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:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003324', 'term': 'Coronary Artery Disease'}], 'ancestors': [{'id': 'D003327', 'term': 'Coronary Disease'}, {'id': 'D017202', 'term': 'Myocardial Ischemia'}, {'id': 'D006331', 'term': 'Heart Diseases'}, {'id': 'D002318', 'term': 'Cardiovascular Diseases'}, {'id': 'D001161', 'term': 'Arteriosclerosis'}, {'id': 'D001157', 'term': 'Arterial Occlusive Diseases'}, {'id': 'D014652', 'term': 'Vascular Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 31}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2017-04-05', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-05', 'completionDateStruct': {'date': '2019-07-05', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-05-14', 'studyFirstSubmitDate': '2018-12-22', 'studyFirstSubmitQcDate': '2019-01-06', 'lastUpdatePostDateStruct': {'date': '2020-05-18', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2019-01-08', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2019-06-05', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Diagnostic Accuracy of FFRct', 'timeFrame': '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.'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['noninvasive assessment of the fractional flow reserve', 'coronary computed tomography angiography'], 'conditions': ['Coronary Artery Disease']}, 'referencesModule': {'references': [{'pmid': '29921835', 'type': 'BACKGROUND', '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.'}], 'seeAlsoLinks': [{'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', 'label': 'Am J Case Rep. 2018 Jun 20;19:724-728. doi: 10.12659/AJCR.908449.'}]}, 'descriptionModule': {'briefSummary': 'This study evaluates the diagnostic efficiency of an automated method of noninvasive assessment of the fractional reserve of coronary blood flow.\n\nFractional 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.', 'detailedDescription': "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.\n\nIn 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.\n\nThe aim of our study is to evaluate the diagnostic efficiency of this technique in clinical practice.\n\nThis 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.\n\nStatistical 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.\n\nThe study should result in determining the sensitivity, specificity, positive and negative predictive values of the method.\n\nAfter the active phase of the research is done, we are planning to proceed observation on the prospective group of patients to verify the endpoints."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '85 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n1. Patients providing written informed consent\n2. Scheduled to undergo clinically-indicated non-emergent invasive coronary angiography (ICA)\n3. Has undergone \\>640 multidetector CCTA within 60 days prior to ICA\n4. No cardiac interventional therapy between the CCTA and ICA\n\nExclusion Criteria:\n\n1. Prior coronary artery bypass graft (CABG) surgery\n2. Prior percutaneous coronary intervention (PCI) for which suspected coronary artery lesion(s) are within a stented coronary vessel\n3. 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\n4. Suspicion of acute coronary syndrome (acute myocardial infarction and unstable angina)\n5. Recent prior myocardial infarction within 40 days of ICA\n6. Known complex congenital heart disease\n7. Prior pacemaker or internal defibrillator lead implantation\n8. Prosthetic heart valve\n9. Significant arrhythmia or tachycardia\n10. Impaired chronic renal function (serum creatinine \\>1.5 mg/dl\n11. Patients with known anaphylactic allergy to iodinated contrast\n12. Pregnancy or unknown pregnancy status\n13. Body mass index \\>35\n14. Patient requires an emergent procedure\n15. 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\n16. Any active, serious, life-threatening disease with a life expectancy of less than 2 months\n17. Inability to comply with study procedures'}, 'identificationModule': {'nctId': 'NCT03797118', 'briefTitle': 'One-Dimensional Mathematical Model-Based Automated Assessment of Fractional Flow Reserve', 'organization': {'class': 'OTHER', 'fullName': 'I.M. Sechenov First Moscow State Medical University'}, 'officialTitle': '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.', 'orgStudyIdInfo': {'id': '17-51-53160'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'FFRct', 'description': 'Patients will receive cCTA, ICA, FFRct, and FFRinv per protocol.', 'interventionNames': ['Device: FFR']}], 'interventions': [{'name': 'FFR', 'type': 'DEVICE', 'description': 'Fractional flow reserve measured during cardiac catheterization', 'armGroupLabels': ['FFRct']}]}, 'contactsLocationsModule': {'locations': [{'zip': '127540', 'city': 'Moscow', 'country': 'Russia', 'facility': 'Daria Gognieva', 'geoPoint': {'lat': 55.75204, 'lon': 37.61781}}], 'overallOfficials': [{'name': 'Daria Gognieva, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'I.M. Sechenov First Moscow State Medical University (Sechenov University)'}, {'name': 'Philipp Kopylov, Professor', 'role': 'STUDY_DIRECTOR', 'affiliation': 'I.M. Sechenov First Moscow State Medical University (Sechenov University)'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'Data disclosure is not permitted by the local ethics committee. For more information about the study, you need to contact the principal investigator.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'I.M. Sechenov First Moscow State Medical University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Principal Investigator', 'investigatorFullName': 'Daria Gognieva', 'investigatorAffiliation': 'I.M. Sechenov First Moscow State Medical University'}}}}