Subtraction fractional flow reserve with computed tomography and pericoronary fat attenuation index enhances the identification of revascularization needs in patients

Abstract

Background: Fractional flow reserve with computed tomography (FFR-CT) is influenced by calcified plaque artifacts, which can reduce its accuracy in predicting myocardial ischemia. Subtraction techniques can mitigate these artifacts, thereby enhancing diagnostic precision. However, the potential of subtraction FFR-CT and the pericoronary fat attenuation index (FAI) to improve the prediction of revascularization in patients with coronary artery disease (CAD) remains unclear. We aimed to evaluate the diagnostic performance of FFR-CT and pericoronary FAI in identifying the need for revascularization in patients with CAD.

Methods: We retrospectively analyzed coronary computed tomography angiography (CCTA) data from 76 patients with CAD (142 branches) using both conventional and subtraction CCTA images. The diagnostic performance of FFR-CT and FAI in identifying revascularization needs was assessed using receiver operating characteristic curves.

Results: Among the 76 patients, 54 underwent revascularization. Patients who underwent revascularization had higher pericoronary FAI and lower FFR-CT values. Subtraction FFR-CT values were higher than those obtained using conventional methods. Models 4 (subtraction CCTA), 5 (Model 4 + subtraction FFR-CT), and 6 (Model 5 + subtraction FAI) showed significantly better diagnostic efficacy for revascularization needs than compared to the Models 1 (conventional CCTA), 2 (Model 1 + conventional FFR-CT), and 3 (Model 2 + conventional FAI) (all p < 0.05). In the subtraction models, Model 6 and 5 were significantly more effective than Models 4 (all p < 0.05). Additionally, when clinical variables (male, age, body mass index, hypertension, dyslipidemia, diabetes mellitus, and smoking) were incorporated into Models 3 and 6, the resulting Models 7 and 8 performed significantly better than Model 3 (all p < 0.05).

Conclusion: Subtraction techniques have significantly improved the efficacy of CCTA with FFR-CT in assessing the need for revascularization in patients with CAD. By integrating clinical variables, CCTA, FFR-CT, and pericoronary FAI, individualized therapeutic decisions for CAD patients can be further optimized.

Keywords: Coronary artery disease; Coronary computed tomography angiography; Fat attenuation index; Fractional flow reserve; Subtraction.

Fig. 1

Patient inclusion flowchart

Fig. 2

Representative images of a patient with coronary artery disease. Conventional coronary computed tomography angiography revealed both calcified and noncalcified plaques in the proximal LAD segment, and part of the lumen could not be evaluated because of occlusion of calcified plaques (A, red arrows). Post-subtraction, significant luminal stenosis became evident (E, white, and red arrows), aligning with invasive coronary angiography findings (D, white and red arrows). The lumen appeared patent and filled after PCI (H, white and red arrows). Conventional and subtraction FFR-CT were 0.63 (B) and 0.50 (F), and the conventional and subtraction fat attenuation indices were − 84 (C) and − 83 Hounsfield units (G), respectively. FFR-CT, fractional flow reserve with computed tomography; LAD, left anterior descending artery

Fig. 3

AUC comparisons for patients with and without revascularization identified by each diagnostic model. The definitions for Models 1–8 were as outlined in Table 3. Positive indicators for these models include FFR-CT measurements ≤ 0.8 and CCTA ≥ 50%. AUC, area under the curve; CCTA, coronary computed tomography angiography; FFR-CT, fractional flow reserve with computed tomography; NRI, net reclassification improvement; IDI, integrated discrimination improvement; CI, confidence interval; p, p-value