Relationship Between Coronary Contrast-Flow Quantitative Flow Ratio and Myocardial Ischemia Assessed by SPECT MPI.

PURPOSE: A new method has been developed to calculate fractional flow reserve (FFR) from invasive coronary angiography, the so-called "contrast-flow quantitative flow ratio (cQFR)". Recently, cQFR was compared to invasive FFR in intermediate coronary lesions showing an overall diagnostic accuracy of 85%. The purpose of this study was to investigate the relationship between cQFR and myocardial ischemia assessed by single-photon emission computed tomography myocardial perfusion imaging (SPECT MPI). METHODS: Patients who underwent SPECT MPI and coronary angiography within 3 months were included. The cQFR computation was performed offline, using dedicated software. The cQFR computation was based on 3-dimensional quantitative coronary angiography (QCA) and computational fluid dynamics. The standard 17-segment model was used to determine the vascular territories. Myocardial ischemia was defined as a summed difference score ≥2 in a vascular territory. A cQFR of ≤0.80 was considered abnormal. RESULTS: Two hundred and twenty-four coronary arteries were analysed in 85 patients. Overall accuracy of cQFR to detect ischemia on SPECT MPI was 90%. In multivariable analysis, cQFR was independently associated with ischemia on SPECT MPI (OR per 0.01 decrease of cQFR: 1.10; 95% CI 1.04-1.18, p = 0.002), whereas clinical and QCA parameters were not. Furthermore, cQFR showed incremental value for the detection of ischemia compared to clinical and QCA parameters (global chi square 48.7 to 62.6; p <0.001). CONCLUSIONS: A good relationship between cQFR and SPECT MPI was found. cQFR was independently associated with ischemia on SPECT MPI and showed incremental value to detect ischemia compared to clinical and QCA parameters.

Clinical validation of the new T- and Y-shape models for the quantitative analysis of coronary bifurcations: an interobserver variability study.

OBJECTIVES: This article presents the results of an interobserver validation study of our new T- and Y-shape bifurcation models including their edge segment analyses. BACKGROUND: Over the last years, the coronary artery intervention procedures have been developed more and more toward bifurcation stenting. Because traditional straight vessel quantitative coronary arteriography (QCA) is not sufficient for these measurements, the need has grown for new bifurcation analysis methods. METHODS: In this article, our two new bifurcation analysis models are presented, the Y-shape and T-shape model. These models were designed for the accurate measurement of the clinically relevant parameters of a coronary bifurcation, for different morphologies and intervention strategies and include an edge segment analysis, to accurately measure (drug-eluting) stent, stent edge, and ostial segment parameters. RESULTS: The results of an interobserver validation study of our T-shape and Y-shape analyses are presented, both containing the pre- and post-intervention analyses of each 10 cases. These results are associated with only small systematic and random errors, in the majority of the cases compliant with the QCA guidelines for straight analyses. The results for the edge segment analyses are also very good, with almost all the values within the margins that have been set by our brachytherapy directive. CONCLUSIONS: Our new bifurcation approaches including their edge segment analyses are very robust and reproducible, and therefore a great extension to the field of quantitative coronary angiography.

The impact of acquisition angle differences on three-dimensional quantitative coronary angiography.

