Comparison of endothelial shear stress between ultrathin strut bioresorbable polymer drug-eluting stent vs durable-polymer drug-eluting stent post-stent implantation: An optical coherence tomography substudy from BIOFLOW II.

BACKGROUND: Recent clinical data indicate a different performance of biodegradable polymer (BP)-drug eluting stent (DES) compared to durable polymer (DP)-DES. Whether this can be explained by a beneficial impact of BP-DES stent design on the local hemodynamic forces distribution remains unclear. OBJECTIVES: To compare endothelial shear stress (ESS) distribution after implantation of ultrathin (us) BP-DES and DP-DES and examine the association between ESS and neointimal thickness (NIT) distribution in the two devices at 9 months follow up. METHODS AND RESULTS: We retrospectively identified patients from the BIOFLOW II trial that had undergone OCT imaging. OCT data were utilized to reconstruct the surface of the stented segment at baseline and 9 months follow-up, simulate blood flow, and measure ESS and NIT in the stented segment. The patients were divided into 3 groups depending on whether DP-DES (N = 8, n = 56,160 sectors), BP-DES with a stent diameter of >3 mm (strut thickness of 80 µm, N = 6, n = 36,504 sectors), or BP-DES with a stent diameter of ≤3 mm (strut thickness of 60 µm, N = 8, n = 50,040 sectors) were used for treatment. The ESS, and NIT distribution and the association of these two variables were estimated and compared among the 3 groups. RESULTS: In the DP-DES group mean NIT was 0.18 ± 0.17 mm and ESS 1.68 ± 1.66 Pa; for the BP-DES ≤3 mm group the NIT was 0.17 ± 0.11 mm and ESS 1.49 ± 1.24 Pa and for the BP-DES >3 mm group 0.20 ± 0.23 mm and 1.42 ± 1.24 Pa respectively (p < 0.001 for both NIT and ESS comparisons across groups). A negative correlation between NIT and baseline ESS was found, the correlation coefficient for all the stented segments was -0.33, p < 0.001. CONCLUSION: In this OCT sub-study of the BIOFLOW II trial, the NIT was statistically different between groups of patients treated with BP-DES and DP-DES. In addition, regions of low ESS were associated with increased NIT in all studied devices.

Test-retest reliability of Bayesian estimations of the effects of stimulation, prior information and individual traits on pain perception.

BACKGROUND: There is inter-individual variability in the influence of different components (e.g. nociception and expectations) on pain perception. Identifying the individual effect of these components could serve for patient stratification, but only if these influences are stable in time. METHODS: In this study, 30 healthy participants underwent a cognitive pain paradigm in which they rated pain after viewing a probabilistic cue informing of forthcoming pain intensity and then receiving electrical stimulation. The trial information was then used in a Bayesian probability model to compute the relative weight each participant put on stimulation, cue, cue uncertainty and trait-like bias. The same procedure was repeated 2 weeks later. Relative and absolute test-retest reliability of all measures was assessed. RESULTS: Intraclass correlation results showed good reliability for the effect of the stimulation (0.83), the effect of the cue (0.75) and the trait-like bias (0.75 and 0.75), and a moderate reliability for the effect of the cue uncertainty (0.55). Absolute reliability measures also supported the temporal stability of the results and indicated that a change in parameters corresponding to a difference in pain ratings ranging between 0.47 and 1.45 (depending on the parameters) would be needed to consider differences in outcomes significant. The comparison of these measures with the closest clinical data we possess supports the reliability of our results. CONCLUSIONS: These findings support the hypothesis that inter-individual differences in the weight placed on different pain factors are stable in time and could therefore be a possible target for patient stratification. SIGNIFICANCE: Our results demonstrate the temporal stability of the weight healthy individuals place on the different factors leading to the pain response. These findings give validity to the idea of using Bayesian estimations of the influence of different factors on pain as a way to stratify patients for treatment personalization.

Advanced deep learning methodology for accurate, real-time segmentation of high-resolution intravascular ultrasound images.

AIMS: The aim of this study is to develop and validate a deep learning (DL) methodology capable of automated and accurate segmentation of intravascular ultrasound (IVUS) image sequences in real-time. METHODS AND RESULTS: IVUS segmentation was performed by two experts who manually annotated the external elastic membrane (EEM) and lumen borders in the end-diastolic frames of 197 IVUS sequences portraying the native coronary arteries of 65 patients. The IVUS sequences of 177 randomly-selected vessels were used to train and optimise a novel DL model for the segmentation of IVUS images. Validation of the developed methodology was performed in 20 vessels using the estimations of two expert analysts as the reference standard. The mean difference for the EEM, lumen and plaque area between the DL-methodology and the analysts was ≤0.23mm2 (standard deviation ≤0.85mm2), while the Hausdorff and mean distance differences for the EEM and lumen borders was ≤0.19 mm (standard deviation≤0.17 mm). The agreement between DL and experts was similar to experts' agreement (Williams Index ranges: 0.754-1.061) with similar results in frames portraying calcific plaques or side branches. CONCLUSIONS: The developed DL-methodology appears accurate and capable of segmenting high-resolution real-world IVUS datasets. These features are expected to facilitate its broad adoption and enhance the applications of IVUS in clinical practice and research.

