OCT-based Machine Learning FFR for Predicting Post-PCI FFR
Optical Coherence Tomography-based Machine Learning for Predicting Fractional Flow Reserve After Coronary Artery Stenting
Study Overview
Status
Intervention / Treatment
Detailed Description
FFR and OCT exam are used for different purposes during percutaneous coronary intervention (PCI). The FFR is a decision-making tool to determine if additional procedures are necessary, while the OCT exam is used to optimize the stent procedure. The use of both tests provides additional information to help perform a excellent procedure, but it is more expensive and time-consuming.
Therefore, an OCT-derived machine learning FFR test may be helpful. Previous studies have demonstrated that OCT-based machine learning FFR before the procedure has shown good diagnostic performance in predicting FFR, irrespective of the coronary territory.
Despite the rapid development of technologies and tools for PCI, a significant number of patients experienced adverse events, such as recurrence of angina and silent ischemia despite angiographically successful PCI. Suboptimal PCI is a well-known independent prognostic factor for major cardiovascular accidents. Therefore, measuring post-PCI FFR immediately after stent implantation is crucial to optimize the procedure outcome and improve the patient's prognosis. Although the importance of measuring post-PCI FFR is gradually emerging, there is currently no model for OCT-based machine learning FFR that predicts FFR after stent insertion. In patients who underwent percutaneous coronary intervention using stents for ischemic heart disease, we will compare the diagnostic accuracy of the fractional flow reserve (FFR) model derived by machine learning based on optical coherence tomography (OCT) exam after coronary artery stent implantation with the wire-based FFR.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Contact
- Name: Oh-Hyun Lee, MD
- Phone Number: +82-31-5189-8786
- Email: Decenthyun@yuhs.ac
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients who underwent stent implantation for ischemic heart disease
- Patients who underwent both OCT examination and FFR using a pressure wire after PCI
Exclusion Criteria:
- Poor OCT imaging quality
- Patients with severe left ventricular dysfunction (<30%)
- Patients with severe valvular heart disease
- Patients with a life expectancy of less than 1 year
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Correlation of OCT-based machine learning FFR compared to wire-based FFR
Time Frame: 4 weeks
|
Determining the diagnostic accuracy of CT-FFR values obtained by the new method compared with invasive coronary angiography with fractional flow reserve
|
4 weeks
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Diagnostic performance of OCT-based machine learning FFR compared to wire-based FFR
Time Frame: 4 weeks
|
Accuracy, sensitivity, specificity, positive predictive value, negative predictive value
|
4 weeks
|
|
Diagnostic performance of OCT-based machine learning FFR according to the coronary artery (LAD, LCx or RCA) compared to wire-based FFR
Time Frame: 4 weeks
|
Accuracy, sensitivity, specificity, positive predictive value, negative predictive value
|
4 weeks
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Jung-Sun Kim, MD, PhD, Severance Cardiovascular Hospital, Yonsei University College of Medicine
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
- OCT-FFR
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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