The new role of diagnostic angiography in coronary physiological assessment

Evaluation of models of sequestration flow in coronary arteries-Physiology versus anatomy?

BACKGROUND

Myocardial ischaemia results from insufficient coronary blood flow. Computed virtual fractional flow reserve (vFFR) allows quantification of proportional flow loss without the need for invasive pressure-wire testing. In the current study, we describe a novel, conductivity model of side branch flow, referred to as 'leak'. This leak model is a function of taper and local pressure, the latter of which may change radically when focal disease is present. This builds upon previous techniques, which either ignore side branch flow, or rely purely on anatomical factors. This study aimed to describe a new, conductivity model of side branch flow and compare this with established anatomical models.

METHODS AND RESULTS

The novel technique was used to quantify vFFR, distal absolute flow (Qd) and microvascular resistance (CMVR) in 325 idealised 1D models of coronary arteries, modelled from invasive clinical data. Outputs were compared to an established anatomical model of flow. The conductivity model correlated and agreed with the reference model for vFFR (r = 0.895, p < 0.0001; ＋0.02, 95% CI 0.00 to ＋ 0.22), Qd (r = 0.959, p < 0.0001; -5.2 mL/min, 95% CI -52.2 to ＋13.0) and CMVR (r = 0.624, p < 0.0001; ＋50 Woods Units, 95% CI -325 to ＋2549).

CONCLUSION

Agreement between the two techniques was closest for vFFR, with greater proportional differences seen for Qd and CMVR. The conductivity function assumes vessel taper was optimised for the healthy state and that CMVR was not affected by local disease. The latter may be addressed with further refinement of the technique or inferred from complementary image data. The conductivity technique may represent a refinement of current techniques for modelling coronary side-branch flow. Further work is needed to validate the technique against invasive clinical data.

Effect of Missed Post-Procedure Creatinine Measurement on Sub-Acute Kidney Injury Following Coronary Angiography

Serum creatinine (SCr) levels are essential for the diagnosis of kidney disease after coronary angiography (CAG). However, the influence of missed post-procedure SCr measurement in this situation is unclear. The present study included 14,127 patients undergoing CAG as part of the Cardiorenal ImprovemeNt registry II. Patients were divided into two groups according to whether a post-procedure SCr was measured within 3 days. The primary endpoint was acute kidney disease (AKD). Logistic regression was used to evaluate the relationship between post-procedure SCr and AKD. Of the 14,127 patients (61.6 ± 9.8 years, 34.2% females), 55.4% (n = 7822) did not have a post-procedure SCr measurement. The incidence of AKD was higher in the missed post-procedure SCr group (15.7 vs 11.9%; median follow-up 6.54 years). Multivariate logistic regression showed that missed post-procedure SCr measurement was associated with significantly higher risk of AKD (adjusted odds ratio [aOR]: 1.26, 95% CI: 1.10-1.45, P < .001). The results were more significant in patients with normal renal function at baseline (aOR: 1.36, 95% CI: 1.16-1.60, P < .001). In our study, over half of the patients undergoing CAG missed their post-procedure SCr measurement. The missed post-procedure SCr group had a significantly higher risk of developing AKD compared with those with a post-procedure SCr measurement.

Rapid virtual fractional flow reserve using 3D computational fluid dynamics

Aims

Over the last ten years, virtual Fractional Flow Reserve (vFFR) has improved the utility of Fractional Flow Reserve (FFR), a globally recommended assessment to guide coronary interventions. Although the speed of vFFR computation has accelerated, techniques utilising full 3D computational fluid dynamics (CFD) solutions rather than simplified analytical solutions still require significant time to compute.

Methods and results

This study investigated the speed, accuracy and cost of a novel 3D-CFD software method based upon a graphic processing unit (GPU) computation, compared with the existing fastest central processing unit (CPU)-based 3D-CFD technique, on 40 angiographic cases. The novel GPU simulation was significantly faster than the CPU method (median 31.7 s (Interquartile Range (IQR) 24.0-44.4s) vs. 607.5 s (490-964 s), P < 0.0001). The novel GPU technique was 99.6% (IQR 99.3-99.9) accurate relative to the CPU method. The initial cost of the GPU hardware was greater than the CPU (£4080 vs. £2876), but the median energy consumption per case was significantly less using the GPU method (8.44 (6.80-13.39) Wh vs. 2.60 (2.16-3.12) Wh, P < 0.0001).

