Fractional flow reserve calculation optimized by myocardial computed tomography perfusion information

Area of Science:

• Cardiovascular Imaging
• Medical Diagnostics
• Computational Fluid Dynamics

Background:

• Current computed tomography angiography-derived fractional flow reserve (CT-FFR) methods have limitations in diagnosing coronary heart disease.
• There is a need for improved accuracy in CT-FFR for better patient outcomes.

Purpose of the Study:

• To enhance the diagnostic accuracy of CT-FFR for coronary heart disease.
• To improve the consistency between CT-FFR and invasive fractional flow reserve (FFR) measurements.

Main Methods:

• Employed a computed fluid dynamics (CFD) boundary condition optimization method to calculate CT-FFR.
• Introduced two enhancement approaches: (A) inlet flow optimization using myocardial blood flow (MBF) and (B) inlet & outlet flow optimization incorporating coronary artery branch analysis.
• Validated methods against 100 invasive FFR measurements from 47 patients.

Main Results:

• Method A (inlet flow optimization) improved accuracy to 93% and specificity to 93.8%.
• Method B (inlet & outlet flow optimization) further increased accuracy to 94% and sensitivity to 100%.
• Both methods demonstrated improved diagnostic performance compared to the traditional CFD method without CTP images.

Conclusions:

• CFD calculations guided by MBF from stress CTP imaging significantly enhance CT-FFR accuracy.
• The optimized CT-FFR methods improve consistency with invasive FFR measurements, offering a more reliable non-invasive diagnostic tool.