Showing papers by "Leslee J. Shaw published in 2020"

Initial invasive or conservative strategy for stable coronary disease.

Abstract: Background Among patients with stable coronary disease and moderate or severe ischemia, whether clinical outcomes are better in those who receive an invasive intervention plus medical ther...

Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART).

Abstract: Background: The future risk of myocardial infarction is commonly assessed using cardiovascular risk scores, coronary artery calcium score, or coronary artery stenosis severity. We assessed whether ...

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry

Abstract: AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. CONCLUSION: A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

Association of Normal Systolic Blood Pressure Level with Cardiovascular Disease in the Absence of Risk Factors

Abstract: Importance The risk of atherosclerotic cardiovascular disease (ASCVD) at currently defined normal systolic blood pressure (SBP) levels in persons without ASCVD risk factors based on current definitions is not well defined. Objective To examine the association of SBP levels with coronary artery calcium and ASCVD in persons without hypertension or other traditional ASCVD risk factors based on current definitions. Design, Setting, and Participants A cohort of 1457 participants free of ASCVD from the Multi-Ethnic Study of Atherosclerosis who were without dyslipidemia (low-density lipoprotein cholesterol level ≥160 mg/dL or high-density lipoprotein cholesterol level Exposures Systolic blood pressure. Main Outcomes and Measures Presence or absence of coronary artery calcium and incident ASCVD events. Results Of the 1457 participants, 894 were women (61.4%); mean (SD) age was 58.1 (9.8) years and mean (SD) follow-up was 14.5 (3.9) years. There was an increase in traditional ASCVD risk factors, coronary artery calcium, and incident ASCVD events with increasing SBP levels. The aHR for ASCVD was 1.53 (95% CI, 1.17-1.99) for every 10-mm Hg increase in SBP levels. Compared with persons with SBP levels 90 to 99 mm Hg, the aHR for ASCVD risk was 3.00 (95% CI, 1.01-8.88) for SBP levels 100 to 109 mm Hg, 3.10 (95% CI, 1.03-9.28) for SBP levels 110 to 119 mm Hg, and 4.58 (95% CI, 1.47-14.27) for SBP levels 120 to 129 mm Hg. Conclusions and Relevance Beginning at an SBP level as low as 90 mm Hg, there appears to be a stepwise increase in the presence of coronary artery calcium and the risk of incident ASCVD with increasing SBP levels. These results highlight the importance of primordial prevention for SBP level increase and other traditional ASCVD risk factors, which generally seem to have similar trajectories of graded increase in risk within values traditionally considered to be normal.

Association of High-Density Calcified 1K Plaque with Risk of Acute Coronary Syndrome

Abstract: Importance: Plaque morphologic measures on coronary computed tomography angiography (CCTA) have been associated with future acute coronary syndrome (ACS). However, the evolution of calcified coronary plaques by noninvasive imaging is not known. Objective: To ascertain whether the increasing density in calcified coronary plaque is associated with risk for ACS. Design, Setting, and Participants: This multicenter case-control cohort study included individuals enrolled in ICONIC (Incident Coronary Syndromes Identified by Computed Tomography), a nested case-control study of patients drawn from the CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) registry, which included 13 study sites in 8 countries. Patients who experienced core laboratory-verified ACS after baseline CCTA (n = 189) and control individuals who did not experience ACS after baseline CCTA (n = 189) were included. Patients and controls were matched 1:1 by propensity scores for age; male sex; presence of hypertension, hyperlipidemia, and diabetes; family history of premature coronary artery disease (CAD); current smoking status; and CAD severity. Data were analyzed from November 2018 to March 2019. Exposures: Whole-heart atherosclerotic plaque volume was quantitated from all coronary vessels and their branches. For patients who underwent invasive angiography at the time of ACS, culprit lesions were coregistered to baseline CCTA lesions by a blinded independent reader. Low-density plaque was defined as having less than 130 Hounsfield units (HU); calcified plaque, as having more than 350 HU and subcategorized on a voxel-level basis into 3 strata: 351 to 700 HU, 701 to 1000 HU, and more than 1000 HU (termed 1K plaque). Main Outcomes and Measures: Association between calcium density and future ACS risk. Results: A total of 189 patients and 189 matched controls (mean [SD] age of 59.9 [9.8] years; 247 [65.3%] were male) were included in the analysis and were monitored during a mean (SD) follow-up period of 3.9 (2.5) years. The overall mean (SD) calcified plaque volume (>350 HU) was similar between patients and controls (76.4 [101.6] mm3 vs 99.0 [156.1] mm3; P =.32), but patients who experienced ACS exhibited less 1K plaque (>1000 HU) compared with controls (3.9 [8.3] mm3 vs 9.4 [23.2] mm3; P =.02). Individuals within the highest quartile of 1K plaque exhibited less low-density plaque, as a percentage of total plaque, when compared with patients within the lower 3 quartiles (12.6% [10.4%] vs 24.9% [20.6%]; P <.001). For 93 culprit precursor lesions detected by CCTA, the volume of 1K plaque was lower compared with the maximally stenotic lesion in controls (2.6 [7.2] mm3 vs 7.6 [20.3] mm3; P =.01). The per-patient and per-lesion results were similar between the 2 groups when restricted to myocardial infarction cases. Conclusions and Relevance: Results of this study suggest that, on a per-patient and per-lesion basis, 1K plaque was associated with a lower risk for future ACS and that measurement of 1K plaque may improve risk stratification beyond plaque burden.