Conclusion

This study demonstrates that vFFR can be computed using 3D-CFD with up to 28-fold acceleration than previous techniques with no clinically significant sacrifice in accuracy.

Sex differences in coronary microvascular resistance measured by a computational fluid dynamics model

Background

Increased coronary microvascular resistance (CMVR) is associated with coronary microvascular dysfunction (CMD). Although CMD is more common in women, sex-specific differences in CMVR have not been demonstrated previously.

Aim

To compare CMVR between men and women being investigated for chest pain.

Methods and results

We used a computational fluid dynamics (CFD) model of human coronary physiology to calculate absolute CMVR based on invasive coronary angiographic images and pressures in 203 coronary arteries from 144 individual patients. CMVR was significantly higher in women than men (860 [650-1,205] vs. 680 [520-865] WU, Z = -2.24, p = 0.025). None of the other major subgroup comparisons yielded any differences in CMVR.

Conclusion

CMVR was significantly higher in women compared with men. These sex-specific differences may help to explain the increased prevalence of CMD in women.

Systematic coronary physiology improves level of agreement in diagnostic coronary angiography

OBJECTIVE

The training of interventional cardiologists (ICs), non-interventional cardiologists (NICs) and cardiac surgeons (CSs) differs, and this may be reflected in their interpretation of invasive coronary angiography (ICA) and management plan. Availability of systematic coronary physiology might result in more homogeneous interpretation and management strategy compared with ICA alone.

METHODS

150 coronary angiograms from patients with stable chest pain were presented independently to three NICs, three ICs and three CSs. By consensus, each group graded (1) coronary disease severity and (2) management plan, using options: (a) optimal medical therapy alone, (b) percutaneous coronary intervention, (c) coronary artery bypass graft or (d) more investigation required. Each group was then provided with fractional flow reserve (FFR) from all major vessels and asked to repeat the analysis.

RESULTS

There was only 'fair' level of agreement of management plan among ICs, NICs and CSs (kappa 0.351, 95% CI 0.295-0.408, p<0.001) based on ICA alone (complete agreement in 35% of cases), which almost doubled to 'good' level (kappa 0.635, 95% CI 0.572-0.697, p<0.001) when comprehensive FFR was available (complete agreement in 66% of cases). Overall, the consensus management plan changed in 36.7%, 52% and 37.3% of cases for ICs, NICs and CSs, respectively, when FFR data were available.

CONCLUSIONS

Compared with ICA alone, the availability of systematic FFR of all major coronary arteries produced a significantly more concordant interpretation and more homogeneous management plan among IC, NIC and CS specialists. Comprehensive physiological assessment may be of value in routine care for Heart Team decision-making.

TRIAL REGISTRATION NUMBER

NCT01070771.

The Complementary Value of Absolute Coronary Flow in the Assessment of Patients with Ischaemic Heart Disease

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. Here we compared fractional CBF with the absolute CBF (aCBF in mL/min), 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, 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 ‘grey-zone’.

The Use of Digital Coronary Phantoms for the Validation of Arterial Geometry Reconstruction and Computation of Virtual FFR

We present computational fluid dynamics (CFD) results of virtual fractional flow reserve (vFFR) calculations, performed on reconstructed arterial geometries derived from a digital phantom (DP). The latter provides a convenient and parsimonious description of the main vessels of the left and right coronary arterial trees, which, crucially, is CFD-compatible. Using our DP, we investigate the reconstruction error in what we deem to be the most relevant way—by evaluating the change in the computed value of vFFR, which results from varying (within representative clinical bounds) the selection of the virtual angiogram pair (defined by their viewing angles) used to segment the artery, the eccentricity and severity of the stenosis, and thereby, the CFD simulation’s luminal boundary. The DP is used to quantify reconstruction and computed haemodynamic error within the VIRTUheartTM software suite. However, our method and the associated digital phantom tool are readily transferable to equivalent, clinically oriented workflows. While we are able to conclude that error within the VIRTUheartTM workflow is suitably controlled, the principal outcomes of the work reported here are the demonstration and provision of a practical tool along with an exemplar methodology for evaluating error in a coronary segmentation process.

