Rapid Plaque Progression Is Independently Associated With Hyperglycemia and Low HDL Cholesterol in Patients With Stable Coronary Artery Disease: A PARADIGM Study.

BACKGROUND: We assessed whether combinations of cardiometabolic risk factors independently predict coronary plaque progression (PP) and major adverse cardiovascular events in patients with stable coronary artery disease. METHODS: Patients with known or suspected stable coronary artery disease (60.9±9.3 years, 55.4% male) undergoing serial coronary computed tomography angiographies (≥2 years apart), with clinical characterization and follow-up (N=1200), were analyzed from the PARADIGM study (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging). Plaque volumes measured in coronary segments (≥2 mm in diameter) were summed to provide whole heart plaque volume (mm3) and percent atheroma volume (plaque volume/vessel volume×100; %) per patient at baseline and follow-up. Rapid PP was defined as a percent atheroma volume increase of ≥1.0%/y. Major adverse cardiovascular events included nonfatal myocardial infarction, death, and unplanned coronary revascularization. RESULTS: In an interscan period of 3.2 years (interquartile range, 1.9), rapid PP occurred in 341 patients (28%). At multivariable analysis, the combination of cardiometabolic risk factors defined as metabolic syndrome predicted rapid PP (odds ratio, 1.51 [95% CI, 1.12-2.03]; P=0.007) together with older age, smoking habits, and baseline percent atheroma volume. Among single cardiometabolic variables, high fasting plasma glucose (diabetes or fasting plasma glucose >100 mg/dL) and low HDL-C (high-density lipoprotein cholesterol; <40 mg/dL in males and <50 mg/dL in females) were independently associated with rapid PP, in particular when combined (odds ratio, 2.37 [95% CI, 1.56-3.61]; P<0.001). In a follow-up of 8.23 years (interquartile range, 5.92-9.53), major adverse cardiovascular events occurred in 201 patients (17%). At multivariable Cox analysis, the combination of high fasting plasma glucose with high systemic blood pressure (treated hypertension or systemic blood pressure >130/85 mm Hg) was an independent predictor of events (hazard ratio, 1.79 [95% CI, 1.10-2.90]; P=0.018) together with family history, baseline percent atheroma volume, and rapid PP. CONCLUSIONS: In patients with stable coronary artery disease, the combination of hyperglycemia with low HDL-C is associated with rapid PP independently of other risk factors, baseline plaque burden, and treatment. The combination of hyperglycemia with high systemic blood pressure independently predicts the worse outcome beyond PP. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02803411.

Epicardial adipose tissue attenuation on computed tomography in women with coronary microvascular dysfunction: A pilot, hypothesis generating study.

BACKGROUND: Patients with myocardial ischemia without obstructive coronary artery disease often have coronary microvascular dysfunction (CMD) and associated increased risk of cardiovascular (CV) events and anginal hospitalizations. Epicardial adipose tissue (EAT) covers much of the myocardium and coronary arteries and when dysfunctional, secretes proinflammatory cytokines and is associated with CV events. While oxidative stress and systemic inflammation are associated with CMD, the relationship between EAT and CMD in women is not well known. METHODS: Women diagnosed with CMD (n = 21) who underwent coronary computed tomography with coronary artery calcium (CAC) scoring were compared to a reference group (RG) of women referred for CAC screening for preventive risk assessment (n = 181). EAT attenuation (Hounsfield units (HU)) was measured adjacent to the proximal right coronary artery, along with subcutaneous adipose tissue (SCAT). Two-sample t-tests with unequal variances were utilized. RESULTS: Mean age of the CMD group was 56 ± 8 years and body mass index (BMI) was 31.6 ± 6.8 kg/m2. CV risk factors in the CMD group were prevalent: 67 % hypertension, 44 % hyperlipidemia, and 33 % diabetes. Both CMD and RG had similar CAC score (25.86 ± 59.54 vs. 24.17 ± 104.6; p = 0.21. In the CMD group, 67 % had a CAC of 0. Minimal atherosclerosis (CAD-RADS 1) was present in 76 % of women with CMD. The CMD group had lower EAT attenuation than RG (-103.3 ± 6.33 HU vs. -97.9 ± 8.3 HU, p = 0.009, respectively). There were no differences in SCAT attenuation. Hypertension, smoking history, age, BMI, and CAC score did not correlate with EAT in either of the groups. CONCLUSIONS: Women with CMD have decreased EAT attenuation compared to RG women. EAT-mediated inflammation and changes in vascular tone may be a mechanistic contributor to abnormal microvascular reactivity. Clinical trials testing therapeutic strategies to decrease EAT may be warranted in the management of CMD.