Association of Sex With Severity of Coronary Artery Disease, Ischemia, and Symptom Burden in Patients With Moderate or Severe Ischemia: Secondary Analysis of the ISCHEMIA Randomized Clinical Trial.

Abstract: Importance While many features of stable ischemic heart disease vary by sex, differences in ischemia, coronary anatomy, and symptoms by sex have not been investigated among patients with moderate or severe ischemia. The enrolled ISCHEMIA trial cohort that underwent coronary computed tomographic angiography (CCTA) was required to have obstructive coronary artery disease (CAD) for randomization. Objective To describe sex differences in stress testing, CCTA findings, and symptoms in ISCHEMIA trial participants. Design, Setting, and Participants This secondary analysis of the multicenter ISCHEMIA randomized clinical trial analyzed baseline characteristics of patients with stable ischemic heart disease. Individuals were enrolled from July 2012 to January 2018 based on local reading of moderate or severe ischemia on a stress test, after which blinded CCTA was performed in most. Core laboratories reviewed stress tests and CCTAs. Participants with no obstructive CAD or with left main CAD of 50% or greater were excluded. Those who met eligibility criteria including CCTA (if performed) were randomized to a routine invasive or a conservative management strategy (N = 5179). Angina was assessed using the Seattle Angina Questionnaire. Analysis began October 1, 2018. Interventions CCTA and angina assessment. Main Outcomes and Measures Sex differences in stress test, CCTA findings, and symptom severity. Results Of 8518 patients enrolled, 6256 (77%) were men. Women were more likely to have no obstructive CAD ( Conclusions and Relevance Women in the ISCHEMIA trial had more frequent angina, independent of less extensive CAD, and less severe ischemia than men. These findings reflect inherent sex differences in the complex relationships between angina, atherosclerosis, and ischemia that may have implications for testing and treatment of patients with suspected stable ischemic heart disease. Trial Registration ClinicalTrials.gov Identifier:NCT01471522

Differences in Progression to Obstructive Lesions per High-Risk Plaque Features and Plaque Volumes With CCTA.

Abstract: Objectives This study explored whether the pattern of nonobstructive lesion progression into obstructive lesions would differ according to the presence of high-risk plaque (HRP). Background It is still debatable whether HRP simply represents a certain phase during the natural history of coronary atherosclerotic plaques or if disease progression would differ according to the presence of HRP. Methods Patients with nonobstructive coronary artery disease, defined as percent diameter stenosis (%DS) Results A total of 3,049 nonobstructive lesions were identified from 1,297 patients (mean age 60.3 ± 9.3 years; 56.8% men). There were 2,624 non-HRP and 425 HRP lesions. HRP lesions had a greater total PAV and all noncalcified components of PAV and %DS at baseline compared with non-HRP lesions. However, the annualized total PAV changes were greater in non-HRP lesions than in HRP lesions. On multivariate analysis adjusted for clinical risk factors, drug use, change in lipid level, total PAV, %DS, and HRP, only the baseline total PAV and %DS independently predicted the development of obstructive lesions (hazard ratio [HR]: 1.04; 95% confidence interval [CI]: 1.02 to 1.07, and HR: 1.07; 95% CI: 1.04 to 1.10, respectively, all p 0.05). Conclusions The pattern of individual coronary atherosclerotic plaque progression differed according to the presence of HRP. Baseline PAV, not the presence of HRP features, was the most important predictor of lesions developing into obstructive lesions. (Progression of Atherosclerotic Plaque Determined By Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411)

Machine Learning Framework to Identify Individuals at Risk of Rapid Progression of Coronary Atherosclerosis: From the PARADIGM Registry.

