Anonymous Comparison of Various Angiography-Derived Fractional Flow Reserve Software With Pressure-Derived Physiological Assessment

Consensus document on the clinical application of invasive functional coronary angiography from the Japanese Association of Cardiovascular Intervention and Therapeutics

Invasive functional coronary angiography (FCA), an angiography-derived physiological index of the functional significance of coronary obstruction, is a novel physiological assessment tool for coronary obstruction that does not require the utilization of a pressure wire. This technology enables operators to rapidly evaluate the functional relevance of coronary stenoses during and even after angiography while reducing the burden of cost and complication risks related to the pressure wire. FCA can be used for treatment decision-making for revascularization, strategy planning for percutaneous coronary intervention, and procedure optimization. Currently, various software-computing FCAs are available worldwide, with unique features in their computation algorithms and functions. With the emerging application of this novel technology in various clinical scenarios, the Japanese Association of Cardiovascular Intervention and Therapeutics task force was created to outline expert consensus on the clinical use of FCA. This consensus document advocates optimal clinical applications of FCA according to currently available evidence while summarizing the concept, history, limitations, and future perspectives of FCA along with globally available software.

Prognostic Implications of Quantitative Flow Ratio and Plaque Characteristics in Intravascular Ultrasound-Guided Treatment Strategy

BACKGROUND

Quantitative flow ratio (QFR) is a method for evaluating fractional flow reserve without the use of an invasive coronary pressure wire or pharmacological hyperemic agent.

OBJECTIVES

The aim of this study was to investigate the prognostic implications of QFR and plaque characteristics in patients who underwent intravascular ultrasound (IVUS)-guided treatment for intermediate lesions.

METHODS

Among the IVUS-guided strategy group in the FLAVOUR (Fractional Flow Reserve and Intravascular Ultrasound for Clinical Outcomes in Patients with Intermediate Stenosis) trial, vessels suitable for QFR analysis were included in this study. High-risk features were defined as low QFR (≤0.90), quantitative high-risk plaque characteristics (qn-HRPCs) (minimal lumen area ≤3.5 mm2, or plaque burden ≥70%), and qualitative high-risk plaque characteristics (ql-HRPCs) (attenuated plaque, positive remodeling, or plaque rupture) assessed using IVUS. The primary clinical endpoint was target vessel failure (TVF), defined as a composite of cardiac death, target vessel myocardial infarction, and target vessel revascularization.

RESULTS

A total of 415 (46.1%) vessels could be analyzable for QFR. The numbers of qn-HRPCs and ql-HRPCs increased with decreasing QFR. Among deferred vessels, those with 3 high-risk features exhibits a significantly higher risk of TVF compared with those with ≤2 high-risk features (12.0% vs 2.7%; HR: 4.54; 95% CI: 1.02-20.29).

CONCLUSIONS

Among the IVUS-guided deferred group, vessels with qn-HRPC and ql-HRPC with low QFR (≤0.90) exhibited a significantly higher risk for TVF compared with those with ≤2 features. Integrative assessment of angiography-derived fractional flow reserve and anatomical and morphological plaque characteristics is recommended to improve clinical outcomes in patients undergoing IVUS-guided deferred treatment.

Assessment of the functional severity of coronary lesions from optical coherence tomography based on ensembled learning

BACKGROUND

Atherosclerosis is one of the most frequent cardiovascular diseases. The dilemma faced by physicians is whether to treat or postpone the revascularization of lesions that fall within the intermediate range given by an invasive fractional flow reserve (FFR) measurement. The paper presents a monocentric study for lesions significance assessment that can potentially cause ischemia on the large coronary arteries.

METHODS

A new dataset is acquired, comprising the optical coherence tomography (OCT) images, clinical parameters, echocardiography and FFR measurements collected from 80 patients with 102 lesions, with stable multivessel coronary artery disease. Having the ground truth given by the invasive FFR measurement, the dataset is challenging because almost 40% of the lesions are in the gray zone, having an FFR value between 0.75 and 0.85. Twenty-six features are extracted from OCT images, clinical characteristics, and echocardiography and the most relevant are identified by examining the models' accuracy. An ensembled learning is performed for solving the binary classification problem of lesion significance considering the leave-one-out cross-validation approach.

RESULTS

Ensemble models are designed from the multi-features voting from 5 features models by prediction aggregation with a maximum accuracy of 81.37% and a maximum area under the curve score (AUC) of 0.856.

CONCLUSIONS

The proposed explainable supervised learning-based lesion classification is a new method that can be improved by training with a larger multicenter dataset for further designing a tool for guiding the decision making of the clinician for the cases outside the gray zone and for the other situation extra clinical information about the lesion is needed.