Wall shear stress estimated by 3D-QCA can predict cardiovascular events in lesions with borderline negative fractional flow reserve.

BACKGROUND AND AIMS: There is some evidence of the implications of wall shear stress (WSS) derived from three-dimensional quantitative coronary angiography (3D-QCA) models in predicting adverse cardiovascular events. This study investigates the efficacy of 3D-QCA-derived WSS in detecting lesions with a borderline negative fractional flow reserve (FFR: 0.81-0.85) that progressed and caused events. METHODS: In this retrospective cohort study, we identified 548 patients who had at least one lesion with an FFR 0.81-0.85 and complete follow-up data; 293 lesions (286 patients) with suitable angiographic characteristics were reconstructed using a dedicated 3D-QCA software and included in the analysis. In the reconstructed models blood flow simulation was performed and the value of 3D-QCA variables and WSS distribution in predicting events was examined. The primary endpoint of the study was the composite of cardiac death, target lesion related myocardial infarction or clinically indicated target lesion revascularization. RESULTS: During a median follow-up of 49.4 months, 37 events were reported. Culprit lesions had a greater area stenosis [(AS), 66.1% (59.5-72.3) vs 54.8% (46.5-63.2), p<0.001], smaller minimum lumen area [(MLA), 1.66 mm2 (1.45-2.30) vs 2.10 mm2 (1.69-2.70), p=0.011] and higher maximum WSS [9.0 Pa (5.10-12.46) vs 5.0 Pa (3.37-7.54), p < 0.001] than those that remained quiescent. In multivariable analysis, AS [hazard ratio (HR): 1.06, 95% confidence interval (CI): 1.03-1.10, p=0.001] and maximum WSS (HR: 1.08, 95% CI: 1.02-1.14, p=0.012) were the only independent predictors of the primary endpoint. Lesions with an increased AS (≥58.6%) that were exposed to high WSS (≥7.69Pa) were more likely to progress and cause events (27.8%) than those with a low AS exposed to high WSS (7.4%) or those exposed to low WSS that had increased (12.8%) or low AS (2.7%, p<0.001). CONCLUSIONS: This study for the first time highlights the potential value of 3D-QCA-derived WSS in detecting, among lesions with a borderline negative FFR, those that cause cardiovascular events.

Diagnostic accuracy of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) estimated retrospectively by conventional radiation saving X-ray angiography.

BACKGROUND: Angiography derived FFR reveals good performance in assessing intermediate coronary stenosis. However, its performance under contemporary low X-ray frame and pulse rate settings is unknown. We aim to validate the feasibility and performance of quantitative flow ratio (QFR) and vessel fractional flow reserve (vFFR) under such angiograms. METHODS: This was an observational, retrospective, single center cohort study. 134 vessels in 102 patients, with angiograms acquired under 7.5fps and 7pps mode, were enrolled. QFR (fQFR and cQFR) and vFFR were validated with FFR as the gold standard. A conventional manual and a newly developed algorithmic exclusion method (M and A group) were both evaluated for identification of poor-quality angiograms. RESULTS: Good agreement between QFR/vFFR and FFR were observed in both M and A group, except for vFFR in the M group. The correlation coefficients between fQFR/cQFR/vFFR and FFR were 0.6242, 0.5888, 0.4089 in the M group, with rvFFR significantly lower than rfQFR (p = 0.0303), and 0.7055, 0.6793, 0.5664 in the A group, respectively. AUCs of detecting lesions with FFR ≤ 0.80 were 0.852 (95% CI 0.722-0.913), 0.858 (95% CI 0.778-0.917), 0.682 (95% CI 0.586-0.768), for fQFR/cQFR/vFFR in the M group, while vFFR performed poorer than fQFR (p = 0.0063) and cQFR (p = 0.0054). AUCs were 0.898 (95% CI 0.811-0.945), 0.892 (95% CI 0.803-0.949), 0.843 (95% CI 0.746-0.914) for fQFR/cQFR/vFFR in the A group. AUCvFFR was significantly higher in the A group than that in the M group (p = 0.0399). CONCLUSIONS: QFR/vFFR assessment is feasible under 7.5fps and 7pps angiography, where cQFR showed no advantage compared to fQFR. Our newly developed algorithmic exclusion method could be a better method of selecting angiograms with adequate quality for angiography derived FFR assessment.

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.

Computerised Methodologies for Non-Invasive Angiography-Derived Fractional Flow Reserve Assessment: A Critical Review.

