Guiding Myocardial Revascularization by Algorithmic Interpretation of FFR Pullback Curves: A Proof of Concept Study

Jean-François Argacha, Jean Decamp, Bert Vandeloo, Danilo Babin, Stijn Lochy, Karen Van den Bussche, Quentin de Hemptinne, Panagiotis Xaplanteris, Julien Magne, Patrick Segers, Bernard Cosyns

Research output: Contribution to journalArticle

Abstract

Background: Coronary artery disease distribution along the vessel is a main determinant of FFR improvement after PCI. Identifying focal from diffuse disease from visual inspections of coronary angiogram (CA) and FFR pullback (FFR-PB) are operator-dependent. Computer science may standardize interpretations of such curves. Methods: A virtual stenting algorithm (VSA) was developed to perform an automated FFR-PB curve analysis. A survey analysis of the evaluations of 39 vessels with intermediate disease on CA and a distal FFR <0.8, rated by 5 interventional cardiologists, was performed. Vessel disease distribution and PCI strategy were successively rated based on CA and distal FFR (CA); CA and FFR-PB curve (CA/FFR-PB); and CA and VSA (CA/VSA). Inter-rater reliability was assessed using Fleiss kappa and an agreement analysis of CA/VSA rating with both algorithmic and human evaluation (operator) was performed. We hypothesize that VSA would increase rater agreement in interpretation of epicardial disease distribution and subsequent evaluation of PCI eligibility. Results: Inter-rater reliability in vessel disease assessment by CA, CA/FFR-PB, and CA/VSA were respectively, 0.32 (95% CI: 0.17-0.47), 0.38 (95% CI: 0.23-0.53), and 0.4 (95% CI: 0.25-0.55). The raters' overall agreement in vessel disease distribution and PCI eligibility was higher with the VSA than with the operator (respectively, 67 vs. 42%, and 80 vs. 70%, both p < 0.05). Compared to CA/FFR-PB, CA/VSA induced more reclassification toward a focal disease (92 vs. 56.2%, p < 0.01) with a trend toward more reclassification as eligible for PCI (70.6 vs. 33%, p = 0.06). Change in PCI strategy did not differ between CA/FFR-PB and CA/VSA (23.6 vs. 28.5%, p = 0.38). Conclusions: VSA is a new program to facilitate and standardize the FFR pullback curves analysis. When expert reviewers integrate VSA data, their assessments are less variable which might help to standardize PCI eligibility and strategy evaluations. Clinical Trial Registration: https://www.clinicaltrials.gov/ct2/show/NCT03824600.

Original languageEnglish
Article number623841
Number of pages12
JournalFrontiers in Cardiovascular Medicine
Volume8
DOIs
Publication statusPublished - 11 Mar 2021

Bibliographical note

Copyright © 2021 Argacha, Decamp, Vandeloo, Babin, Lochy, Van den Bussche, de Hemptinne, Xaplanteris, Magne, Segers and Cosyns.

Keywords

  • computer science
  • coronary artery disease
  • coronary physiology
  • fractional flow reserve
  • percutaneous coronary intervention
  • pullback
  • vessel disease distribution
  • virtual coronary stenting

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