BACKGROUND: Three-dimensional (3D) quantitative coronary angiography (QCA) requires two angiographic views to restore vessel dimensions. This study investigated the impact of acquisition angle differences (AADs) of the two angiographic views on the assessed dimensions by 3D QCA. METHODS: X-ray angiograms of an assembled brass phantom with different types of straight lesions were recorded at multiple angiographic projections. The projections were randomly matched as pairs and 3D QCA was performed in those pairs with AAD larger than 25°. The lesion length and diameter stenosis in three different lesions, a circular concentric severe lesion (A), a circular concentric moderate lesion (B), and a circular eccentric moderate lesion (C), were measured by 3D QCA. The acquisition protocol was repeated for a silicone bifurcation phantom, and the bifurcation angles and bifurcation core volume were measured by 3D QCA. The measurements were compared with the true dimensions if applicable and their correlation with AAD was studied. RESULTS: 50 matched pairs of angiographic views were analyzed for the brass phantom. The average value of AAD was 48.0 ± 14.1°. The percent diameter stenosis was slightly overestimated by 3D QCA for all lesions: A (error 1.2 ± 0.9%, P < 0.001); B (error 0.6 ± 0.5%, P < 0.001); C (error 1.1 ± 0.6%, P < 0.001). The correlation of the measurements with AAD was only significant for lesion A (R(2) = 0.151, P = 0.005). The lesion length was slightly overestimated by 3D QCA for lesion A (error 0.06 ± 0.18 mm, P = 0.026), but well assessed for lesion B (error -0.00 ± 0.16 mm, P = 0.950) and lesion C (error -0.01 ± 0.18 mm, P = 0.585). The correlation of the measurements with AAD was not significant for any lesion. Forty matched pairs of angiographic views were analyzed for the bifurcation phantom. The average value of AAD was 49.1 ± 15.4°. 3D QCA slightly overestimated the proximal angle (error 0.4 ± 1.1°, P = 0.046) and the distal angle (error 1.5 ± 1.3°, P < 0.001). The correlation with AAD was only significant for the distal angle (R(2) = 0.256, P = 0.001). The correlation of bifurcation core volume measurements with AAD was not significant (P = 0.750). Of the two aforementioned measurements with significant correlation with AAD, the errors tended to increase as AAD became larger. CONCLUSIONS: 3D QCA can be used to reliably assess vessel dimensions and bifurcation angles. Increasing the AAD of the two angiographic views does not increase accuracy and precision of 3D QCA for circular lesions or bifurcation dimensions.

A novel three-dimensional quantitative coronary angiography system: In-vivo comparison with intravascular ultrasound for assessing arterial segment length.

BACKGROUND: Accurate on-line assessments of vessel dimensions are of utmost importance for selecting the appropriate stent size in coronary interventions. Recently a new three-dimensional quantitative coronary angiography (3D QCA) analytical software package was developed to accurately assess the vessel dimensions for the planning and guidance of such coronary interventions. This study aimed to validate the 3D QCA software package for assessing arterial segment length by comparing with intravascular ultrasound (IVUS). In addition, the difference in the two measurements from 3D QCA and IVUS for curved segments was studied. METHODS: A retrospective study including 20 patients undergoing both coronary angiography and IVUS examinations of the left coronary artery was set up for the validation. The same vessel segments of interest between proximal and distal markers were identified and measured on both angiographic and IVUS images, by the 3D QCA software and by a quantitative IVUS software package, respectively. In addition, the curvature of each of the segments of interest was assessed and the correlation between the accumulated curvature of the segment and the difference in segment lengths measured from the two imaging modalities was analyzed. RESULTS: 37 vessel segments of interest were identified from both angiographic and IVUS images. The 3D QCA segment length was slightly longer than the IVUS segment length (15.42 +/- 6.02 mm vs. 15.12 +/- 5.81 mm, P = 0.040). The linear correlation of the two measurements was: 3D QCA Length = -0.09 + 1.03 x IVUS Length (r(2) = 0.98, P < 0.001). Bland-Altman plot showed that the difference in the two measurements was not correlated with the average of the two measurements (P = 0.141), but with the accumulated curvature of the segment (P = 0.015). After refining the difference by the correlation, the average difference of the two measurements decreased from 0.30 +/- 0.86 mm (P = 0.040) to 0.00 +/- 0.78 mm (P = 0.977). CONCLUSIONS: The 3D QCA software package can accurately assess the actual arterial segment length. The difference in segment lengths measured from 3D QCA and IVUS was correlated with the accumulated curvature of the segment.

Shear Stress Estimated by Quantitative Coronary Angiography Predicts Plaques Prone to Progress and Cause Events.

