One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve
Condition: Coronary Artery Disease
MeSH terms: Coronary Artery Disease
Study type: Interventional

Summary: 
      This study evaluates the diagnostic efficiency of an automated method of noninvasive
      assessment of the fractional reserve of coronary blood flow.

      Fractional flow reserve is estimated with a one-dimensional mathematical model constructed by
      means of an automated algorithm. Noninvasive method values are thereafter compared with
      invasive method values.
    

Detailed description: 
      Noninvasive assessment of Fractional Flow Reserve is almost never applied in the Russian
      Federation due to the relative novelty and study insufficiency, lack of the appropriate
      resource base, specific necessary software and trained qualified personnel.

      In 2015, scientists from the Institute of Numerical Mathematics RAS in collaboration with
      specialists of the I.M. Sechenov First Moscow State Medical University developed a
      noninvasive method of fractional flow reserve assessment based on a one-dimensional
      mathematical model. A model is constructed based on images derived from the coronary computed
      tomography angiography performed by standard protocol; the method is fully automated.

      The aim of our study is to evaluate the diagnostic efficiency of this technique in clinical
      practice.

      This is a pilot study; we are planning to enroll 30 patients: 13 of them underwent 64-slice
      computed tomography and are included retrospectively; 17 will be included prospectively, with
      a 640-slice CT scan. Specialists from the Laboratory of Mathematical Modeling will process CT
      images and evaluate noninvasive FFR. Ischemia is confirmed if FFR < 0.80 and disproved if FFR
      ≥ 0.80. After that, the prospective group of patients will be hospitalized for invasive FFR
      assessment as a reference standard; if ischemia is proved, patients will undergo stent
      implantation. In the retrospective group, patients already have invasive FFR values
      estimated.

      Statistical analysis will be performed using R programming language packages
      (cran-r.project.com). Continuous variables will be presented as mean values ± standard
      deviations, order variables will be presented as medians with interquartile ranges in
      parentheses. We are going to use the D'Agostino-Pearson omnibus test for the assessment of
      normality of distribution and construct a Q-Q Plot. We will compare these two methods with
      the Bland-Altman analysis and ROC-analysis and will assess the degree of correlation with the
      Pearson's chi-squared.

      The study should result in determining the sensitivity, specificity, positive and negative
      predictive values of the method.

      After the active phase of the research is done, we are planning to proceed observation on the
      prospective group of patients to verify the endpoints.
    

Intervention name(s): FFR
Intervention type(s): Device
Intervention description(s): Fractional flow reserve measured during cardiac catheterization
Intervention model: Single Group Assignment
Masking: None (Open Label)
Primary purpose: Diagnostic
Keywords: noninvasive assessment of the fractional flow reserve; coronary computed tomography angiography