Fractional flow reserve is the gold standard for assessing the haemodynamic significance of intermediate coronary artery stenoses. Cumulative evidence has shown that FFR-guided revascularisation reduces stent implantations and improves patient outcomes. However, despite the wealth of evidence and guideline recommendations, its use in clinical practice remains minimal. Patient and technical limitations of FFR as well as the need for intracoronary instrumentation, use of adenosine, and increased costs have limited FFR's applicability in clinical practice. Over the last decade, several angiography-derived FFR software packages have been developed which do not require intracoronary pressure assessment with a guidewire or need for administration of hyperaemic agents. At present, there are 3 commercially available software packages and several other non-commercial technologies that have been described in the literature. These technologies have been validated against invasive FFR showing good accuracy and correlation. However, the methodology behind these solutions is different-some algorithms are based on solving the governing equations of fluid dynamics such as the Navier-Stokes equation while others have opted for a more simplified mathematical formula approach. The aim of this review is to critically appraise the methodology behind all the known angiography-derived FFR technologies highlighting the key differences and limitations.

Evaluation of the Efficacy of Computed Tomographic Coronary Angiography in Assessing Coronary Artery Morphology and Physiology: Rationale and Study Design.

Computed tomographic coronary angiography (CTCA) is a non-invasive imaging modality, which allows plaque burden and composition assessment and detection of plaque characteristics associated with increased vulnerability. In addition, CTCA-based coronary artery reconstruction enables local haemodynamic forces assessment, which regulate plaque formation and vascular inflammation and prediction of lesions that are prone to progress and cause events. However, the use of CTCA for vulnerable plaque detection in the clinical arena remains limited. To unlock the full potential of CTCA and enable its broad use, further work is needed to develop user-friendly processing tools that will allow fast and accurate analysis of CTCA, computational fluid dynamic modelling, and evaluation of the local haemodynamic forces. The present study aims to develop a seamless platform that will overcome the limitations of CTCA and enable fast and accurate evaluation of plaque morphology and physiology. We will analyse imaging data from 70 patients with coronary artery disease who will undergo state-of-the-art CTCA and near-infrared spectroscopy-intravascular ultrasound imaging and develop and train algorithms that will take advantage of the intravascular imaging data to optimise vessel segmentation and plaque characterisation. Furthermore, we will design an advanced module that will enable reconstruction of coronary artery anatomy from CTCA, blood flow simulation, shear stress estimation, and comprehensive visualisation of vessel pathophysiology. These advances are expected to facilitate the broad use of CTCA, not only for risk stratification but also for the evaluation of the effect of emerging therapies on plaque evolution.

The Evolution of Data Fusion Methodologies Developed to Reconstruct Coronary Artery Geometry From Intravascular Imaging and Coronary Angiography Data: A Comprehensive Review.

Understanding the mechanisms that regulate atherosclerotic plaque formation and evolution is a crucial step for developing treatment strategies that will prevent plaque progression and reduce cardiovascular events. Advances in signal processing and the miniaturization of medical devices have enabled the design of multimodality intravascular imaging catheters that allow complete and detailed assessment of plaque morphology and biology. However, a significant limitation of these novel imaging catheters is that they provide two-dimensional (2D) visualization of the lumen and vessel wall and thus they cannot portray vessel geometry and 3D lesion architecture. To address this limitation computer-based methodologies and user-friendly software have been developed. These are able to off-line process and fuse intravascular imaging data with X-ray or computed tomography coronary angiography (CTCA) to reconstruct coronary artery anatomy. The aim of this review article is to summarize the evolution in the field of coronary artery modeling; we thus present the first methodologies that were developed to model vessel geometry, highlight the modifications introduced in revised methods to overcome the limitations of the first approaches and discuss the challenges that need to be addressed, so these techniques can have broad application in clinical practice and research.

Predictive value of the QFR in detecting vulnerable plaques in non-flow limiting lesions: a combined analysis of the PROSPECT and IBIS-4 study.

Studies have shown that the quantitative flow ratio (QFR), recently introduced to assess lesion severity from coronary angiography, provides useful prognostic information; however the additive value of this technique over intravascular imaging in detecting lesions that are likely to cause events is yet unclear. We analysed data acquired in the PROSPECT and IBIS-4 studies, in particular the baseline virtual histology-intravascular ultrasound (VH-IVUS) and angiographic data from 17 non-culprit lesions with a presumable vulnerable phenotype (i.e., thin or thick cap fibroatheroma) that caused major adverse cardiac events or required revascularization (MACE) at 5-year follow-up and from a group of 78 vulnerable plaques that remained quiescent. The segments studied by VH-IVUS were identified in coronary angiography and the QFR was estimated. The additive value of 3-dimensional quantitative coronary angiography (3D-QCA) and of the QFR in predicting MACE at 5 year follow-up beyond plaque characteristics was examined. It was found that MACE lesions had a greater plaque burden (PB) and smaller minimum lumen area (MLA) on VH-IVUS, a longer length and a smaller minimum lumen diameter (MLD) on 3D-QCA and a lower QFR compared with lesions that remained quiescent. By univariate analysis MLA, PB, MLD, lesion length on 3D-QCA and QFR were predictors of MACE. In multivariate analysis a low but normal QFR (> 0.80 to < 0.97) was the only independent prediction of MACE (HR 3.53, 95% CI 1.16-10.75; P = 0.027). In non-flow limiting lesions with a vulnerable phenotype, QFR may provide additional prognostic information beyond plaque morphology for predicting MACE throughout 5 years.