Abstract: Background Rapid coronary plaque progression (RPP) is associated with incident cardiovascular events. To date, no method exists for the identification of individuals at risk of RPP at a single point in time. This study integrated coronary computed tomography angiography-determined qualitative and quantitative plaque features within a machine learning (ML) framework to determine its performance for predicting RPP. Methods and Results Qualitative and quantitative coronary computed tomography angiography plaque characterization was performed in 1083 patients who underwent serial coronary computed tomography angiography from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry. RPP was defined as an annual progression of percentage atheroma volume ≥1.0%. We employed the following ML models: model 1, clinical variables; model 2, model 1 plus qualitative plaque features; model 3, model 2 plus quantitative plaque features. ML models were compared with the atherosclerotic cardiovascular disease risk score, Duke coronary artery disease score, and a logistic regression statistical model. 224 patients (21%) were identified as RPP. Feature selection in ML identifies that quantitative computed tomography variables were higher-ranking features, followed by qualitative computed tomography variables and clinical/laboratory variables. ML model 3 exhibited the highest discriminatory performance to identify individuals who would experience RPP when compared with atherosclerotic cardiovascular disease risk score, the other ML models, and the statistical model (area under the receiver operating characteristic curve in ML model 3, 0.83 [95% CI 0.78-0.89], versus atherosclerotic cardiovascular disease risk score, 0.60 [0.52-0.67]; Duke coronary artery disease score, 0.74 [0.68-0.79]; ML model 1, 0.62 [0.55-0.69]; ML model 2, 0.73 [0.67-0.80]; all P<0.001; statistical model, 0.81 [0.75-0.87], P=0.128). Conclusions Based on a ML framework, quantitative atherosclerosis characterization has been shown to be the most important feature when compared with clinical, laboratory, and qualitative measures in identifying patients at risk of RPP.

Stress Myocardial Perfusion Imaging vs Coronary Computed Tomographic Angiography for Diagnosis of Invasive Vessel-Specific Coronary Physiology: Predictive Modeling Results From the Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) Trial.

Abstract: Importance Stress imaging has been the standard for diagnosing functionally significant coronary artery disease. It is unknown whether novel, atherosclerotic plaque measures improve accuracy beyond coronary stenosis for diagnosing invasive fractional flow reserve (FFR) measurement. Objective To compare the diagnostic accuracy of comprehensive anatomic (obstructive and nonobstructive atherosclerotic plaque) vs functional imaging measures for estimating vessel-specific FFR. Design, Setting, and Participants Controlled clinical trial of diagnostic accuracy with a multicenter derivation-validation cohort of patients referred for nonemergent invasive coronary angiography. A total of 612 patients (64 [10] years; 30% women) with signs and symptoms suggestive of myocardial ischemia from 23 sites were included. Patients were recruited from 2014 to 2017. Data analysis began in August 2018. Interventions Patients underwent invasive coronary angiography with measurement of invasive FFR, coronary computed tomographic angiography (CCTA) quantification of atherosclerotic plaque and FFR by CT (FFR-CT), and semiquantitative scoring of rest/stress myocardial perfusion imaging (by magnetic resonance, positron emission tomography, or single photon emission CT). Multivariable generalized linear mixed models were derived and validated calculating the area under the receiver operating characteristics curve. Main Outcomes and Measures The primary end point was invasive FFR of 0.80 or less. Results Of the 612 patients, the mean (SD) age was 64 (10) years, and 426 (69.9%) were men. An invasive FFR of 0.80 or less was measured in 26.5% of 1727 vessels. In the derivation cohort, CCTA vessel-specific factors associated with FFR 0.80 or less were stenosis severity, percentage of noncalcified atheroma volume, lumen volume, the number of lesions with high-risk plaque (≥2 of low attenuation plaque, positive remodeling, napkin ring sign, or spotty calcification), and the number of lesions with stenosis greater than 30%. Fractional flow reserve–CT was not additive to this model including stenosis and atherosclerotic plaque. Significant myocardial perfusion imaging predictors were the summed rest and difference scores. In the validation cohort, the areas under the receiver operating characteristic curve were 0.81 for CCTA vs 0.67 for myocardial perfusion imaging (P Conclusions and Relevance A comprehensive anatomic interpretation with CCTA, including quantification of obstructive and nonobstructive atherosclerotic plaque, was superior to functional imaging in the diagnosis of invasive FFR. Comprehensive CCTA measures improve prediction of vessel-specific coronary physiology more so than stress-induced alterations in myocardial perfusion. Trial Registration ClinicalTrials.gov Identifier:NCT02173275.