Refining Our Understanding of the Flow Through Coronary Artery Branches; Revisiting Murray's Law in Human Epicardial Coronary Arteries

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 D^P) 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.

Intelligent Algorithm-Based Multislice Spiral Computed Tomography to Diagnose Coronary Heart Disease

In this study, dictionary learning and expectation maximization reconstruction (DLEM) was combined to denoise 64-slice spiral CT images, and results of coronary angiography (CAG) were used as standard to evaluate its clinical value in diagnosing coronary artery diseases. 120 patients with coronary heart disease (CHD) confirmed by CAG examination were retrospectively selected as the research subjects. According to the random number table method, the patients were divided into two groups: the control group was diagnosed by conventional 64-slice spiral CT images, and the observation group was diagnosed by 64-slice spiral CT images based on the DLEM algorithm, with 60 cases in both groups. With CAG examination results as the standard, the diagnostic effects of the two CT examination methods were compared. The results showed that when the number of iterations of maximum likelihood expectation maximization (MLEM) algorithm reached 50, the root mean square error (RMSE) and peak signal to noise ratio (PSNR) values were similar to the results obtained by the DLEM algorithm under a number of iterations of 10 when the RMSE and PSNR values were 18.9121 dB and 74.9911 dB, respectively. In the observation group, 28.33% (17/60) images were of grade 4 or above before processing; after processing, it was 70% (42/60), significantly higher than the proportion of high image quality before processing. The overall diagnostic consistency, sensitivity, specificity, and accuracy (88.33%, 86.67%, 80%, and 85%) of the observation group were better than those in the control group (60.46%, 62.5%, 58.33%, and 61.66%). In conclusion, the DLEM algorithm has good denoising effect on 64-slice spiral CT images, which significantly improves the accuracy in the diagnosis of coronary artery stenosis and has good clinical diagnostic value and is worth promoting.

Assessment of the routine reporting of very low-dose exercise-first myocardial perfusion SPECT from a large-scale real-world cohort and correlation with the subsequent reporting of coronary stenosis at angiography

PURPOSE

Our study assesses the routine reporting of exercise ischemia using very low-dose exercise-first myocardial perfusion SPECT in a large number of patients and under real-life conditions, by evaluating correlations with the subsequent routine reporting of coronary stenosis by angiography and with factors that predict ischemia.

METHODS

Data from 13,126 routine exercise MPI reports, from 11,952 patients (31% women), using very low doses of sestamibi and a high-sensitivity cardiac CZT camera, were extracted to assess the reporting of significant MPI-ischemia (> 1 left ventricular segment), to determine the MPI normalcy rate in a group with < 5% pretest probability of coronary artery disease (CAD) (n = 378), and to assess the ability of MPI to predict a > 50% coronary stenosis in patients with available coronary angiography reports in the 3 months after the MPI (n = 713).

RESULTS

The median effective patient dose was 2.51 [IQR: 1.00-4.71] mSv. The normalcy rate was 98%, and the MPI-ischemia rate was independently predicted by a known CAD, the male gender, obesity, and a < 50% LV ejection fraction, ranging from 29.5% with all these risk factors represented to 1.5% when there were no risk factors. A > 50% coronary stenosis was significantly predicted by MPI-ischemia, less significantly for mild (odds ratio [95% confidence interval]: 1.61 [1.26-1.96]) than for moderate-to-severe MPI-ischemia (4.05 [3.53-4.57]) and was also impacted by having a known CAD (2.17 [1.83-2.51]), by a submaximal exercise test (1.48 [1.15-1.81]) and being ≥ 65 years of age (1.43 [1.11-1.76]).

CONCLUSION

Ischemia detected using a very low-dose exercise-first MPI protocol in a large-scale clinical cohort and under real-life routine conditions is a highly significant predictor for the subsequent reporting of coronary stenosis, although this prediction is enhanced by other variables. This weakly irradiating approach is amenable to being repeated at shorter time intervals, in target patient groups with a high probability of MPI-ischemia.

