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Rofo 2024; 196(12): 1253-1261
DOI: 10.1055/a-2271-0887
Heart

The value of AI-based analysis of fractional flow reserve of volume computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance

Article in several languages: English | deutsch
Hans-Jürgen Noblé
1   Department of Radiology, German Air Force Center of Aerospace Medicine, Cologne, Germany
,
Nadine Mühlbauer
1   Department of Radiology, German Air Force Center of Aerospace Medicine, Cologne, Germany
,
Josef Ehling
1   Department of Radiology, German Air Force Center of Aerospace Medicine, Cologne, Germany
,
Paul Martin Bansmann
2   Institute for Diagnostic and Interventional Radiology, Hospital Porz am Rhein, Cologne, Germany
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Abstract

Purpose The aim of our work was to demonstrate the importance of artificial intelligence-based analysis of fractional flow reserves of computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance in patients with unclear chest pain and suspected stable coronary heart disease with a low to medium pre-test probability.

Material and Methods The collective of our retrospective analysis includes 63 patients in whom coronary artery stenosis was detected by volume computed tomographic examination in “one beat, whole heart” mode in the period from March to October 2022. In these patients, the fractional flow reserve was also determined by computed tomography, which was modulated by the use of artificial intelligence.

Results The calculated values of the fractional flow reserve and the degrees of stenosis determined by computed tomography showed a moderate and significant negative correlation for all three coronary vascular territories (LAD/CX/RCA) (correlation coefficient rho = 0.54/0.54/0.6; p < 0.01 respectively). In just over a third (37.6 %) of all stenoses classified as high-grade by computed tomography, the assessment of hemodynamic relevance by calculating the fractional flow reserve deviated from the severity of the stenosis diagnosed by computed tomography, while the results in the peripheral areas “no stenosis/vascular occlusion” were 100 % consistent in each case.

Conclusion The present results of this work illustrate that the calculation of the fractional flow reserve based on artificial intelligence as a supplement to volume computed tomography of the heart can make a decisive contribution to further therapy planning by increasing the specificity of the purely morphological method by the physiological aspect.

Key Points 

  • Calculation of fractional flow reserve is a useful addition to computed tomography of the heart.

  • It provides possibility to dispense with unnecessary further diagnostics by increasing specificity.

  • The combination of both procedures leads to therapy optimization for patients.

Citation Format

  • Noblé H, Mühlbauer N, Ehling J et al. The value of AI-based analysis of fractional flow reserve of volume computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance. Fortschr Röntgenstr 2024; 196: 1253 – 1261

Keywords

hemodynamics/flow dynamics - angiocardiography - heart


Publication History

Received: 27 September 2023

Accepted: 13 February 2024

Article published online:
17 April 2024

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