Multimodality Cardiovascular Imaging in the Midst of the COVID-19 Pandemic: Ramping Up Safely to a New Normal.

Abstract: The coronavirus disease 2019 (COVID-19) pandemic created an unprecedented disruption to routine patient care ([1][1]). Health care professionals scrambled within weeks to attend to the surge of affected individuals amid concerns of hospital capacity and scarcity of personal protective equipment (PPE

Interplay of Coronary Artery Calcium and Risk Factors for Predicting CVD/CHD Mortality: The CAC Consortium

Abstract: Objectives This study sought to evaluate the association and burden of coronary artery calcium (CAC) with long-term, cause-specific mortality across the spectrum of baseline risk. Background Although CAC is a known predictor of short-term, all-cause mortality, data on long-term and cause-specific mortality are inadequate. Methods The CAC Consortium cohort is a multicenter cohort of 66,636 participants without coronary heart disease (CHD) who underwent CAC testing. The following risk factors (RFs) were considered: 1) current cigarette smoking; 2) dyslipidemia; 3) diabetes mellitus; 4) hypertension; and 5) family history of CHD. Results During the 12.5-years median follow-up, 3,158 (4.7%) deaths occurred; 32% were cardiovascular disease (CVD) deaths. Participants with CAC scores ≥400 had a significantly increased risk for CHD and CVD mortality (hazard ratio [HR]: 5.44; 95% confidence interval [CI]: 3.88 to 7.62; and HR: 4.15; 95% CI: 3.29 to 5.22, respectively) compared with CAC of 0. Participants with ≥3 RFs had a smaller increased risk for CHD and CVD mortality (HR: 2.09; 95% CI: 1.52 to 2.85; and HR: 1.84; 95% CI: 1.46 to 2.31, respectively) compared with those without RFs. Across RF strata, CAC added prognostic information. For example, participants without RFs but with CAC ≥400 had significantly higher all-cause, non-CVD, CVD, and CHD mortality rates compared with participants with ≥3 RFs and CAC of 0. Conclusions Across the spectrum of RF burden, a higher CAC score was strongly associated with long-term, all-cause mortality and a greater proportion of deaths due to CVD and CHD. Absence of CAC identified people with a low risk over 12 years of follow-up, with most deaths being non-CVD in nature, regardless of RF burden.

Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning Method

Abstract: Objectives This study designed and evaluated an end-to-end deep learning solution for cardiac segmentation and quantification. Background Segmentation of cardiac structures from coronary computed tomography angiography (CCTA) images is laborious. We designed an end-to-end deep-learning solution. Methods Scans were obtained from multicenter registries of 166 patients who underwent clinically indicated CCTA. Left ventricular volume (LVV) and right ventricular volume (RVV), left atrial volume (LAV) and right atrial volume (RAV), and left ventricular myocardial mass (LVM) were manually annotated as ground truth. A U-Net-inspired, deep-learning model was trained, validated, and tested in a 70:20:10 split. Results Mean age was 61.1 ± 8.4 years, and 49% were women. A combined overall median Dice score of 0.9246 (interquartile range: 0.8870 to 0.9475) was achieved. The median Dice scores for LVV, RVV, LAV, RAV, and LVM were 0.938 (interquartile range: 0.887 to 0.958), 0.927 (interquartile range: 0.916 to 0.946), 0.934 (interquartile range: 0.899 to 0.950), 0.915 (interquartile range: 0.890 to 0.920), and 0.920 (interquartile range: 0.811 to 0.944), respectively. Model prediction correlated and agreed well with manual annotation for LVV (r = 0.98), RVV (r = 0.97), LAV (r = 0.78), RAV (r = 0.97), and LVM (r = 0.94) (p Conclusions A deep-learning model rapidly segmented and quantified cardiac structures. This was done with high accuracy on a pixel level, with good agreement with manual annotation, facilitating its expansion into areas of research and clinical import.

The Relationship Between Coronary Calcification and the Natural History of Coronary Artery Disease.

