Background: Quantification of coronary blood flow is used to evaluate coronary artery disease, but our understanding of flow through branched systems is poor. Murray’s law defines coronary morphometric scaling, the relationship between flow (Q) and vessel diameter (D) and is the basis for minimum lumen area targets when intervening on bifurcation lesions. Murray’s original law (Q α DP) dictates that the exponent (P) is 3.0, whilst constant blood velocity throughout the system would suggest an exponent of 2.0. In human coronary arteries, the value of Murray’s exponent remains unknown.Aim: To establish the exponent in Murray’s power law relationship that best reproduces coronary blood flows (Q) and microvascular resistances (Rmicro) in a bifurcating coronary tree.Methods and Results: We screened 48 cases, and were able to evaluate inlet Q and Rmicro in 27 branched coronary arteries, taken from 20 patients, using a novel computational fluid dynamics (CFD) model which reconstructs 3D coronary anatomy from angiography and uses pressure-wire measurements to compute Q and Rmicro distribution in the main- and side-branches. Outputs were validated against invasive measurements using a Rayflow™ catheter. A Murray’s power law exponent of 2.15 produced the strongest correlation and closest agreement with inlet Q (zero bias, r = 0.47, p = 0.006) and an exponent of 2.38 produced the strongest correlation and closest agreement with Rmicro (zero bias, r = 0.66, p = 0.0001).Conclusions: The optimal power law exponents for Q and Rmicro were not 3.0, as dictated by Murray’s Law, but 2.15 and 2.38 respectively. These data will be useful in assessing patient-specific coronary physiology and tailoring revascularisation decisions.
The duty to protect patient welfare underpins undergraduate medical ethics and patient safety teaching. The current syllabus for patient safety emphasises the significance of organisational contribution to healthcare failures. However, the ongoing over-reliance on whistleblowing disproportionately emphasises individual contributions, alongside promoting a culture of blame and defensiveness among practitioners. Diane Vaughan’s ‘Normalisation of Deviance’ (NoD) provides a counterpoise to such individualism, describing how signals of potential danger are collectively misinterpreted and incorporated into the accepted margins of safe operation. NoD is an insidious process that often goes unnoticed, thus minimising the efficacy of whistleblowing as a defence against inevitable disaster. In this paper, we illustrate what can be learnt by greater attention to the collective, organisational contributions to healthcare failings by applying NoD to The Morecambe Bay Investigation. By focusing on a cluster of five ‘serious untoward incidents’ occurring in 2008, we describe a cycle of NoD affecting trust handling of events that allowed poor standards of care to persist for several years, before concluding with a poignant example of the limitations of whistleblowing, whereby the raising of concerns by a senior consultant failed to generate a response at trust board level. We suggest that greater space in medical education is needed to develop a thorough understanding of the cultural and organisational processes that underpin healthcare failures, and that medical education would benefit from integrating the teaching of medical ethics and patient safety to resolve the tension between systems approaches to safety and the individualism of whistleblowing.
Background Ischaemic heart disease results from insufficient coronary blood flow. Direct measurement of absolute flow (mL/min) is feasible, but has not entered routine clinical practice in most catheterisation laboratories. Interventional cardiologists therefore rely on surrogate markers of flow. Recently, we described a computational fluid dynamics (CFD) method for predicting flow that differentiates inlet, side branch and outlet flows during angiography. In the current study, we evaluate a new method that regionalises flow along the length of the artery. Methods and Results Three-dimensional coronary anatomy was reconstructed from angiograms from 20 patients with chronic coronary syndrome. All flows were computed using CFD by applying the pressure gradient to the reconstructed geometry. Side branch flow was modelled as a porous wall boundary. Side branch flow magnitude was based on morphometric scaling laws with two models: a homogenous model with flow loss along the entire arterial length; and a regionalised model with flow proportional to local taper. Flow results were validated against invasive measurements of flow by continuous infusion thermodilution (Coroventis™, Abbott). Both methods quantified flow relative to the invasive measures: homogenous (r 0.47, P 0.006; zero bias; 95% CI -168 to +168 mL/min); regionalised method (r 0.43, P 0.013; zero bias; 95% CI -175 to +175 mL/min). Conclusions During angiography and pressure-wire assessment, coronary flow can now be regionalised and differentiated at the inlet, outlet and side branches. The effect of epicardial disease on agreement suggests the model may be best targeted at cases with a stenosis close to side branches.
Fractional flow reserve (FFR) is the current gold standard invasive assessment of coronary artery disease (CAD). FFR reports coronary blood flow (CBF) as a fraction of a hypothetical and unknown normal value. Although used routinely to diagnose CAD and guide treatment, how accurately FFR predicts actual CBF changes remains unknown. In this study, we compared fractional CBF with absolute CBF (aCBF, in ml min−1), measured with a computational method during standard angiography and pressure wire assessment, on 203 diseased arteries (143 patients). We found a substantial correlation between the two measurements (r = 0.89 and Cohen’s kappa = 0.71). Concordance between fractional and absolute CBF reduction was high when FFR was >0.80 (91%) but reduced when FFR was ≤0.80 (81%), 0.70–0.80 (68%) and, particularly, 0.75–0.80 (62%). Discordance was associated with coronary microvascular resistance, vessel diameter and mass of myocardium subtended, all factors to which FFR is agnostic. Assessment of aCBF complements FFR and may be valuable to assess CBF, particularly in cases within the FFR ‘gray zone’.
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