The importance of three dimensional coronary artery reconstruction accuracy when computing virtual fractional flow reserve from invasive angiography

Three dimensional (3D) coronary anatomy, reconstructed from coronary angiography (CA), is now being used as the basis to compute 'virtual' fractional flow reserve (vFFR), and thereby guide treatment decisions in patients with coronary artery disease (CAD). Reconstruction accuracy is therefore important. Yet the methods required remain poorly validated. Furthermore, the magnitude of vFFR error arising from reconstruction is unkown. We aimed to validate a method for 3D CA reconstruction and determine the effect this had upon the accuracy of vFFR. Clinically realistic coronary phantom models were created comprosing seven standard stenoses in aluminium and 15 patient-based 3D-printed, imaged with CA, three times, according to standard clinical protocols, yielding 66 datasets. Each was reconstructed using epipolar line projection and intersection. All reconstructions were compared against the real phantom models in terms of minimal lumen diameter, centreline and surface similarity. 3D-printed reconstructions (n = 45) and the reference files from which they were printed underwent vFFR computation, and the results were compared. The average error in reconstructing minimum lumen diameter (MLD) was 0.05 (± 0.03 mm) which was < 1% (95% CI 0.13-1.61%) compared with caliper measurement. Overall surface similarity was excellent (Hausdorff distance 0.65 mm). Errors in 3D CA reconstruction accounted for an error in vFFR of ± 0.06 (Bland Altman 95% limits of agreement). Errors arising from the epipolar line projection method used to reconstruct 3D coronary anatomy from CA are small but contribute to clinically relevant errors when used to compute vFFR.

Operator-dependent variability of angiography-derived fractional flow reserve and the implications for treatment

AIMS

To extend the benefits of physiologically guided percutaneous coronary intervention to many more patients, angiography-derived, or 'virtual' fractional flow reserve (vFFR) has been developed, in which FFR is computed, based upon the images, instead of being measured invasively. The effect of operator experience with these methods upon vFFR accuracy remains unknown. We investigated variability in vFFR results based upon operator experience with image-based computational modelling techniques.

METHODS AND RESULTS

Virtual fractional flow reserve was computed using a proprietary method (VIRTUheart) from the invasive angiograms of patients with coronary artery disease. Each case was processed by an expert (>100 vFFR cases) and a non-expert (<20 vFFR cases) operator and results were compared. The primary outcome was the variability in vFFR between experts and non-experts and the impact this had upon treatment strategy (PCI vs. conservative management). Two hundred and thirty-one vessels (199 patients) were processed. Mean non-expert and expert vFFRs were similar overall [0.76 (0.13) and 0.77 (0.16)] but there was significant variability between individual results (variability coefficient 12%, intraclass correlation coefficient 0.58), with only moderate agreement (κ = 0.46), and this led to a statistically significant change in management strategy in 27% of cases. Variability was significantly lower, and agreement higher, for expert operators; a change in their recommended management occurred in 10% of repeated expert measurements and 14% of inter-expert measurements.

CONCLUSION

Virtual fractional flow reserve results are influenced by operator experience of vFFR processing. This had implications for treatment allocation. These results highlight the importance of training and quality assurance to ensure reliable, repeatable vFFR results.

Virtual (Computed) Fractional Flow Reserve: Future Role in Acute Coronary Syndromes

The current management of acute coronary syndromes (ACS) is with an invasive strategy to guide treatment. However, identifying the lesions which are physiologically significant can be challenging. Non-invasive imaging is generally not appropriate or timely in the acute setting, so the decision is generally based upon visual assessment of the angiogram, supplemented in a small minority by invasive pressure wire studies using fractional flow reserve (FFR) or related indices. Whilst pressure wire usage is slowly increasing, it is not feasible in many vessels, patients and situations. Limited evidence for the use of FFR in non-ST elevation (NSTE) ACS suggests a 25% change in management, compared with traditional assessment, with a shift from more to less extensive revascularisation. Virtual (computed) FFR (vFFR), which uses a 3D model of the coronary arteries constructed from the invasive angiogram, and application of the physical laws of fluid flow, has the potential to be used more widely in this situation. It is less invasive, fast and can be integrated into catheter laboratory software. For severe lesions, or mild disease, it is probably not required, but it could improve the management of moderate disease in 'real time' for patients with non-ST elevation acute coronary syndromes (NSTE-ACS), and in bystander disease in ST elevation myocardial infarction. Its practicability and impact in the acute setting need to be tested, but the underpinning science and potential benefits for rapid and streamlined decision-making are enticing.