Abstract: Objectives The aim of the current study was to explore the impact of plaque calcification in terms of absolute calcified plaque volume (CPV) and in the context of its percentage of the total plaque volume at a lesion and patient level on the progression of coronary artery disease. Background Coronary artery calcification is an established marker of risk of future cardiovascular events. Despite this, plaque calcification is also considered a marker of plaque stability, and it increases in response to medical therapy. Methods This analysis included 925 patients with 2,568 lesions from the PARADIGM (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging) registry, in which patients underwent clinically indicated serial coronary computed tomography angiography. Plaque calcification was examined by using CPV and percent CPV (PCPV), calculated as (CPV/plaque volume) × 100 at a per-plaque and per-patient level (summation of all individual plaques). Results CPV was strongly correlated with plaque volume (r = 0.780; p Conclusions Calcified plaque is a marker for risk of adverse events and disease progression due to its strong association with the total plaque burden. When considered as a percentage of the total plaque volume, increasing PCPV is a marker of plaque stability and reduced risk at both a lesion and patient level. (Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging [PARADIGM]; NCT02803411 )

Quantitative assessment of coronary plaque volume change related to triglyceride glucose index: The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry

Abstract: The association between triglyceride glucose (TyG) index and coronary atherosclerotic change remains unclear. We aimed to evaluate the association between TyG index and coronary plaque progression (PP) using serial coronary computed tomography angiography (CCTA). A total of 1143 subjects (aged 60.7 ± 9.3 years, 54.6% male) who underwent serial CCTA with available data on TyG index and diabetic status were analyzed from The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry. PP was defined as plaque volume (PV) (mm3) at follow-up minus PV at index > 0. Annual change of PV (mm3/year) was defined as PV change divided by inter-scan period. Rapid PP was defined as the progression of percent atheroma volume (PV divided by vessel volume multiplied by 100) ≥ 1.0%/year. The median inter-scan period was 3.2 (range 2.6–4.4) years. All participants were stratified into three groups based on TyG index tertiles. The overall incidence of PP was 77.3%. Baseline total PV (group I [lowest]: 30.8 (0.0–117.7), group II: 47.2 (6.2–160.4), and group III [highest]: 57.5 (8.4–154.3); P < 0.001) and the annual change of total PV (group I: 5.7 (0.0–20.2), group II: 7.6 (0.5–23.5), and group III: 9.4 (1.4–27.7); P = 0.010) were different among all groups. The risk of PP (odds ratio [OR] 1.648; 95% confidence interval [CI] 1.167–2.327; P = 0.005) and rapid PP (OR 1.777; 95% CI 1.288–2.451; P < 0.001) was increased in group III compared to that in group I. TyG index had a positive and significant association with an increased risk of PP and rapid PP after adjusting for confounding factors. TyG index is an independent predictive marker for the progression of coronary atherosclerosis. Clinical registration ClinicalTrials.gov NCT02803411

Clinical risk factors and atherosclerotic plaque extent to define risk for major events in patients without obstructive coronary artery disease: the long-term coronary computed tomography angiography CONFIRM registry

Abstract: AIMS: In patients without obstructive coronary artery disease (CAD), we examined the prognostic value of risk factors and atherosclerotic extent. METHODS AND RESULTS: Patients from the long-term CONFIRM registry without prior CAD and without obstructive (≥50%) stenosis were included. Within the groups of normal coronary computed tomography angiography (CCTA) (N = 1849) and non-obstructive CAD (N = 1698), the prognostic value of traditional clinical risk factors and atherosclerotic extent (segment involvement score, SIS) was assessed with Cox models. Major adverse cardiac events (MACE) were defined as all-cause mortality, non-fatal myocardial infarction, or late revascularization. In total, 3547 patients were included (age 57.9 ± 12.1 years, 57.8% male), experiencing 460 MACE during 5.4 years of follow-up. Age, body mass index, hypertension, and diabetes were the clinical variables associated with increased MACE risk, but the magnitude of risk was higher for CCTA defined atherosclerotic extent; adjusted hazard ratio (HR) for SIS >5 was 3.4 (95% confidence interval [CI] 2.3-4.9) while HR for diabetes and hypertension were 1.7 (95% CI 1.3-2.2) and 1.4 (95% CI 1.1-1.7), respectively. Exclusion of revascularization as endpoint did not modify the results. In normal CCTA, presence of ≥1 traditional risk factors did not worsen prognosis (log-rank P = 0.248), while it did in non-obstructive CAD (log-rank P = 0.025). Adjusted for SIS, hypertension and diabetes predicted MACE risk in non-obstructive CAD, while diabetes did not increase risk in absence of CAD (P-interaction = 0.004). CONCLUSION: Among patients without obstructive CAD, the extent of CAD provides more prognostic information for MACE than traditional cardiovascular risk factors. An interaction was observed between risk factors and CAD burden, suggesting synergistic effects of both.