OBJECTIVES: This study examined the value of endothelial shear stress (ESS) estimated in 3-dimensional quantitative coronary angiography (3D-QCA) models in detecting plaques that are likely to progress and cause events. BACKGROUND: Cumulative evidence has shown that plaque characteristics and ESS derived from intravascular ultrasound (IVUS)-based reconstructions enable prediction of lesions that will cause cardiovascular events. However, the prognostic value of ESS estimated by 3D-QCA in nonflow limiting lesions is yet unclear. METHODS: This study analyzed baseline virtual histology (VH)-IVUS and angiographic data from 28 lipid-rich lesions (i.e., fibroatheromas) that caused major adverse cardiovascular events or required revascularization (MACE-R) at 5-year follow-up and 119 lipid-rich plaques from a control group that remained quiescent. The segments studied by VH-IVUS at baseline were reconstructed using 3D-QCA software. In the obtained geometries, blood flow simulation was performed, and the pressure gradient across the lipid-rich plaque and the mean ESS values in 3-mm segments were estimated. The additive value of these hemodynamic indexes in predicting MACE-R beyond plaque characteristics was examined. RESULTS: MACE-R lesions were longer, had smaller minimum lumen area, increased plaque burden (PB), were exposed to higher ESS, and exhibited a higher pressure gradient. In multivariable analysis, PB (hazard ratio: 1.08; p = 0.004) and the maximum 3-mm ESS value (hazard ratio: 1.11; p = 0.001) were independent predictors of MACE-R. Lesions exposed to high ESS (>4.95 Pa) with a high-risk anatomy (minimal lumen area <4 mm2 and PB >70%) had a higher MACE-R rate (53.8%) than those with a low-risk anatomy exposed to high ESS (31.6%) or those exposed to low ESS who had high- (20.0%) or low-risk anatomy (7.1%; p < 0.001). CONCLUSIONS: In the present study, 3D-QCA-derived local hemodynamic variables provided useful prognostic information, and, in combination with lesion anatomy, enabled more accurate identification of MACE-R lesions.

Quantitative angiographic methods for bifurcation lesions: a consensus statement from the European Bifurcation Group.

The treatment of bifurcation lesions is complex and increasingly common. A growing number of dedicated bifurcation devices are under clinical evaluation, but no standardized methodology exists. Specifically, the angiographic analysis of bifurcation lesions is not standardized and current QCA packages are not designed for bifurcation lesions. This consensus statement outlines the limitations of conventional QCA in the bifurcation application, and outlines a new standard approach for the analysis and reporting of the angiographic results of the bifurcation lesion allowing for future trial and device comparisons and mechanistic insight into location and modes of treatment failure.

Comparison of Diagnostic Performance of Quantitative Flow Ratio in Patients With Versus Without Diabetes Mellitus.

Quantitative flow ratio (QFR) is a novel technique to calculate fractional flow reserve (FFR), without hyperemia induction or a pressure wire, and has not yet been validated in patients with diabetes mellitus (DM), who are at increased risk of coronary microvascular dysfunction. The purpose of our study was to compare the diagnostic performance of QFR in diabetic and nondiabetic patients. Patients who underwent invasive coronary angiography and subsequent invasive FFR measurement within 6 months were included. QFR was determined in all coronary arteries in which invasive FFR was performed, using a dedicated software package. Diagnostic accuracy and the area under the receiver-operating characteristic curve (AUC) were determined for QFR, using an invasive FFR cut-off value of ≤0.80 as the reference standard. In total, 320 coronary arteries from 66 (25%) diabetic and 193 (75%) nondiabetic patients were analyzed. On a vessel-based analysis, diagnostic accuracy, sensitivity, and specificity showed no significant difference between diabetic and nondiabetic patients: 88% versus 85% (p = 0.47), 71% versus 69% (p = 0.72), and 95% versus 91% (p = 0.24). Moreover, the AUC was not significantly different between patients with and without DM, 0.91 versus 0.93 (p = 0.74). The per-vessel AUC was significantly higher for QFR compared with percent diameter stenosis in both diabetic and nondiabetic patients, 0.91 versus 0.76 (p <0.05) and 0.93 versus 0.77 (p <0.001), respectively. In conclusion, we showed a good diagnostic performance of QFR which was independent of the presence of DM.

