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Ultrasound Based Assessment of Coronary Artery Flow and Coronary Flow Reserve Using the Pressure Overload Model in Mice
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Quantitative Flow Ratio Analysis by Paramedical Compared With Medical Users.

Farhang Aminfar, Benjamin Honton, Pierre Meyer

  • 1Department of Cardiology, Arnault Tzanck Institute, Saint Laurent du Var, France. julienadjedj@hotmail.com.

The Journal of Invasive Cardiology
|March 18, 2022
PubMed
Summary

Certified medical and paramedical users can accurately perform quantitative flow ratio (QFR) analysis, showing strong correlation with fractional flow reserve (FFR). This validates QFR as a reliable tool for assessing coronary artery disease, potentially reducing physician workload.

Keywords:
coronary artery diseasefunctional evaluationnon-physicianparamedicalpercutaneous coronary intervention

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Area of Science:

  • Cardiovascular medicine
  • Interventional cardiology
  • Medical imaging analysis

Background:

  • Quantitative flow ratio (QFR) enables the calculation of fractional flow reserve (FFR) using coronary angiograms.
  • QFR analysis requires certified users with specific training and skills.
  • The proficiency of both medical and paramedical personnel in performing QFR analysis is not well-established.

Purpose of the Study:

  • To validate if certified medical and paramedical users can perform quantitative flow ratio (QFR) analysis.
  • To compare QFR values derived by medical and paramedical users against conventional guidewire-based fractional flow reserve (FFR).

Main Methods:

  • A prospective, single-center study included 67 patients with stable coronary artery disease requiring physiological assessment.
  • QFR was performed and analyzed by one medical and two paramedical users, blinded to FFR results.
  • Core laboratory analysis compared QFR values with guidewire-based FFR measurements.

Main Results:

  • A strong correlation was observed between QFR analysis performed by paramedical users and medical users (Pearson's r=0.89).
  • Bland-Altman analysis indicated no significant bias between the two user groups (-0.0008).
  • Receiver-operator characteristic curves demonstrated high accuracy for both groups in predicting FFR values below 0.80 (AUC 0.964 for paramedical, 0.970 for medical).

Conclusions:

  • QFR analysis demonstrates a notable correlation when performed by certified paramedical and medical users, compared to FFR.
  • These findings suggest that certified paramedical professionals can conduct QFR analysis.
  • Implementing paramedical QFR analysis may reduce physician workload without compromising the quality of results in assessing coronary artery disease.