A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA

Abstract: Objectives This study sought to identify culprit lesion (CL) precursors among acute coronary syndrome (ACS) patients based on qualitative and quantitative computed tomography–based plaque characteristics. Background Coronary computed tomography angiography (CTA) has been validated for patient-level prediction of ACS. However, the applicability of coronary CTA to CL assessment is not known. Methods Utilizing the ICONIC (Incident COroNary Syndromes Identified by Computed Tomography) study, a nested case-control study of 468 patients with baseline coronary CTA, the study included ACS patients with invasive coronary angiography–adjudicated CLs that could be aligned to CL precursors on baseline coronary CTA. Separate blinded core laboratories adjudicated CLs and performed atherosclerotic plaque evaluation. Thereafter, the study used a boosted ensemble algorithm (XGBoost) to develop a predictive model of CLs. Data were randomly split into a training set (80%) and a test set (20%). The area under the receiver-operating characteristic curve of this model was compared with that of diameter stenosis (model 1), high-risk plaque features (model 2), and lesion-level features of CL precursors from the ICONIC study (model 3). Thereafter, the machine learning (ML) model was applied to 234 non-ACS patients with 864 lesions to determine model performance for CL exclusion. Results CL precursors were identified by both coronary angiography and baseline coronary CTA in 124 of 234 (53.0%) patients, with a total of 582 lesions (containing 124 CLs) included in the analysis. The ML model demonstrated significantly higher area under the receiver-operating characteristic curve for discriminating CL precursors (0.774; 95% confidence interval [CI]: 0.758 to 0.790) compared with model 1 (0.599; 95% CI: 0.599 to 0.599; p Conclusions In a high-risk cohort, a boosted ensemble algorithm can be used to predict CL from non-CL precursors on coronary CTA.

Sex Differences in Compositional Plaque Volume Progression in Patients With Coronary Artery Disease

Abstract: OBJECTIVES: This study sought to explore sex-based differences in total and compositional plaque volume (PV) progression. BACKGROUND: It is unclear whether sex has an impact on PV progression in patients with coronary artery disease (CAD). METHODS: The study analyzed a prospective multinational registry of consecutive patients with suspected CAD who underwent 2 or more clinically indicated coronary computed tomography angiography (CTA) at ≥2-year intervals. Total and compositional PV at baseline and follow-up were quantitatively analyzed and normalized using the analyzed total vessel length. Multivariate linear regression models were constructed. RESULTS: Of the 1,255 patients included (median coronary CTA interval 3.8 years), 543 were women and 712 were men. Women were older (62 ± 9 years of age vs. 59 ± 9 years of age; p 0.05). At baseline, men possessed greater total PV (31.3 mm3 [interquartile range (IQR): 0 to 121.8 mm3] vs. 56.7 mm3 [IQR: 6.8 to 152.1 mm3] p = 0.005), and there was an approximately 9-year delay in women in developing total PV than in men. The prevalence of high-risk plaques was greater in men than women (31% vs. 20%; p < 0.001). In multivariate analysis, after adjusting for age, clinical risk factors, medication use, and total PV at baseline, despite similar total PV progression rates, female sex was associated with greater calcified PV progression (β = 2.83; p = 0.004) but slower noncalcified PV progression (β = -3.39; p = 0.008) and less development of high-risk plaques (β = -0.18; p = 0.049) than in men. CONCLUSIONS: The compositional PV progression differed according to sex, suggesting that comprehensive plaque evaluation may contribute to further refining of risk stratification according to sex. (NCT02803411).

Sex Differences in Coronary Artery Calcium and Mortality From Coronary Heart Disease, Cardiovascular Disease, and All Causes in Adults With Diabetes: The Coronary Calcium Consortium.