Optical Coherence Tomography-Based Functional Stenosis Assessment: FUSION-A Prospective Multicenter Trial.

BACKGROUND: Intravascular imaging and intracoronary physiology may both be used to guide and optimize percutaneous coronary intervention; however, they are rarely used together. The virtual flow reserve (VFR) is an optical coherence tomography (OCT)-based model of fractional flow reserve (FFR) facilitating the assessment of the physiological significance of coronary lesions. We aimed to validate the VFR assessment of intermediate coronary artery stenoses. METHODS: FUSION (Validation of OCT-Based Functional Diagnosis of Coronary Stenosis) was a multicenter, prospective, observational study comparing OCT-derived VFR to invasive FFR. VFR was mathematically derived from a lumped parameter flow model based on 3-dimensional lumen morphology. Patients undergoing coronary angiography with intermediate angiographic stenosis (40%-90%) requiring physiological assessment were enrolled. Investigational sites were blinded to the VFR analysis, and all OCT and FFR data were reviewed by an independent core laboratory. The coprimary end points were the sensitivity and specificity of VFR against FFR as the reference standard, each of which was tested against prespecified performance goals. RESULTS: After core laboratory review, 266 vessels in 224 patients from 25 US centers were included in the analysis. The mean angiographic diameter stenosis was 65.5%±14.9%, and the mean FFR was 0.83±0.11. Overall accuracy, sensitivity, and specificity of VFR versus FFR using a binary cutoff point of 0.80 were 82.0%, 80.4%, and 82.9%, respectively. The 97.5% lower confidence bound met the prespecified performance goal for sensitivity (71.6% versus 70%; P=0.01) and specificity (76.6% versus 75%; P=0.01). The area under the curve was 0.88 (95% CI, 0.84-0.92; P<0.0001). CONCLUSIONS: OCT-derived VFR demonstrates high sensitivity and specificity for predicting invasive FFR. Integrating high-resolution intravascular imaging with imaging-derived physiology may provide synergistic benefits as an adjunct to percutaneous coronary intervention. REGISTRATION: URL: https://clinicaltrials.gov; Unique identifier: NCT04356027.

Prediction of the development of new coronary atherosclerotic plaques with radiomics.

BACKGROUND: Radiomics is expected to identify imaging features beyond the human eye. We investigated whether radiomics can identify coronary segments that will develop new atherosclerotic plaques on coronary computed tomography angiography (CCTA). METHODS: From a prospective multinational registry of patients with serial CCTA studies at ≥ 2-year intervals, segments without identifiable coronary plaque at baseline were selected and radiomic features were extracted. Cox models using clinical risk factors (Model 1), radiomic features (Model 2) and both clinical risk factors and radiomic features (Model 3) were constructed to predict the development of a coronary plaque, defined as total PV â€‹≥ â€‹1 â€‹mm3, at follow-up CCTA in each segment. RESULTS: In total, 9583 normal coronary segments were identified from 1162 patients (60.3 â€‹± â€‹9.2 years, 55.7% male) and divided 8:2 into training and test sets. At follow-up CCTA, 9.8% of the segments developed new coronary plaque. The predictive power of Models 1 and 2 was not different in both the training and test sets (C-index [95% confidence interval (CI)] of Model 1 vs. Model 2: 0.701 [0.690-0.712] vs. 0.699 [0.0.688-0.710] and 0.696 [0.671-0.725] vs. 0.0.691 [0.667-0.715], respectively, all p â€‹> â€‹0.05). The addition of radiomic features to clinical risk factors improved the predictive power of the Cox model in both the training and test sets (C-index [95% CI] of Model 3: 0.772 [0.762-0.781] and 0.767 [0.751-0.787], respectively, all p â€‹< â€‹00.0001 compared to Models 1 and 2). CONCLUSION: Radiomic features can improve the identification of segments that would develop new coronary atherosclerotic plaque. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT0280341.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Comparative Healthcare Resource Utilization of Percutaneous Mechanical Circulatory Support Using Impella Versus Intra-aortic Balloon Pump Use for Patients With Acute Coronary Syndrome and Cardiogenic Shock Undergoing Percutaneous Coronary Interventions: Insights From National Inpatient Sample.

