Ignite Creation Date:
2025-12-25 @ 5:00 AM
Ignite Modification Date:
2026-01-26 @ 6:40 PM
Study NCT ID:
NCT03797118
Status:
COMPLETED
Last Update Posted:
2020-05-18
First Post:
2018-12-22
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve
Sponsor:
I.M. Sechenov First Moscow State Medical University
Organization:
Study Overview
Official Title:
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
Status Verified Date:
2020-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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.
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.
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.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: