J Korean Med Sci.  2023 Aug;38(32):e254. 10.3346/jkms.2023.38.e254.

Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis

• Kang SH
• Kim SH
• Kim SH
• Chun EJ
• Chung WY
• Yoon CH
• Park SD
• Nam CW
• Kwon KH
• Doh JH
• Byun YS
• Bae JW
• Youn TJ
• Chae IH

• KMID: 2545203
• DOI: http://doi.org/10.3346/jkms.2023.38.e254

Abstract

Background
Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease.
Methods
Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR ≤ 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B.
Results
Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63–0.80) for CCTA, 0.65 (95% CI, 0.56–0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70–0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55–0.71) for CCTA alone, 0.66 (0.58–0.74) for algorithm A, and 0.76 (0.68–0.82) for algorithm B.
Conclusion
This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

Keyword

Computed Tomography; Coronary CT Angiography; Fractional Flow Reserve; Coronary Artery Disease

Figure

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  Fig. 1 AUC of CT-FFR and CCTA. AUC of CT-FFR (red) and CCTA stenosis diameter (blue) for detecting hemodynamically significant lesion defined by invasive FFR ≤ 0.80. (A) Algorithm A, (B) Algorithm B.AUC = area under the receiver operating characteristic curve, CT-FFR = computed tomography-based fractional flow reserve, CCTA = coronary computed tomography angiography, FFR = fractional flow reserve.

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  Fig. 2 Bland-Altman plots. Bland-Altman plots for the difference between the observed invasive fractional flow reserve and the estimated computed tomography-based fractional flow reserve. (A) Algorithm A, (B) Algorithm B.

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  Fig. 3 A representative figure of (A) coronary CT angio, (B) invasive FFR, (C) and CT-FFR.CT-FFR = computed tomography-based fractional flow reserve, FFR = fractional flow reserve, CT = computed tomography.

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