Novel motion correction algorithm improves diagnostic performance of CT fractional flow reserve

Area of Science:

• Cardiovascular imaging
• Medical physics

Background:

• Coronary artery disease (CAD) diagnosis relies on invasive methods.
• Non-invasive CT-FFR offers a promising alternative but is limited by image quality.
• Motion artifacts in CCTA can affect CT-FFR accuracy.

Purpose of the Study:

• To evaluate the diagnostic performance of CT-FFR derived from CCTA images processed with different motion correction algorithms.
• To compare the efficacy of standard (STD), first-generation (SSF1), and second-generation (SSF2) SnapShot Freeze algorithms.

Main Methods:

• Retrospective analysis of 151 patients with CCTA and invasive FFR.
• CCTA images reconstructed with iterative reconstruction and processed via SSF1 and SSF2.
• Comparison of CT-FFR accuracy against invasive FFR for identifying ischemic lesions.

Main Results:

• SSF2 significantly improved image quality scores compared to STD and SSF1 (p < 0.001).
• SSF2 demonstrated the best correlation (r=0.652) and consistency (mean difference=0.04) with invasive FFR.
• CT-FFR derived from SSF2 images showed superior diagnostic performance at both per-lesion and per-patient levels.

Conclusions:

• The SSF2 algorithm markedly enhances CCTA image quality.
• SSF2 improves the diagnostic performance of CT-FFR for stenosis severity assessment.
• This advanced algorithm holds potential for more accurate non-invasive evaluation of coronary artery disease.