OCT-based Machine Learning FFR for Predicting Post-PCI FFR

NCT06341361 | Not Yet Recruiting

• 1 other identifier: OCT-FFR
• Study Type: observational
• Target: 82
• Locations: 0 countries
• Sites: N/A

Brief Summary

This study aims to 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.

Conditions

Tomography, Optical Coherence; Fractional Flow Reserve, Myocardial

Outcome Measures

Primary Outcomes (1)

• Correlation of OCT-based machine learning FFR compared to wire-based FFR

  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 Outcomes (2)

• Diagnostic performance of OCT-based machine learning FFR compared to wire-based FFR

  4 weeks

• Diagnostic performance of OCT-based machine learning FFR according to the coronary artery (LAD, LCx or RCA) compared to wire-based FFR

  4 weeks

Interventions

OCT-based machine learning FFR DIAGNOSTIC_TEST

OCT-based machine learning FFR and wire-based FFR

Eligibility Criteria

• Age: 19 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Among patients who underwent PCI for ischemic heart disease, those who underwent both OCT examination and pressure wire-based FFR after coronary artery stenting.

You may qualify if:

• Patients who underwent stent implantation for ischemic heart disease
• Patients who underwent both OCT examination and FFR using a pressure wire after PCI

You may not qualify if:

• 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

Sponsors & Collaborators

• Yonsei University: lead
• Gangnam Severance Hospital: collaborator
• Severance Hospital: collaborator

Study Officials

• Jung-Sun Kim, MD, PhD

  Severance Cardiovascular Hospital, Yonsei University College of Medicine

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Oh-Hyun Lee, MD

CONTACT

+82-31-5189-8786; Decenthyun@yuhs.ac

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: March 26, 2024
• First Posted: April 2, 2024
• Study Start: April 15, 2024
• Primary Completion: April 30, 2024
• Study Completion: October 15, 2025
• Last Updated: April 2, 2024

Record last verified: 2024-03

Data Sharing

• IPD Sharing: Will not share