The use of percutaneous mechanical circulatory support (MCS) devices, including Impella and Intra-aortic balloon pump (IABP), in patients with cardiogenic shock has increased in recent times. We aimed to evaluate the impact of the choice of an MCS device on healthcare resource utilization. We queried the National Inpatient Sample registry between October 2016 and December 2018 to identify adults admitted for acute coronary syndrome-related cardiogenic shock and who received percutaneous coronary intervention (PCI). The study population was segregated into Impella and IABP groups using ICD 10 diagnosis codes. The primary endpoint was high healthcare resource utilization (HRU), while secondary outcomes included periprocedural complications. Propensity scoring matching was used to determine which patients in the Impella cohort had similar health to IABP patients. During the study period, 439,610 patients were admitted who received hemodynamic support using, Impella or IABP on account of acute coronary syndrome complicated by cardiogenic shock (CS). The median age (years) of the Impella cohort and IABP cohorts were similar (64.1 vs 65.1, P = 0.08). Gender distribution of the Impella CS patients was like IABP patients with female majorities in both groups, (71.9% vs 67.9%, P = 0.05). Impella CS patients had a higher representation of those with hypertension (P = 0.002), smoking (P = 0.040), obesity (P = 0.034), diabetes mellitus (P = 0.009), CHF (P = 0.030), COPD (P = 0.034), chronic liver disease (P = 0.028), and chronic kidney disease (P = 0.031). 1:1 Propensity score matching identified 2620 Impella patients' comparable severity index with the IABP patients. Patients with hemodynamic support using Impella had higher healthcare resource utilization, (HRU), the surrogate of length of stay (LOS) ≥7 or nonhome disposition at discharge, when compared with those with IABP (57.41% vs 42.76%, P < 0.0001). Impella CS patients had higher in-hospital mortality as compared to the IABP patients (55.45% vs 45.86%, P < 0.0001). Impella CS patients developed more periprocedural complications, including vascular injury (4.8% vs 1.4%, P < 0.0001), acute kidney injury (58.36% vs 41.64%, P < 0.0001), end-stage renal disease requiring dialysis (8.75% vs 1.25%, P = 0.002) when compared to the IABP patients. Among patients with ACS undergoing PCI and receiving MCS devices, those receiving Impella demonstrated higher healthcare resource utilization, higher LOS ≥7 days, and more nonhome disposition at discharge compared to patients receiving IABP. Further investigation is warranted to elucidate factors associated with these findings.

Changes in post-PCI physiology based on anatomical vessel location: a DEFINE PCI substudy.