Referral of patients for fractional flow reserve using quantitative flow ratio.

AIMS: Quantitative flow ratio (QFR) is a recently developed technique to calculate fractional flow reserve (FFR) based on 3D quantitative coronary angiography and computational fluid dynamics, obviating the need for a pressure-wire and hyperaemia induction. QFR might be used to guide patient selection for FFR and subsequent percutaneous coronary intervention (PCI) referral in hospitals not capable to perform FFR and PCI. We aimed to investigate the feasibility to use QFR to appropriately select patients for FFR referral. METHODS AND RESULTS: Patients who underwent invasive coronary angiography in a hospital where FFR and PCI could not be performed and were referred to our hospital for invasive FFR measurement, were included. Angiogram images from the referring hospitals were retrospectively collected for QFR analysis. Based on QFR cut-off values of 0.77 and 0.86, our patient cohort was reclassified to 'no referral' (QFR ≥0.86), referral for 'FFR' (QFR 0.78-0.85), or 'direct PCI' (QFR ≤0.77). In total, 290 patients were included. Overall accuracy of QFR to detect an invasive FFR of ≤0.80 was 86%. Based on a QFR cut-off value of 0.86, a 50% reduction in patient referral for FFR could be obtained, while only 5% of these patients had an invasive FFR of ≤0.80 (thus, these patients were incorrectly reclassified to the 'no referral' group). Furthermore, 22% of the patients that still need to be referred could undergo direct PCI, based on a QFR cut-off value of 0.77. CONCLUSION: QFR is feasible to use for the selection of patients for FFR referral.

Automated contour detection in X-ray left ventricular angiograms using multiview active appearance models and dynamic programming.

This paper describes a new approach to the automated segmentation of X-ray left ventricular (LV) angiograms, based on active appearance models (AAMs) and dynamic programming. A coupling of shape and texture information between the end-diastolic (ED) and end-systolic (ES) frame was achieved by constructing a multiview AAM. Over-constraining of the model was compensated for by employing dynamic programming, integrating both intensity and motion features in the cost function. Two applications are compared: a semi-automatic method with manual model initialization, and a fully automatic algorithm. The first proved to be highly robust and accurate, demonstrating high clinical relevance. Based on experiments involving 70 patient data sets, the algorithm's success rate was 100% for ED and 99% for ES, with average unsigned border positioning errors of 0.68 mm for ED and 1.45 mm for ES. Calculated volumes were accurate and unbiased. The fully automatic algorithm, with intrinsically less user interaction was less robust, but showed a high potential, mostly due to a controlled gradient descent in updating the model parameters. The success rate of the fully automatic method was 91% for ED and 83% for ES, with average unsigned border positioning errors of 0.79 mm for ED and 1.55 mm for ES.

A new approach to contour detection in x-ray arteriograms: the wavecontour.

OBJECTIVES: We sought to develop a novel approach (the Wavecontour) for the detection of contours in vascular x-ray images, designed to eliminate any systematic underestimation or overestimation for vessel sizes in the range of 0.5 to 15 mm and further minimize the influence of the user-defined start points and end points. MATERIALS AND METHODS: This method is based on the Wavefront Propagation principle in a 2-stage approach. Two validation experiments were performed: a Plexiglas phantom study (tube sizes ranging from 0.51 to 9.9 mm) and an in vivo patient study (114 patients with various degrees of stenosis). RESULTS: The phantom study demonstrated an accuracy of 0.007 mm and a precision of 0.072 mm. The patient study showed a high similarity between the detected and the expert-drawn contours: 93% for a threshold of 1.0 pixel and 81% for a threshold of 0.5 pixels. Furthermore, the contours are robust in complex lesions and are almost independent in the middle part of the segment from the user-defined start point and end point. A variation of only 0.6 pixels exists in the middle 60% of the contours. CONCLUSIONS: Our new Wavecontour approach performs very well on phantom images as well as on clinical data over the whole range of 0.5 to 15 mm and results in more robust QCA/QVA analyses.