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One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve

The First Experience With Using a One-dimensional Mathematical Model With Fully Automated Algorithm of Extraction of Patient-specific Geometry From CT Images for a Noninvasive Assessment of Fractional Flow Reserve.

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT03797118
Enrollment
31
Registered
2019-01-08
Start date
2017-04-05
Completion date
2019-07-05
Last updated
2020-05-18

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Coronary Artery Disease

Keywords

noninvasive assessment of the fractional flow reserve, coronary computed tomography angiography

Brief 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.

Interventions

DEVICEFFR

Fractional flow reserve measured during cardiac catheterization

Sponsors

I.M. Sechenov First Moscow State Medical University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No

Inclusion criteria

1. Patients providing written informed consent 2. Scheduled to undergo clinically-indicated non-emergent invasive coronary angiography (ICA) 3. Has undergone \>640 multidetector CCTA within 60 days prior to ICA 4. No cardiac interventional therapy between the CCTA and ICA

Exclusion criteria

1. Prior coronary artery bypass graft (CABG) surgery 2. Prior percutaneous coronary intervention (PCI) for which suspected coronary artery lesion(s) are within a stented coronary vessel 3. Contraindication to adenosine, including 2nd or 3rd-degree heart block; sick sinus syndrome; long QT syndrome; severe hypotension, severe asthma, severe COPD or bronchodilator-dependent COPD 4. Suspicion of acute coronary syndrome (acute myocardial infarction and unstable angina) 5. Recent prior myocardial infarction within 40 days of ICA 6. Known complex congenital heart disease 7. Prior pacemaker or internal defibrillator lead implantation 8. Prosthetic heart valve 9. Significant arrhythmia or tachycardia 10. Impaired chronic renal function (serum creatinine \>1.5 mg/dl 11. Patients with known anaphylactic allergy to iodinated contrast 12. Pregnancy or unknown pregnancy status 13. Body mass index \>35 14. Patient requires an emergent procedure 15. Evidence of ongoing or active clinical instability, including acute chest pain (sudden onset), cardiogenic shock, unstable blood pressure with systolic blood pressure \<90 mmHg, and severe congestive heart failure (NYHA III or IV) or acute pulmonary edema 16. Any active, serious, life-threatening disease with a life expectancy of less than 2 months 17. Inability to comply with study procedures

Design outcomes

Primary

MeasureTime frameDescription
Diagnostic Accuracy of FFRctthrough study completion, an average of 8 monthsSensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of FFRct at the vessel level using binary outcomes whith compared to FFR as the reference standard.

Countries

Russia

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026