<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03797118</url>
  </required_header>
  <id_info>
    <org_study_id>17-51-53160</org_study_id>
    <nct_id>NCT03797118</nct_id>
  </id_info>
  <brief_title>One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve</brief_title>
  <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.</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>I.M. Sechenov First Moscow State Medical University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>I.M. Sechenov First Moscow State Medical University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This study evaluates the diagnostic efficiency of an automated method of noninvasive&#xD;
      assessment of the fractional reserve of coronary blood flow.&#xD;
&#xD;
      Fractional flow reserve is estimated with a one-dimensional mathematical model constructed by&#xD;
      means of an automated algorithm. Noninvasive method values are thereafter compared with&#xD;
      invasive method values.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Noninvasive assessment of Fractional Flow Reserve is almost never applied in the Russian&#xD;
      Federation due to the relative novelty and study insufficiency, lack of the appropriate&#xD;
      resource base, specific necessary software and trained qualified personnel.&#xD;
&#xD;
      In 2015, scientists from the Institute of Numerical Mathematics RAS in collaboration with&#xD;
      specialists of the I.M. Sechenov First Moscow State Medical University developed a&#xD;
      noninvasive method of fractional flow reserve assessment based on a one-dimensional&#xD;
      mathematical model. A model is constructed based on images derived from the coronary computed&#xD;
      tomography angiography performed by standard protocol; the method is fully automated.&#xD;
&#xD;
      The aim of our study is to evaluate the diagnostic efficiency of this technique in clinical&#xD;
      practice.&#xD;
&#xD;
      This is a pilot study; we are planning to enroll 30 patients: 13 of them underwent 64-slice&#xD;
      computed tomography and are included retrospectively; 17 will be included prospectively, with&#xD;
      a 640-slice CT scan. Specialists from the Laboratory of Mathematical Modeling will process CT&#xD;
      images and evaluate noninvasive FFR. Ischemia is confirmed if FFR &lt; 0.80 and disproved if FFR&#xD;
      ≥ 0.80. After that, the prospective group of patients will be hospitalized for invasive FFR&#xD;
      assessment as a reference standard; if ischemia is proved, patients will undergo stent&#xD;
      implantation. In the retrospective group, patients already have invasive FFR values&#xD;
      estimated.&#xD;
&#xD;
      Statistical analysis will be performed using R programming language packages&#xD;
      (cran-r.project.com). Continuous variables will be presented as mean values ± standard&#xD;
      deviations, order variables will be presented as medians with interquartile ranges in&#xD;
      parentheses. We are going to use the D'Agostino-Pearson omnibus test for the assessment of&#xD;
      normality of distribution and construct a Q-Q Plot. We will compare these two methods with&#xD;
      the Bland-Altman analysis and ROC-analysis and will assess the degree of correlation with the&#xD;
      Pearson's chi-squared.&#xD;
&#xD;
      The study should result in determining the sensitivity, specificity, positive and negative&#xD;
      predictive values of the method.&#xD;
&#xD;
      After the active phase of the research is done, we are planning to proceed observation on the&#xD;
      prospective group of patients to verify the endpoints.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">April 5, 2017</start_date>
  <completion_date type="Actual">July 5, 2019</completion_date>
  <primary_completion_date type="Actual">June 5, 2019</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Diagnostic Accuracy of FFRct</measure>
    <time_frame>through study completion, an average of 8 months</time_frame>
    <description>Sensitivity, 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.</description>
  </primary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">31</enrollment>
  <condition>Coronary Artery Disease</condition>
  <arm_group>
    <arm_group_label>FFRct</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Patients will receive cCTA, ICA, FFRct, and FFRinv per protocol.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>FFR</intervention_name>
    <description>Fractional flow reserve measured during cardiac catheterization</description>
    <arm_group_label>FFRct</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Patients providing written informed consent&#xD;
&#xD;
          2. Scheduled to undergo clinically-indicated non-emergent invasive coronary angiography&#xD;
             (ICA)&#xD;
&#xD;
          3. Has undergone &gt;640 multidetector CCTA within 60 days prior to ICA&#xD;
&#xD;
          4. No cardiac interventional therapy between the CCTA and ICA&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Prior coronary artery bypass graft (CABG) surgery&#xD;
&#xD;
          2. Prior percutaneous coronary intervention (PCI) for which suspected coronary artery&#xD;
             lesion(s) are within a stented coronary vessel&#xD;
&#xD;
          3. Contraindication to adenosine, including 2nd or 3rd-degree heart block; sick sinus&#xD;
             syndrome; long QT syndrome; severe hypotension, severe asthma, severe COPD or&#xD;
             bronchodilator-dependent COPD&#xD;
&#xD;
          4. Suspicion of acute coronary syndrome (acute myocardial infarction and unstable angina)&#xD;
&#xD;
          5. Recent prior myocardial infarction within 40 days of ICA&#xD;
&#xD;
          6. Known complex congenital heart disease&#xD;
&#xD;
          7. Prior pacemaker or internal defibrillator lead implantation&#xD;