BACKGROUND: Anatomical vessel location affects post-percutaneous coronary intervention (PCI) physiology. AIMS: We aimed to compare the post-PCI instantaneous wave-free ratio (iFR) in left anterior descending (LAD) versus non-LAD vessels and to identify the factors associated with a suboptimal post-PCI iFR. METHODS: DEFINE PCI was a multicentre, prospective, observational study in which a blinded post-PCI iFR pullback was used to assess residual ischaemia following angiographically successful PCI. RESULTS: Pre- and post-PCI iFR recordings of 311 LAD and 195 non-LAD vessels were compared. Though pre-PCI iFR in the LAD vessels (median 0.82 [0.63, 0.86]) were higher compared with those in non-LAD vessels (median 0.72 [0.49, 0.84]; p<0.0001), post-PCI iFR were lower in the LAD vessels (median 0.92 [0.88, 0.94] vs 0.98 [0.95, 1.00]; p<0.0001). The prevalence of a suboptimal post-PCI iFR of <0.95 was higher in the LAD vessels (77.8% vs 22.6%; p<0.0001). While the overall frequency of residual physiological diffuse disease (31.4% vs 38.6%; p=0.26) and residual focal disease in the non-stented segment (49.6% vs 50.0%; p=0.99) were similar in both groups, residual focal disease within the stented segment was more common in LAD versus non-LAD vessels (53.7% vs 27.3%; p=0.0009). Improvement in iFR from pre- to post-PCI was associated with angina relief regardless of vessel location. CONCLUSIONS: After angiographically successful PCI, post-PCI iFR is lower in the LAD compared with non-LAD vessels, resulting in a higher prevalence of suboptimal post-PCI iFR in LAD vessels. This difference is, in part, due to a greater frequency of a residual focal pressure gradient within the stented segment which may be amenable to more aggressive PCI.

Artificial Intelligence, Computational Simulations, and Extended Reality in Cardiovascular Interventions.

Artificial intelligence, computational simulations, and extended reality, among other 21st century computational technologies, are changing the health care system. To collectively highlight the most recent advances and benefits of artificial intelligence, computational simulations, and extended reality in cardiovascular therapies, we coined the abbreviation AISER. The review particularly focuses on the following applications of AISER: 1) preprocedural planning and clinical decision making; 2) virtual clinical trials, and cardiovascular device research, development, and regulatory approval; and 3) education and training of interventional health care professionals and medical technology innovators. We also discuss the obstacles and constraints associated with the application of AISER technologies, as well as the proposed solutions. Interventional health care professionals, computer scientists, biomedical engineers, experts in bioinformatics and visualization, the device industry, ethics committees, and regulatory agencies are expected to streamline the use of AISER technologies in cardiovascular interventions and medicine in general.

How early can atherosclerosis be detected by coronary CT angiography? Insights from quantitative CT analysis of serial scans in the PARADIGM trial.

BACKGROUND: Non-obstructing small coronary plaques may not be well recognized by expert readers during coronary computed tomography angiography (CCTA) evaluation. Recent developments in atherosclerosis imaging quantitative computed tomography (AI-QCT) enabled by machine learning allow for whole-heart coronary phenotyping of atherosclerosis, but its diagnostic role for detection of small plaques on CCTA is unknown. METHODS: We performed AI-QCT in patients who underwent serial CCTA in the multinational PARADIGM study. AI-QCT results were verified by a level III experienced reader, who was blinded to baseline and follow-up status of CCTA. This retrospective analysis aimed to characterize small plaques on baseline CCTA and evaluate their serial changes on follow-up imaging. Small plaques were defined as a total plaque volume <50 â€‹mm3. RESULTS: A total of 99 patients with 502 small plaques were included. The median total plaque volume was 6.8 â€‹mm3 (IQR 3.5-13.9 â€‹mm3), most of which was non-calcified (median 6.2 â€‹mm3; 2.9-12.3 â€‹mm3). The median age at the time of baseline CCTA was 61 years old and 63% were male. The mean interscan period was 3.8 â€‹± â€‹1.6 years. On follow-up CCTA, 437 (87%) plaques were present at the same location as small plaques on baseline CCTA; 72% were larger and 15% decreased in volume. The median total plaque volume and non-calcified plaque volume increased to 18.9 â€‹mm3 (IQR 8.3-45.2 â€‹mm3) and 13.8 â€‹mm3 (IQR 5.7-33.4 â€‹mm3), respectively, among plaques that persisted on follow-up CCTA. Small plaques no longer visualized on follow-up CCTA were significantly more likely to be of lower volume, shorter in length, non-calcified, and more distal in the coronary artery, as compared with plaques that persisted at follow-up. CONCLUSION: In this retrospective analysis from the PARADIGM study, small plaques (<50 â€‹mm3) identified by AI-QCT persisted at the same location and were often larger on follow-up CCTA.

