METHODS

A retrospective study was conducted, including 216 patients with AMI who underwent Cardiac Magnetic Resonance (CMR) within a week post-PCI. Clinical data were collected for all patients, and their SS were calculated based on coronary angiography results. Based on the presence or absence of IMH as indicated by CMR, patients were categorized into two groups: the IMH group (109 patients) and the non-IMH group (107 patients). The patients were randomly divided in a 7:3 ratio into a training set (151 patients) and a validation set (65 patients). A nomogram model was constructed using univariate and multivariate logistic regression analyses. The predictive capability of the model was assessed using Receiver Operating Characteristic (ROC) curve analysis, comparing the predictive value based on the area under the ROC curve (AUC).

RESULTS

In the training set, IMH post-PCI was observed in 78 AMI patients on CMR, while 73 did not show IMH. Variables with a significance level of P < 0.05 were screened using univariate logistic regression analysis. Twelve indicators were selected for multivariate logistic regression analysis: heart rate, diastolic blood pressure, ST segment elevation on electrocardiogram, culprit vessel, symptom onset to reperfusion time, C-reactive protein, aspartate aminotransferase, lactate dehydrogenase, creatine kinase, creatine kinase-MB, high-sensitivity troponin T (HS-TnT), and SYNTAX Score. Based on multivariate logistic regression results, two independent predictive factors were identified: HS-TnT (Odds Ratio [OR] = 1.61, 95% Confidence Interval [CI]: 1.21-2.25, P = 0.003) and SS (OR = 2.54, 95% CI: 1.42-4.90, P = 0.003). Consequently, a nomogram model was constructed based on these findings. The AUC of the nomogram model in the training set was 0.893 (95% CI: 0.840-0.946), and in the validation set, it was 0.910 (95% CI: 0.823-0.970). Good consistency and accuracy of the model were demonstrated by calibration and decision curve analysis.

CONCLUSION

The nomogram model, constructed utilizing HS-TnT and SS, demonstrates accurate predictive capability for the risk of IMH post-PCI in patients with AMI. This model offers significant guidance and theoretical support for the clinical diagnosis and treatment of these patients.

Is it the Time to Move Towards Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve Guided Percutaneous Coronary Intervention? The Pros and Cons

Coronary artery disease is the leading cause of mortality worldwide. Diagnosis is conventionally performed by direct visualization of the arteries by invasive coronary angiography (ICA), which has inherent limitations and risks. Measurement of fractional flow reserve (FFR) has been suggested for a more accurate assessment of ischemia in the coronary artery with high accuracy for determining the severity and decision on the necessity of intervention. Nevertheless, invasive coronary angiography-derived fractional flow reserve (ICA-FFR) is currently used in less than one-third of clinical practices because of the invasive nature of ICA and the need for additional equipment and experience, as well as the cost and extra time needed for the procedure. Recent technical advances have moved towards non-invasive high-quality imaging modalities, such as magnetic resonance, single-photon emission computed tomography, and coronary computed tomography (CT) scan; however, none had a definitive modality to confirm hemodynamically significant coronary artery stenosis. Coronary computed tomography angiography (CCTA) can provide accurate anatomic and hemodynamic data about the coronary lesion, especially calculating fractional flow reserve derived from CCTA (CCTA-FFR). Although growing evidence has been published regarding CCTA-FFR results being comparable to ICA-FFR, CCTA-FFR has not yet replaced the invasive conventional angiography, pending additional studies to validate the advantages and disadvantages of each diagnostic method. Furthermore, it has to be identified whether revascularization of a stenotic lesion is plausible based on CCTA-FFR and if the therapeutic plan can be determined safely and accurately without confirmation from invasive methods. Therefore, in the present review, we will outline the pros and cons of using CCTA-FFR vs. ICA-FFR regarding diagnostic accuracy and treatment decision-making.