Key result
Novel computational fluid dynamics combining angiography and FFR detects abnormal SPECT MPI with ~0.88 AUC.
Why the study?
To investigate the clinical feasibility of a novel computational fluid dynamics method combining coronary angiography and FFR by evaluating its ability to identify myocardial ischemia diagnosed by SPECT-MPI.
Does a novel computational fluid dynamics based method combining coronary angiography and FFR accurately identify myocardial ischemia compared to SPECT-MPI?
Observational (n=52)
Does a novel computational fluid dynamics based method combining coronary angiography and FFR accurately identify myocardial ischemia compared to SPECT-MPI?
Effect estimate: ROC-AUC 0.876 (95% CI 0.783-0.970)
p-value: p=<0.001
A novel CFD-based method combining coronary angiography and FFR accurately identifies myocardial ischemia, offering a quantitative approach for assessing coronary physiology.
May support CFD flow metrics for ischemia detection; leaves open prospective validation before clinical adoption.
BACKGROUND: With a 3D model reconstructed from coronary angiography, intracoronary blood flow can be calculated using a computational fluid dynamics (CFD) model with fractional flow reserve (FFR) measured pressure as boundary conditions. AIMS: The aim of this study is to investigate the clinical feasibility of this method by evaluating its ability to identify myocardial ischemia diagnosed by SPECT myocardial perfusion imaging (MPI). METHODS: Patients who underwent both SPECT-MPI and coronary angiography with FFR within 1 week were enrolled. Based on the summed stress score (SSS) and summed difference score (SDS) of SPECT MPI, myocardial ischemia in individual coronary territories was identified. Mean flow rate (Q), total flow resistance (TFR), absolute microvascular resistance (AMR) and their corresponding resting state indices were computed using the novel CFD model. RESULTS: A total of 52 patients with 53 vessels were investigated. Based on SPECT MPI, 23 patients (43.4%) were associated with abnormal MPI. Q was significant higher in normal MPI group compared with abnormal MPI group (59.68 ± 40.33 mL/min vs. 25.67 ± 21.55 mL/min, p < 0.001). The TFR were significantly lower in normal MPI group (TFR: 1898.25 ± 951.55 mmHg min/L vs. 4786.31 ± 3056.18 mmHg min/L, p < 0.001). The ROC-AUC of Q and TFR for discriminating normal and abnormal MPI were 0.876 (95% CI: 0.783-0.970, p < 0.001) and 0.854 (95% CI: 0.745-0.963, p < 0.001). CONCLUSIONS: Intracoronary flow assessed by the novel CFD based method has shown promise in accurately identifying patients with abnormal SPECT MPI, offering a convenient and quantitative approach for assessing coronary physiology.
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Xie et al. (2025) conducted an observational in Myocardial ischemia (n=52). Computational fluid dynamics (CFD) based method vs. SPECT myocardial perfusion imaging (MPI) was evaluated on Discrimination of normal and abnormal SPECT MPI using mean flow rate (Q) (ROC-AUC 0.876, 95% CI 0.783-0.970, p=<0.001). A novel computational fluid dynamics method combining coronary angiography and FFR accurately identified abnormal SPECT MPI, with an ROC-AUC of 0.876 (95% CI: 0.783-0.970; p < 0.001) for mean flow rate.
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