Dataset Information

Impact of physiologically diffuse versus focal pattern of coronary disease on quantitative flow reserve diagnostic accuracy.

ABSTRACT:

Background

Fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) disagree in about 20% of intermediate coronary lesions. As the physiological pattern of coronary artery disease has a significant influence on FFR-iFR discordance, we sought to assess it may impact on the diagnostic accuracy of quantitative flow reserve (QFR).

Methods

One hundred and ninety-four patients with 224 intermediate coronary lesions were investigated with iFR, FFR, and QFR. The physiological pattern of disease was assessed with iFR Scout pullback and QFR virtual pullback in all the cases.

Results

A predominantly physiologically focal pattern was observed in 81 (36.2%) lesions, whereas a predominantly physiologically diffuse was observed in 143 (63.8%) cases. QFR demonstrated a significant correlation (r = 0.581, p < 0.001) and a substantial agreement with iFR, both in diffuse (AUC = 0.798) and in focal (AUC = 0.812) pattern of disease. Discordance between QFR and iFR was observed in 51 (22.8%) lesions, consisting of iFR+/QFR- (64.7%) and iFR-/QFR+ (35.3%). Notably, the physiological pattern of disease was the only variable significantly associated with iFR/QFR discordance. QFR virtual pullback demonstrated an excellent agreement (83.9%) with iFR Scout pullback in classifying the physiological pattern of disease.

Conclusions

QFR has a good diagnostic accuracy in assessing myocardial ischemia independently of the pattern of coronary disease. However, the physiological pattern of disease has an influence on the QFR/iFR discordance, which occurs in ~20% of the cases. The QFR virtual pullback correctly defined the physiological pattern of disease in the majority of the cases using the iFR pullback as reference.

SUBMITTER: Scarsini R

PROVIDER: S-EPMC9544909 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Impact of physiologically diffuse versus focal pattern of coronary disease on quantitative flow reserve diagnostic accuracy.

Scarsini Roberto R Fezzi Simone S Pesarini Gabriele G Del Sole Paolo Alberto PA Venturi Gabriele G Mammone Concetta C Marcoli Michele M Gambaro Alessia A Tavella Domenico D Pighi Michele M Ribichini Flavio F

Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions 20211110 3

<h4>Background</h4>Fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) disagree in about 20% of intermediate coronary lesions. As the physiological pattern of coronary artery disease has a significant influence on FFR-iFR discordance, we sought to assess it may impact on the diagnostic accuracy of quantitative flow reserve (QFR).<h4>Methods</h4>One hundred and ninety-four patients with 224 intermediate coronary lesions were investigated with iFR, FFR, and QFR. The physiological ...[more]

PMID: 34761492

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Project description:Purpose To compare the diagnostic accuracy of different computed tomographic (CT) fractional flow reserve (FFR) algorithms for vessels with intermediate stenosis. Materials and Methods This cross-sectional HIPAA-compliant and human research committee-approved study applied a four-step CT FFR algorithm in 61 patients (mean age, 69 years ± 10; age range, 29-89 years) with a lesion of intermediate-diameter stenosis (25%-69%) at CT angiography who underwent FFR measurement within 90 days. The per-lesion diagnostic performance of CT FFR was tested for three different approaches to estimate blood flow distribution for CT FFR calculation. The first two, the Murray law and the Huo-Kassab rule, used coronary anatomy; the third used contrast material opacification gradients. CT FFR algorithms and CT angiography percentage diameter stenosis (DS) measurements were compared by using the area under the receiver operating characteristic curve (AUC) to detect FFRs of 0.8 or lower. Results Twenty-five lesions (41%) had FFRs of 0.8 or lower. The AUC of CT FFR determination by using contrast material gradients (AUC = 0.953) was significantly higher than that of the Huo-Kassab (AUC = 0.882, P = .043) and Murray law models (AUC = 0.871, P = .033). All three AUCs were higher than that for 50% or greater DS at CT angiography (AUC = 0.596, P < .001). Correlation of CT FFR with FFR was highest for gradients (Spearman ρ = 0.80), followed by the Huo-Kassab rule (ρ = 0.68) and Murray law (ρ = 0.67) models. All CT FFR algorithms had small biases, ranging from -0.015 (Murray) to -0.049 (Huo-Kassab). Limits of agreement were narrowest for gradients (-0.182, 0.147), followed by the Huo-Kassab rule (-0.246, 0.149) and the Murray law (-0.285, 0.256) models. Conclusion Clinicians can perform CT FFR by using a four-step approach on site to accurately detect hemodynamically significant intermediate-stenosis lesions. Estimating blood flow distribution by using coronary contrast opacification variations may improve CT FFR accuracy. © RSNA, 2017 Online supplemental material is available for this article.

Project description:Background Quantitative flow ratio ( QFR ) has a high diagnostic accuracy in assessing functional stenoses relevance, as judged by fractional flow reserve ( FFR ). However, its diagnostic performance has not been thoroughly evaluated using instantaneous wave-free ratio ( iFR ) or coronary flow reserve as the reference standard. This study sought to evaluate the diagnostic performance of QFR using other reference standards beyond FFR . Methods and Results We analyzed 182 patients (253 vessels) with stable ischemic heart disease and 82 patients (105 nonculprit vessels) with acute myocardial infarction in whom coronary stenoses were assessed with FFR , iFR, and coronary flow reserve. Contrast QFR analysis of interrogated vessels was performed in blinded fashion by a core laboratory, and its diagnostic performance was evaluated with respect to the other invasive physiological indices. Mean percentage diameter stenosis, FFR , iFR , coronary flow reserve, and QFR were 53.1±19.0%, 0.80±0.13, 0.88±0.12, 3.14±1.30, and 0.81±0.14, respectively. QFR showed higher correlation ( r=0.863 with FFR versus 0.740 with iFR , P<0.001), diagnostic accuracy (90.8% versus 81.3%, P<0.001), and discriminant function (area under the curve=0.953 versus 0.880, P<0.001) when FFR was used as a reference standard than when iFR was used as the reference standard. However, when coronary flow reserve was used as an independent reference standard, FFR , iFR , and QFR showed modest discriminant function (area under the curve=0.682, 0.765, and 0.677, respectively) and there were no significant differences in diagnostic accuracy among FFR , iFR , and QFR (65.4%, 70.6%, and 64.9%; all P values in pairwise comparisons >0.05, overall comparison P=0.061). Conclusions QFR has a high correlation and agreement with respect to both FFR and iFR , although it is better when FFR is used as the comparator. As a pressure-derived index not depending on wire or adenosine, QFR might be a promising tool for improving the adoption rate of physiology-based revascularization in clinical practice.

Dataset Information

Impact of physiologically diffuse versus focal pattern of coronary disease on quantitative flow reserve diagnostic accuracy.

Background

Methods

Results

Conclusions

Publications

Impact of physiologically diffuse versus focal pattern of coronary disease on quantitative flow reserve diagnostic accuracy.

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