Differential predictability for high-risk plaque characteristics between fractional flow reserve and instantaneous wave-free ratio.

To evaluate the differential associations of high-risk plaque characteristics (HRPC) with resting or hyperemic physiologic indexes (instantaneous wave-free ratio [iFR] or fractional flow reserve [FFR]), a total of 214 vessels from 127 patients with stable angina or acute coronary syndrome who underwent coronary computed tomography angiography (CCTA) and invasive physiologic assessment were investigated. HPRC were classified into quantitative (minimal luminal area < 4 mm2 or plaque burden ≥ 70%) and qualitative features (low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification). Vessels with FFR ≤ 0.80 or iFR ≤ 0.89 had significantly higher proportions of HRPC than those with FFR > 0.80 or iFR > 0.89, respectively. FFR was independently associated with both quantitative and qualitative HRPC, but iFR was only associated with quantitative HRPC. Both FFR and iFR were significantly associated with the presence of ≥ 3 HRPC, and FFR demonstrated higher discrimination ability than iFR (AUC 0.703 vs. 0.648, P = 0.045), which was predominantly driven by greater discriminating ability of FFR for quantitative HRPC (AUC 0.832 vs. 0.744, P = 0.005). In conclusion, both FFR and iFR were significantly associated with CCTA-derived HRPC. Compared with iFR, however, FFR was independently associated with the presence of qualitative HRPC and showed a higher predictive ability for the presence of ≥ 3 HRPC.

Effects of renin-angiotensin-aldosterone-system inhibitors on coronary atherosclerotic plaques: The PARADIGM registry.

BACKGROUND AND AIMS: Inhibition of Renin-Angiotensin-Aldosterone-System (RAAS) has been hypothesized to improve endothelial function and reduce plaque inflammation, however, their impact on the progression of coronary atherosclerosis is unclear. We aim to study the effects of RAAS inhibitor on plaque progression and composition assessed by serial coronary CT angiography (CCTA). METHODS: We performed a prospective, multinational study consisting of a registry of patients without history of CAD, who underwent serial CCTAs. Patients using RAAS inhibitors were propensity matched to RAAS inhibitor naïve patients based on clinical and CCTA characteristics at baseline. Atherosclerotic plaques in CCTAs were quantitatively analyzed for percent atheroma volume (PAV) according to plaque composition. Interactions between RAAS inhibitor use and baseline PAV on plaque progression were assessed in the unmatched cohort using a multivariate linear regression model. RESULTS: Of 1248 patients from the registry, 299 RAAS inhibitor taking patients were matched to 299 RAAS inhibitor naïve patients. Over a mean interval of 3.9 years, there was no significant difference in annual progression of total PAV between RAAS inhibitor naïve vs taking patients (0.75 vs 0.79%/year, p = 0.66). With interaction testing in the unmatched cohort, however, RAAS inhibitor use was significantly associated with lower non-calcified plaque progression (Beta coefficient -0.100, adjusted p = 0.038) with higher levels of baseline PAV. CONCLUSIONS: The use of RAAS inhibitors over a period of nearly 4 years did not significantly impact on total atherosclerotic plaque progression or various plaque components. However, interaction testing to assess the differential effect of RAAS inhibition based on baseline PAV suggested a significant decrease in progression of non-calcified plaque in patients with a higher burden of baseline atherosclerosis, which should be considered hypothesis generating.

Impact of statins based on high-risk plaque features on coronary plaque progression in mild stenosis lesions: results from the PARADIGM study.

