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Artificial intelligence-powered software outperforms interventional cardiologists in assessment of IVUS-based stent

Pablo M Rubio1, Hector M Garcia-Garcia1, Jason Galo1

  • 1Interventional Cardiology, MedStar Washington Hospital Center, Washington, DC, USA.

Cardiovascular Revascularization Medicine : Including Molecular Interventions
|July 31, 2025
PubMed
Summary

Artificial intelligence (AI) software AVVIGO™+ identified suboptimal stent expansion and geographic miss more effectively than interventional cardiologists during intravascular ultrasound (IVUS) analysis. This AI tool significantly reduced analysis time, offering a more efficient approach to percutaneous coronary intervention (PCI).

Keywords:
Artificial intelligenceCoronary interventionIntravascular ultrasoundPlaque burdenStent expansion

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Area of Science:

  • Cardiovascular Interventions
  • Medical Imaging Analysis
  • Artificial Intelligence in Medicine

Background:

  • Optimal stent deployment via intravascular ultrasound (IVUS) improves percutaneous coronary intervention (PCI) outcomes.
  • IVUS analysis is underutilized due to time constraints and operator dependency.
  • AI software AVVIGO™+ automates lesion assessment but requires validation for stent evaluation.

Purpose of the Study:

  • To compare the AI software AVVIGO™+ against interventional cardiologists (ICs) for evaluating IVUS-based stent expansion and geographic miss.
  • To assess AVVIGO™+'s accuracy in identifying Minimum Stent Area (MSA) and plaque burden (PB) at stent edges.
  • To evaluate the time efficiency of AI-driven analysis versus traditional IC assessment.

Main Methods:

  • Retrospective analysis of 60 patients (47,997 IVUS frames) undergoing IVUS-guided PCI.
  • Independent analysis of Minimum Stent Area (MSA), stent expansion index, and plaque burden (PB) by ICs and AVVIGO™+.
  • Comparison of concordance, differences, and analysis time between the two assessment methods.

Main Results:

  • AVVIGO™+ detected significantly lower stent expansion (70.3%) compared to ICs (91.2%), identifying more suboptimal cases.
  • AI analysis was substantially faster, reducing evaluation time by 59.7% (0.76 min vs. 1.89 min).
  • AVVIGO™+ reported higher plaque burden at stent edges, identifying more instances of geographic miss than ICs.

Conclusions:

  • AVVIGO™+ demonstrated superior detection of suboptimal stent expansion and geographic miss compared to interventional cardiologists.
  • The AI software significantly decreased analysis time, indicating enhanced efficiency in IVUS-based stent assessment.
  • AI-powered platforms like AVVIGO™+ show potential for improving reliability and consistency in IVUS-guided PCI optimization.