Abstract: OBJECTIVE While diabetes has been previously noted to be a stronger risk factor for cardiovascular disease (CVD) in women compared with men, whether this is still the case is not clear. Coronary artery calcium (CAC) predicts coronary heart disease (CHD) and CVD in people with diabetes; however, its sex-specific impact is less defined. We compared the relation of CAC in women versus men with diabetes for total, CVD, and CHD mortality. RESEARCH DESIGN AND METHODS We studied adults with diabetes from a large registry of patients with CAC scanning with mortality follow-up over 11.5 years. Cox regression examined the relation of CAC with mortality end points. RESULTS Among 4,503 adults with diabetes (32.5% women) aged 21–93 years, 61.2% of women and 80.4% of men had CAC >0. Total, CVD, and CHD mortality rates were directly related to CAC; women had higher total and CVD death rates than men when CAC >100. Age- and risk factor-adjusted hazard ratios (HRs) per log unit CAC were higher among women versus men for total (1.28 vs. 1.18) (interaction P = 0.01) and CVD mortality (1.47 vs. 1.27) (interaction P = 0.04) but were similar for CHD mortality (1.53 and 1.48). For CVD mortality, HRs with CAC scores of 101–400 and >400 were 3.67 and 6.27, respectively, for women and 1.63 and 3.48, respectively, for men (interaction P = 0.04). For total mortality, HRs were 2.56 and 4.05 for women, respectively, and 1.88 and 2.66 for men, respectively (interaction P = 0.01). CONCLUSIONS CAC predicts CHD, CVD, and all-cause mortality in patients with diabetes; however, greater CAC predicts CVD and total mortality more strongly in women.

Association of Cardiovascular Disease Risk Factor Burden With Progression of Coronary Atherosclerosis Assessed by Serial Coronary Computed Tomographic Angiography

Abstract: Importance Several studies have reported that the progression of coronary atherosclerosis, as measured by serial coronary computed tomographic (CT) angiography, is associated with the risk of future cardiovascular events. However, the cumulative consequences of multiple risk factors for plaque progression and the development of adverse plaque characteristics have not been well characterized. Objectives To examine the association of cardiovascular risk factor burden, as assessed by atherosclerotic cardiovascular disease (ASCVD) risk score, with the progression of coronary atherosclerosis and the development of adverse plaque characteristics. Design, Setting, and Participants This cohort study is a subgroup analysis of participant data from the prospective observational Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) study, which evaluated the association between serial coronary CT angiography findings and clinical presentation. The PARADIGM international multicenter registry, which includes 13 centers in 7 countries (Brazil, Canada, Germany, Italy, Portugal, South Korea, and the US), was used to identify 1005 adult patients without known coronary artery disease who underwent serial coronary CT angiography scans (median interscan interval, 3.3 years; interquartile range [IQR], 2.6-4.8 years) between December 24, 2003, and December 16, 2015. Based on the 10-year ASCVD risk score, the cardiovascular risk factor burden was classified as low ( 20.0%). Data were analyzed from February 8, 2019, to April 17, 2020. Exposures Association of baseline ASCVD risk burden with plaque progression. Main Outcomes and Measures Noncalcified plaque, calcified plaque, and total plaque volumes (mm3) were measured. Noncalcified plaque was subclassified using predefined Hounsfield unit thresholds for fibrous, fibrofatty, and low-attenuation plaque. The percent atheroma volume (PAV) was defined as plaque volume divided by vessel volume. Adverse plaque characteristics were defined as the presence of positive remodeling, low-attenuation plaque, or spotty calcification. Results In total, 1005 patients (mean [SD] age, 60 [8] years; 575 men [57.2%]) were included in the analysis. Of those, 463 patients (46.1%) had a low 10-year ASCVD risk score (low-risk group), 373 patients (37.1%) had an intermediate ASCVD risk score (intermediate-risk group), and 169 patients (16.8%) had a high ASCVD risk score (high-risk group). The annualized progression rate of PAV for total plaque, calcified plaque, and noncalcified plaque was associated with increasing ASCVD risk (r = 0.26 for total plaque,r = 0.23 for calcified plaque, andr = 0.11 for noncalcified plaque;P Conclusions and Relevance Progression of coronary atherosclerosis occurred across all ASCVD risk groups and was associated with an increase in 10-year ASCVD risk. The progression of fibrofatty and low-attenuation plaques and the development of adverse plaque characteristics was greater in patients with a high risk of ASCVD.

Automatic segmentation of multiple cardiovascular structures from cardiac computed tomography angiography images using deep learning.

