Key result
Angiography-derived 3D CFD predicts continuous thermodilution MRR with fair diagnostic accuracy and ~0.77 AUC.
Why the study?
Invasive assessment of coronary microvascular dysfunction is technically challenging, costly, and time-consuming, and although 3D computational fluid dynamics modelling offers an alternative, it lacks robust in vivo validation.
Does a 3D computational fluid dynamics model derived from invasive coronary angiography accurately estimate microvascular resistance reserve and absolute coronary flow compared to invasive continuous thermodilution in patients with acute and chronic coronary syndromes?
Cohort (n=89)
All reconstructions and physiological simulations were performed blinded to invasive physiology
Yes
Does a 3D computational fluid dynamics model derived from invasive coronary angiography accurately estimate microvascular resistance reserve and absolute coronary flow compared to invasive continuous thermodilution in patients with acute and chronic coronary syndromes?
An angiography-derived 3D computational fluid dynamics model demonstrated moderate correlation and fair diagnostic accuracy (AUC 0.77) for assessing microvascular resistance reserve compared to invasive continuous thermodilution, offering a potentially less-invasive alternative that avoids dedicated infusion microcatheters.
Answers are grounded in this paper and cite their sources.
3D CFD may support non-invasive MRR estimation; leaves open validation before replacing invasive thermodilution.
Coronary microvascular dysfunction is associated with myocardial ischaemia and an adverse prognosis, but accurate invasive assessment is technically challenging, requires dedicated hardware and increases procedure time and cost. Assessment can be performed with three-dimensional (3D) computational fluid dynamics (CFD) modelling, but this technique lacks robust in vivo validation. In this study, we compared the accuracy of a 3D CFD method against continuous thermodilution (CIT). Patients with acute and chronic coronary syndromes, undergoing CIT and angiography-derived assessment, were prospectively recruited from two tertiary cardiac centres. Invasive coronary angiographic images were used to reconstruct 3D anatomy in silico . Microvascular resistance reserve (MRR) and absolute flow were computed using 3D CFD in reconstructed coronary arteries. Invasive pressure measurements, recorded during fractional flow reserve assessment, informed the CFD boundary conditions. Paired flow results were available for 131 arteries from 89 patients. Median FFR was 0.81 [0.70 – 0.89] and 108 (81%) vessels contained an epicardial stenosis. Median computed MRR was 2.31 [1.83 – 3.00], which was significantly lower than CIT assessed MRR (2.79 [2.21 – 3.52], z = 3.57, p = 0.0004). There was evidence of a moderate relationship between computed and measured MRR (ρ = 0.58, p < 0.0001) and area under the receiver operator characteristic curve was 0.77 (95% CI 0.68–0.86), indicating fair classification. There was a moderate relationship between computed and measured hyperaemic vessel inlet flow (ρ = 0.44, p < 0.0001). For both MRR and flow, agreement improved at lower, more clinically relevant, values. In this clinical validation study, when compared with CIT, the novel CFD method demonstrated a moderate correlation, and fair diagnostic accuracy. This CFD method may be a useful, low-cost and less-invasive tool in the assessment of microvascular physiology that could complement current invasive techniques.
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Taylor et al. (2026) conducted a cohort in Acute and chronic coronary syndromes undergoing coronary physiological assessment (n=89). 3D computational fluid dynamics (CFD) modelling (virtuQ) vs. Invasive continuous infusion thermodilution (CIT) was evaluated on Agreement and diagnostic accuracy of microvascular resistance reserve (MRR) between 3D CFD (virtuQ) and continuous thermodilution (CIT) (ρ = 0.58; AUC 0.77, 95% CI 0.68-0.86, p=<0.0001). The 3D CFD model (virtuQ) showed moderate correlation and fair diagnostic accuracy for MRR compared with continuous thermodilution.
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