&#xD;
          8. Prosthetic heart valve&#xD;
&#xD;
          9. Significant arrhythmia or tachycardia&#xD;
&#xD;
         10. Impaired chronic renal function (serum creatinine &gt;1.5 mg/dl&#xD;
&#xD;
         11. Patients with known anaphylactic allergy to iodinated contrast&#xD;
&#xD;
         12. Pregnancy or unknown pregnancy status&#xD;
&#xD;
         13. Body mass index &gt;35&#xD;
&#xD;
         14. Patient requires an emergent procedure&#xD;
&#xD;
         15. Evidence of ongoing or active clinical instability, including acute chest pain (sudden&#xD;
             onset), cardiogenic shock, unstable blood pressure with systolic blood pressure &lt;90&#xD;
             mmHg, and severe congestive heart failure (NYHA III or IV) or acute pulmonary edema&#xD;
&#xD;
         16. Any active, serious, life-threatening disease with a life expectancy of less than 2&#xD;
             months&#xD;
&#xD;
         17. Inability to comply with study procedures&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>85 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Daria Gognieva, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>I.M. Sechenov First Moscow State Medical University (Sechenov University)</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Philipp Kopylov, Professor</last_name>
    <role>Study Director</role>
    <affiliation>I.M. Sechenov First Moscow State Medical University (Sechenov University)</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Daria Gognieva</name>
      <address>
        <city>Moscow</city>
        <zip>127540</zip>
        <country>Russian Federation</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Russian Federation</country>
  </location_countries>
  <link>
    <url>https://www.ncbi.nlm.nih.gov/pubmed?term=Am+J+Case+Rep+%5BJour%5D+AND+One-Dimensional+Mathematical+Model-Based+Automated+Assessment+of+Fractional+Flow+Reserve+in+a+Patient+with+Silent+Myocardial+Ischemia&amp;TransSchema=title&amp;cmd=detailssearch</url>
    <description>Am J Case Rep. 2018 Jun 20;19:724-728. doi: 10.12659/AJCR.908449.</description>
  </link>
  <reference>
    <citation>Gognieva D, Gamilov T, Pryamonosov R, Betelin V, Ternovoy SK, Serova NS, Abugov S, Shchekochikhin D, Mitina Y, El-Manaa H, Kopylov P. One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve in a Patient with Silent Myocardial Ischemia. Am J Case Rep. 2018 Jun 20;19:724-728. doi: 10.12659/AJCR.908449.</citation>
    <PMID>29921835</PMID>
  </reference>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>December 22, 2018</study_first_submitted>
  <study_first_submitted_qc>January 6, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">January 8, 2019</study_first_posted>
  <last_update_submitted>May 14, 2020</last_update_submitted>
  <last_update_submitted_qc>May 14, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">May 18, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>I.M. Sechenov First Moscow State Medical University</investigator_affiliation>
    <investigator_full_name>Daria Gognieva</investigator_full_name>
    <investigator_title>Principal Investigator</investigator_title>
  </responsible_party>
  <keyword>noninvasive assessment of the fractional flow reserve</keyword>
  <keyword>coronary computed tomography angiography</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Coronary Artery Disease</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
    <ipd_description>Data disclosure is not permitted by the local ethics committee. For more information about the study, you need to contact the principal investigator.</ipd_description>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03797118
org study id: 17-51-53160
nct id: NCT03797118
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
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.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Diagnostic
masking: None (Open Label)
measure: Diagnostic Accuracy of FFRct
time frame: through study completion, an average of 8 months
description: Sensitivity, 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.
arm group label: FFRct
arm group type: Experimental
description: Patients will receive cCTA, ICA, FFRct, and FFRinv per protocol.
intervention type: Device
intervention name: FFR
description: Fractional flow reserve measured during cardiac catheterization
arm group label: FFRct
criteria: 
gender: All
minimum age: 18 Years
maximum age: 85 Years
healthy volunteers: No
last name: Daria Gognieva, MD
role: Principal Investigator
affiliation: I.M. Sechenov First Moscow State Medical University (Sechenov University)
last name: Philipp Kopylov, Professor
role: Study Director
affiliation: I.M. Sechenov First Moscow State Medical University (Sechenov University)
facility: 
country: Russian Federation
url: https://www.ncbi.nlm.nih.gov/pubmed?term=Am+J+Case+Rep+%5BJour%5D+AND+One-Dimensional+Mathematical+Model-Based+Automated+Assessment+of+Fractional+Flow+Reserve+in+a+Patient+with+Silent+Myocardial+Ischemia&TransSchema=title&cmd=detailssearch
description: Am J Case Rep. 2018 Jun 20;19:724-728. doi: 10.12659/AJCR.908449.
citation: Gognieva D, Gamilov T, Pryamonosov R, Betelin V, Ternovoy SK, Serova NS, Abugov S, Shchekochikhin D, Mitina Y, El-Manaa H, Kopylov P. One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve in a Patient with Silent Myocardial Ischemia. Am J Case Rep. 2018 Jun 20;19:724-728. doi: 10.12659/AJCR.908449.
PMID: 29921835
responsible party type: Principal Investigator
investigator affiliation: I.M. Sechenov First Moscow State Medical University
investigator full name: Daria Gognieva
investigator title: Principal Investigator
mesh term: Coronary Artery Disease
sharing ipd: No
ipd description: Data disclosure is not permitted by the local ethics committee. For more information about the study, you need to contact the principal investigator.