Abstract: OBJECTIVES: To develop, demonstrate and evaluate an automated deep learning method for multiple cardiovascular structure segmentation. BACKGROUND: Segmentation of cardiovascular images is resource-intensive. We design an automated deep learning method for the segmentation of multiple structures from Coronary Computed Tomography Angiography (CCTA) images. METHODS: Images from a multicenter registry of patients that underwent clinically-indicated CCTA were used. The proximal ascending and descending aorta (PAA, DA), superior and inferior vena cavae (SVC, IVC), pulmonary artery (PA), coronary sinus (CS), right ventricular wall (RVW) and left atrial wall (LAW) were annotated as ground truth. The U-net-derived deep learning model was trained, validated and tested in a 70:20:10 split. RESULTS: The dataset comprised 206 patients, with 5.130 billion pixels. Mean age was 59.9 ± 9.4 yrs., and was 42.7% female. An overall median Dice score of 0.820 (0.782, 0.843) was achieved. Median Dice scores for PAA, DA, SVC, IVC, PA, CS, RVW and LAW were 0.969 (0.979, 0.988), 0.953 (0.955, 0.983), 0.937 (0.934, 0.965), 0.903 (0.897, 0.948), 0.775 (0.724, 0.925), 0.720 (0.642, 0.809), 0.685 (0.631, 0.761) and 0.625 (0.596, 0.749) respectively. Apart from the CS, there were no significant differences in performance between sexes or age groups. CONCLUSIONS: An automated deep learning model demonstrated segmentation of multiple cardiovascular structures from CCTA images with reasonable overall accuracy when evaluated on a pixel level.

Non-obstructive high-risk plaques increase the risk of future culprit lesions comparable to obstructive plaques without high-risk features The iconic study

Abstract: Author(s): Ferraro, Richard A; van Rosendael, Alexander R; Lu, Yao; Andreini, Daniele; Al-Mallah, Mouaz H; Cademartiri, Filippo; Chinnaiyan, Kavitha; Chow, Benjamin JW; Conte, Edoardo; Cury, Ricardo C; Feuchtner, Gudrun; de Araujo Goncalves, Pedro; Hadamitzky, Martin; Kim, Yong-Jin; Leipsic, Jonathon; Maffei, Erica; Marques, Hugo; Plank, Fabian; Pontone, Gianluca; Raff, Gilbert L; Villines, Todd C; Lee, Sang-Eun; Al'Aref, Subhi J; Baskaran, Lohendran; Cho, Iksung; Danad, Ibrahim; Gransar, Heidi; Budoff, Matthew J; Samady, Habib; Stone, Peter H; Virmani, Renu; Narula, Jagat; Berman, Daniel S; Chang, Hyuk-Jae; Bax, Jeroen J; Min, James K; Shaw, Leslee J; Lin, Fay Y | Abstract: AimsHigh-risk plaque (HRP) and non-obstructive coronary artery disease independently predict adverse events, but their importance to future culprit lesions has not been resolved. We sought to determine in patients prior to confirmed acute coronary syndrome (ACS) the association between lesion percent diameter stenosis (%DS), and the absolute number and prevalence of HRP. The secondary objective was to examine the relative importance of non-obstructive HRP in future culprit lesions.Methods and resultsWithin the ICONIC study, a nested case-control study of patients undergoing coronary computed tomographic angiography (coronary CT), we included ACS cases with culprit lesions confirmed by invasive coronary angiography and coregistered to baseline coronary CT. Quantitative CT was used to evaluate obstructive (≥50%) and non-obstructive (l50%) diameter stenosis, with HRP defined as ≥2 features of spotty calcification, positive remodelling, or low-attenuation plaque at baseline. A total of 234 patients with downstream ACS over 54 (interquartile range 5-525.5) days exhibited 198/898 plaques with HRP on coronary CT. While HRP was less prevalent in non-obstructive (19.7%, 161/819) than obstructive lesions (46.8%, 37/79, P l 0.001), non-obstructive plaque comprised 81.3% (161/198) of HRP lesions overall. Among the 128 patients with identifiable culprit lesion precursors, the adjusted hazard ratio (HR) was 1.85 [95% confidence interval (CI) 1.26-2.72] for HRP, with no interaction between %DS and HRP (P = 0.82). Compared to non-obstructive HRP lesions, obstructive lesions without HRP exhibited a non-significant HR of 1.41 (95% CI 0.61-3.25, P = 0.42).ConclusionsWhile HRP is more prevalent among obstructive lesions, non-obstructive HRP lesions outnumber those that are obstructive and confer risk clinically approaching that of obstructive lesions without HRP.

Cardiac Imaging in the Post-ISCHEMIA Trial Era: A Multisociety Viewpoint

Abstract: The highly anticipated ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) trial, the largest study to-date conducted to assess for the incremental clinical benefits of an initial invasive management strategy over an initial medical therapy