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Non-invasive physiological assessment of coronary artery obstruction on coronary computed tomography angiography

Leonie M Becker1,2, Joyce Peper3, Sophie H van Nes3

  • 1Department of Cardiology, St. Antonius Hospital, Nieuwegein, The Netherlands. l.becker@antoniusziekenhuis.nl.

Netherlands Heart Journal : Monthly Journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation
|October 7, 2024
PubMed

Insights

Computed tomography-derived fractional flow reserve (CT-FFR) improves coronary computed tomography angiography (CCTA) specificity for stable coronary artery disease (CAD). CT-FFR reduces unnecessary invasive procedures, costs, and complications without impacting cardiovascular events.

Area of Science:

  • Cardiovascular imaging
  • Medical diagnostics
  • Computational physiology

Background:

  • Coronary computed tomography angiography (CCTA) has limitations in specificity for stable coronary artery disease (CAD).
  • Invasive coronary angiography (ICA) is the gold standard but carries risks and costs.
  • There is a need for non-invasive methods to accurately assess the functional significance of coronary stenoses.

Purpose of the Study:

  • To review the practical application, interpretation, and impact of CT-derived fractional flow reserve (CT-FFR) on patient care.
  • To discuss how CT-FFR integrates into CCTA for comprehensive coronary assessment and prognosis.
  • To highlight the role of CT-FFR in reducing unnecessary invasive diagnostic testing.

Main Methods:

  • Review of current literature and clinical applications of CT-FFR.
  • Discussion of CT-FFR algorithms, accuracy, and generalizability.
  • Exploration of advancements in CCTA quality and artificial intelligence (AI) impacting CT-FFR.

Main Results:

  • CT-FFR enhances CCTA specificity while maintaining high sensitivity in stable CAD.
  • CT-FFR significantly reduces negative ICA procedures, associated costs, and complications.
  • No increase in cardiovascular events observed with CT-FFR guided management.

Conclusions:

  • CT-FFR acts as an effective gatekeeper for ICA, improving diagnostic yield.
  • Future advancements in CT-FFR algorithms and AI promise enhanced accuracy and broader clinical utility.
  • Selective adoption of objective CT-FFR techniques maximizes CCTA's diagnostic value in CAD management.

Keywords:
Artificial intelligenceCT-derived fractional flow reserveComputed tomography angiographyCoronary artery diseaseMyocardial ischaemia

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