AIMS: To investigate the impact of statins on plaque progression according to high-risk coronary atherosclerotic plaque (HRP) features and to identify predictive factors for rapid plaque progression in mild coronary artery disease (CAD) using serial coronary computed tomography angiography (CCTA). METHODS AND RESULTS: We analyzed mild stenosis (25-49%) CAD, totaling 1432 lesions from 613 patients (mean age, 62.2 years, 63.9% male) and who underwent serial CCTA at a ≥2 year inter-scan interval using the Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging (NCT02803411) registry. The median inter-scan period was 3.5 ± 1.4 years; plaques were quantitatively assessed for annualized percent atheroma volume (PAV) and compositional plaque volume changes according to HRP features, and the rapid plaque progression was defined by the ≥90th percentile annual PAV. In mild stenotic lesions with ≥2 HRPs, statin therapy showed a 37% reduction in annual PAV (0.97 ± 2.02 vs. 1.55 ± 2.22, P = 0.038) with decreased necrotic core volume and increased dense calcium volume compared to non-statin recipient mild lesions. The key factors for rapid plaque progression were ≥2 HRPs [hazard ratio (HR), 1.89; 95% confidence interval (CI), 1.02-3.49; P = 0.042], current smoking (HR, 1.69; 95% CI 1.09-2.57; P = 0.017), and diabetes (HR, 1.55; 95% CI, 1.07-2.22; P = 0.020). CONCLUSION: In mild CAD, statin treatment reduced plaque progression, particularly in lesions with a higher number of HRP features, which was also a strong predictor of rapid plaque progression. Therefore, aggressive statin therapy might be needed even in mild CAD with higher HRPs. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT02803411.

Stent underexpansion is associated with high wall shear stress: a biomechanical analysis of the shear stent study.

Coronary stent underexpansion is associated with restenosis and stent thrombosis. In clinical studies of atherosclerosis, high wall shear stress (WSS) has been associated with activation of prothrombotic pathways, upregulation of matrix metalloproteinases, and future myocardial infarction. We hypothesized that stent underexpansion is predictive of high WSS. WSS distribution was investigated in patients enrolled in the prospective randomized controlled study of angulated coronary arteries randomized to undergo percutaneous coronary intervention with R-ZES or X-EES. WSS was calculated from 3D reconstructions of arteries from intravascular ultrasound (IVUS) and angiography using computational fluid dynamics. A logistic regression model investigated the relationship between WSS and underexpansion and the relationship between underexpansion and stent platform. Mean age was 63±11, 78% were male, 35% had diabetes, mean pre-stent angulation was 36.7°±14.7°. Underexpansion was assessed in 83 patients (6,181 IVUS frames). Frames with stent underexpansion were significantly more likely to exhibit high WSS (> 2.5 Pa) compared to those without underexpansion with an OR of 2.197 (95% CI = [1.233-3.913], p = 0.008). There was no significant association between underexpansion and low WSS (< 1.0 Pa) and no significant differences in underexpansion between R-ZES and X-EES. In the Shear Stent randomized controlled study, underexpanded IVUS frames were more than twice as likely to be associated with high WSS than frames without underexpansion.

Endothelial shear stress computed from coronary computed tomography angiography: A direct comparison to intravascular ultrasound.

