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Implementation of a national AI technology program on cardiovascular outcomes and the health system

Timothy A Fairbairn1,2, Liam Mullen3, Edward Nicol4,5

  • 1Liverpool Centre for Cardiovascular Science, Liverpool Heart and Chest Hospital, Liverpool, UK. tfair@liverpool.ac.uk.

Nature Medicine
|April 4, 2025
PubMed

Insights

Artificial intelligence (AI) in computed tomography (CT)-derived fractional flow reserve (FFR-CT) safely reduced cardiac tests for patients with chest pain. This AI tool improved decision-making without impacting mortality, benefiting patients and healthcare systems.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Artificial Intelligence in Healthcare

Background:

  • Coronary artery disease (CAD) is a leading global cause of mortality and morbidity.
  • Coronary computed tomographic angiography (CCTA) is a primary diagnostic tool for symptomatic CAD.
  • Current diagnostic pathways risk increased downstream cardiac testing and associated costs.

Purpose of the Study:

  • To evaluate the impact of an artificial intelligence (AI) diagnostic tool, computed tomography (CT)-derived fractional flow reserve (FFR-CT), on cardiovascular outcomes.
  • To assess the safety and efficacy of FFR-CT in improving physician decision-making and reducing unnecessary cardiac procedures.
  • To analyze the effect of FFR-CT implementation on patient pathways and healthcare system resource utilization.

Main Methods:

  • An observational cohort study included patients investigated with CCTA during a national AI implementation program across 27 hospitals.
  • Data encompassed 90,553 patients who underwent CCTA and 7,863 who received FFR-CT analysis.
  • Cardiovascular outcomes, including all-cause mortality, cardiovascular mortality, invasive coronary angiograms, and noninvasive cardiac tests, were compared between groups.

Main Results:

  • FFR-CT demonstrated safety, with no significant difference in all-cause mortality (3.2% vs 2.9%) or cardiovascular mortality (1.3% vs 1.1%) compared to CCTA alone.
  • Implementation of FFR-CT led to a significant reduction in invasive coronary angiograms (16% vs 14.9%) and noninvasive cardiac tests (189/1,000 vs 167/1,000 patients).
  • The AI diagnostic tool proved beneficial, streamlining patient care pathways and reducing healthcare system burden.

Conclusions:

  • The integration of AI-driven FFR-CT into clinical practice is safe and effective for investigating patients with suspected CAD.
  • FFR-CT enhances diagnostic accuracy, leading to a significant decrease in unnecessary cardiac interventions and tests.
  • This AI intervention offers substantial benefits to both patient management and healthcare economics.

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