INTRODUCTION: Intravascular ultrasound (IVUS) studies have shown that biomechanical variables, particularly endothelial shear stress (ESS), add synergistic prognostic insight when combined with anatomic high-risk plaque features. Non-invasive risk assessment of coronary plaques with coronary computed tomography angiography (CCTA) would be helpful to enable broad population risk-screening. AIM: To compare the accuracy of ESS computation of local ESS metrics by CCTA vs IVUS imaging. METHODS: We analyzed 59 patients from a registry of patients who underwent both IVUS and CCTA for suspected CAD. CCTA images were acquired using either a 64- or 256-slice scanner. Lumen, vessel, and plaque areas were segmented from both IVUS and CCTA (59 arteries, 686 3-mm segments). Images were co-registered and used to generate a 3-D arterial reconstruction, and local ESS distribution was assessed by computational fluid dynamics (CFD) and reported in consecutive 3-mm segments. RESULTS: Anatomical plaque characteristics (vessel, lumen, plaque area and minimal luminal area [MLA] per artery) were correlated when measured with IVUS and CCTA: 12.7 â€‹± â€‹4.3 vs 10.7 â€‹± â€‹4.5 â€‹mm2, r â€‹= â€‹0.63; 6.8 â€‹± â€‹2.7 vs 5.6 â€‹± â€‹2.7 â€‹mm2, r â€‹= â€‹0.43; 5.9 â€‹± â€‹2.9 vs 5.1 â€‹± â€‹3.2 â€‹mm2, r â€‹= â€‹0.52; 4.5 â€‹± â€‹1.3 vs 4.1 â€‹± â€‹1.5 â€‹mm2, r â€‹= â€‹0.67 respectively. ESS metrics of local minimal, maximal, and average ESS were also moderately correlated when measured with IVUS and CCTA (2.0 â€‹± â€‹1.4 vs 2.5 â€‹± â€‹2.6 â€‹Pa, r â€‹= â€‹0.28; 3.3 â€‹± â€‹1.6 vs 4.2 â€‹± â€‹3.6 â€‹Pa, r â€‹= â€‹0.42; 2.6 â€‹± â€‹1.5 vs 3.3 â€‹± â€‹3.0 â€‹Pa, r â€‹= â€‹0.35, respectively). CCTA-based computation accurately identified the spatial localization of local ESS heterogeneity compared to IVUS, with Bland-Altman analyses indicating that the absolute ESS differences between the two CCTA methods were pathobiologically minor. CONCLUSION: Local ESS evaluation by CCTA is possible and similar to IVUS; and is useful for identifying local flow patterns that are relevant to plaque development, progression, and destabilization.

Clinical and Coronary Plaque Predictors of Atherosclerotic Nonresponse to Statin Therapy.

BACKGROUND: Statins reduce the incidence of major cardiovascular events, but residual risk remains. The study examined the determinants of atherosclerotic statin nonresponse. OBJECTIVES: This study aimed to investigate factors associated with statin nonresponse-defined atherosclerosis progression in patients treated with statins. METHODS: The multicenter PARADIGM (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging) registry included patients who underwent serial coronary computed tomography angiography ≥2 years apart, with whole-heart coronary tree quantification of vessel, lumen, and plaque, and matching of baseline and follow-up coronary segments and lesions. Patients with statin use at baseline and follow-up coronary computed tomography angiography were included. Atherosclerotic statin nonresponse was defined as an absolute increase in percent atheroma volume (PAV) of 1.0% or more per year. Furthermore, a secondary endpoint was defined by the additional requirement of progression of low-attenuation plaque or fibro-fatty plaque. RESULTS: The authors included 649 patients (age 62.0 ± 9.0 years, 63.5% male) on statin therapy and 205 (31.5%) experienced atherosclerotic statin nonresponse. Age, diabetes, hypertension, and all atherosclerotic plaque features measured at baseline scan (high-risk plaque [HRP] features, calcified and noncalcified PAV, and lumen volume) were significantly different between patients with and without atherosclerotic statin nonresponse, whereas only diabetes, number of HRP features, and noncalcified and calcified PAV were independently associated with atherosclerotic statin nonresponse (odds ratio [OR]: 1.41 [95% CI: 0.95-2.11], OR: 1.15 [95% CI: 1.09-1.21], OR: 1.06 [95% CI: 1.02-1.10], OR: 1.07 [95% CI: 1.03-1.12], respectively). For the secondary endpoint (N = 125, 19.2%), only noncalcified PAV and number of HRP features were the independent determinants (OR: 1.08 [95% CI: 1.03-1.13] and OR: 1.21 [95% CI: 1.06-1.21], respectively). CONCLUSIONS: In patients treated with statins, baseline plaque characterization by plaque burden and HRP is associated with atherosclerotic statin nonresponse. Patients with the highest plaque burden including HRP were at highest risk for plaque progression, despite statin therapy. These patients may need additional therapies for further risk reduction.

Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.

BACKGROUND AND HYPOTHESIS: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. METHODS: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. RESULTS: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. CONCLUSIONS: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.

Combining IVUS + OCT Data, Biomechanical Models and Machine Learning Method for Accurate Coronary Plaque Morphology Quantification and Cap Thickness and Stress/Strain Index Predictions.

Assessment and prediction of vulnerable plaque progression and rupture risk are of utmost importance for diagnosis, management and treatment of cardiovascular diseases and possible prevention of acute cardiovascular events such as heart attack and stroke. However, accurate assessment of plaque vulnerability assessment and prediction of its future changes require accurate plaque cap thickness, tissue component and structure quantifications and mechanical stress/strain calculations. Multi-modality intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography image data with follow-up were acquired from ten patients to obtain accurate and reliable plaque morphology for model construction. Three-dimensional thin-slice finite element models were constructed for 228 matched IVUS + OCT slices to obtain plaque stress/strain data for analysis. Quantitative plaque cap thickness and stress/strain indices were introduced as substitute quantitative plaque vulnerability indices (PVIs) and a machine learning method (random forest) was employed to predict PVI changes with actual patient IVUS + OCT follow-up data as the gold standard. Our prediction results showed that optimal prediction accuracies for changes in cap-PVI (C-PVI), mean cap stress PVI (meanS-PVI) and mean cap strain PVI (meanSn-PVI) were 90.3% (AUC = 0.877), 85.6% (AUC = 0.867) and 83.3% (AUC = 0.809), respectively. The improvements in prediction accuracy by the best combination predictor over the best single predictor were 6.6% for C-PVI, 10.0% for mean S-PVI and 8.0% for mean Sn-PVI. Our results demonstrated the potential using multi-modality IVUS + OCT image to accurately and efficiently predict plaque cap thickness and stress/strain index changes. Combining mechanical and morphological predictors may lead to better prediction accuracies.

Automated finite element approach to generate anatomical patient-specific biomechanical models of atherosclerotic arteries from virtual histology-intravascular ultrasound.

Despite advancements in early detection and treatment, atherosclerosis remains the leading cause of death across all cardiovascular diseases (CVD). Biomechanical analysis of atherosclerotic lesions has the potential to reveal biomechanically instable or rupture-prone regions. Treatment decisions rarely consider the biomechanics of the stenosed lesion due in-part to difficulties in obtaining this information in a clinical setting. Previous 3D FEA approaches have incompletely incorporated the complex curvature of arterial geometry, material heterogeneity, and use of patient-specific data. To address these limitations and clinical need, herein we present a user-friendly fully automated program to reconstruct and simulate the wall mechanics of patient-specific atherosclerotic coronary arteries. The program enables 3D reconstruction from patient-specific data with heterogenous tissue assignment and complex arterial curvature. Eleven arteries with coronary artery disease (CAD) underwent baseline and 6-month follow-up angiographic and virtual histology-intravascular ultrasound (VH-IVUS) imaging. VH-IVUS images were processed to remove background noise, extract VH plaque material data, and luminal and outer contours. Angiography data was used to orient the artery profiles along the 3D centerlines. The resulting surface mesh is then resampled for uniformity and tetrahedralized to generate the volumetric mesh using TetGen. A mesh convergence study revealed edge lengths between 0.04 mm and 0.2 mm produced constituent volumes that were largely unchanged, hence, to save computational resources, a value of 0.2 mm was used throughout. Materials are assigned and finite element analysis (FEA) is then performed to determine stresses and strains across the artery wall. In a representative artery, the highest average effective stress was in calcium elements with 235 kPa while necrotic elements had the lowest average stress, reaching as low as 0.79 kPa. After applying nodal smoothening, the maximum effective stress across 11 arteries remained below 288 kPa, implying biomechanically stable plaques. Indeed, all atherosclerotic plaques remained unruptured at the 6-month longitudinal follow up diagnosis. These results suggest our automated analysis may facilitate assessment of atherosclerotic plaque stability.