Sex and age-specific interactions of coronary atherosclerotic plaque onset and prognosis from coronary computed tomography.

AIMS: The totality of atherosclerotic plaque derived from coronary computed tomography angiography (CCTA) emerges as a comprehensive measure to assess the intensity of medical treatment that patients need. This study examines the differences in age onset and prognostic significance of atherosclerotic plaque burden between sexes. METHODS AND RESULTS: From a large multi-center CCTA registry the Leiden CCTA score was calculated in 24 950 individuals. A total of 11 678 women (58.5 ± 12.4 years) and 13 272 men (55.6 ± 12.5 years) were followed for 3.7 years for major adverse cardiovascular events (MACE) (death or myocardial infarction). The age where the median risk score was above zero was 12 years higher in women vs. men (64-68 years vs. 52-56 years, respectively, P < 0.001). The Leiden CCTA risk score was independently associated with MACE: score 6-20: HR 2.29 (1.69-3.10); score > 20: HR 6.71 (4.36-10.32) in women, and score 6-20: HR 1.64 (1.29-2.08); score > 20: HR 2.38 (1.73-3.29) in men. The risk was significantly higher for women within the highest score group (adjusted P-interaction = 0.003). In pre-menopausal women, the risk score was equally predictive and comparable with men. In post-menopausal women, the prognostic value was higher for women [score 6-20: HR 2.21 (1.57-3.11); score > 20: HR 6.11 (3.84-9.70) in women; score 6-20: HR 1.57 (1.19-2.09); score > 20: HR 2.25 (1.58-3.22) in men], with a significant interaction for the highest risk group (adjusted P-interaction = 0.004). CONCLUSION: Women developed coronary atherosclerosis approximately 12 years later than men. Post-menopausal women within the highest atherosclerotic burden group were at significantly higher risk for MACE than their male counterparts, which may have implications for the medical treatment intensity.

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.

Age related compositional plaque burden by CT in patients with future ACS.

BACKGROUND: We examined age differences in whole-heart volumes of non-calcified and calcified atherosclerosis by coronary computed tomography angiography (CCTA) of patients with future ACS. METHODS: A total of 234 patients with core-lab adjudicated ACS after baseline CCTA were enrolled. Atherosclerotic plaque was quantified and characterized from the main epicardial vessels and side branches on a 0.5 â€‹mm cross-sectional basis. Calcified plaque and non-calcified plaque were defined by above or below 350 Hounsfield units. Patients were categorized according to their age by deciles. Also, coronary artery calcium scores (CACS) were evaluated when available. RESULTS: Patients were on average 62.2 â€‹± â€‹11.5 years old. On the pre-ACS CCTA, patients showed diffuse, multi-site, predominantly non-obstructive atherosclerosis across all age categories, with plaque being detected in 93.5% of all ACS cases. The proportion calcified plaque from the total plaque burden increased significantly with older presentation (10% calcification in those <50 years, and 50% calcification in those >80 years old). Patients with ACS <50 years had remarkably lower atherosclerotic burden compared with older patients, but a high proportion of high risk markers such as low-attenuation plaque. CACS was >0 in 85% of the patients older than 50 years, and in 57% of patients younger than 50 years. CONCLUSION: The proportion of calcified plaque varied depending on patient age at the time of ACS. Only a small proportion of plaque was calcified when ACS occurred at <50 years old, while this increased gradually with older age. Purely non-calcified atherosclerotic plaque was not uncommon in patients <50 years.

Aspirin and Statin Therapy for Nonobstructive Coronary Artery Disease: Five-year Outcomes from the CONFIRM Registry.

Purpose: In this cohort study, 5-year data from the Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry (ie, CONFIRM) were examined to identify associations of baseline aspirin and statin use with mortality, major adverse cardiovascular events (MACE), and myocardial infarction (MI) in individuals without substantial (≥50%) stenosis. Materials and Methods: In this prospective cohort study, all participants in the registry underwent coronary CT angiography and were classified as having no detectable coronary plaque or having nonobstructive coronary artery disease (CAD) (1%-49% stenosis). Participants with obstructive (≥50%) stenosis were excluded from analysis. The study commenced in June 2003 and was completed in March 2016. All unadjusted and risk-adjusted analyses utilized the Cox proportional hazard model with hospital sites modeled using shared frailty. Results: A total of 6386 participants with no detectable plaque or with nonobstructive CAD were included (mean age, 56.0 years ± 13.3 [SD], 52% men). The mean follow-up period was 5.66 years ± 1.10. Nonobstructive CAD (n = 2815, 44% of all participants included in the study) was associated with a greater risk of all-cause mortality (10.6% [298 of 2815] vs 4.8% [170 of 3571], P < .001) compared to those without CAD (n = 3571, 56%). Baseline aspirin and statin use was documented for 1415 and 1429 participants, respectively, with nonobstructive CAD, and for 1560 and 1565 participants without detectable plaque, respectively. In individuals with nonobstructive CAD, baseline aspirin use was not associated with a reduction in MACE (10.9% [102 of 936] vs 14.7% [52 of 355], P = .06), all-cause mortality (9.6% [95 of 991] vs 10.9% [46 of 424], P = .468), or MI (4.4% [41 of 936] vs 6.2% [22 of 355], P = .18). On multivariate risk-adjusted analysis, baseline statin use was associated with a lower rate of MACE (hazard ratio, 0.59; 95% CI: 0.40, 0.87; P = .007). Neither therapy improved clinical outcomes for participants with no detectable plaque. Conclusion: In participants with nonobstructive CAD, baseline use of statins, but not of aspirin, was associated with improved clinical outcomes. Neither therapy was associated with benefit in participants without plaque.Keywords: Aspirin, Statin, Coronary Artery Disease, CT Angiography, Nonobstructive Coronary Artery DiseaseClinical trial registration no. NCT01443637 Supplemental material is available for this article. © RSNA, 2022See also the commentary by Canan and Navar in this issue.

Associations between dyspnoea, coronary atherosclerosis, and cardiovascular outcomes: results from the long-term follow-up CONFIRM registry.

AIMS: The relationship between dyspnoea, coronary artery disease (CAD), and major cardiovascular events (MACE) is poorly understood. This study evaluated (i) the association of dyspnoea with the severity of anatomical CAD by coronary computed tomography angiography (CCTA) and (ii) to which extent CAD explains MACE in patients with dyspnoea. METHODS AND RESULTS: From the international COronary CT Angiography EvaluatioN for Clinical Outcomes: An InteRnational Multicenter (CONFIRM) registry, 4425 patients (750 with dyspnoea) with suspected but without known CAD were included and prospectively followed for ≥5 years. First, the association of dyspnoea with CAD severity was assessed using logistic regression analysis. Second, the prognostic value of dyspnoea for MACE (myocardial infarction and death), and specifically, the interaction between dyspnoea and CAD severity was investigated using Cox proportional-hazard analysis. Mean patient age was 60.3 ± 11.9 years, 63% of patients were male and 592 MACE events occurred during a median follow-up duration of 5.4 (IQR 5.1-6.0) years. On uni- and multivariable analysis (adjusting for age, sex, body mass index, chest pain typicality, and risk factors), dyspnoea was associated with two- and three-vessel/left main (LM) obstructive CAD. The presence of dyspnoea increased the risk for MACE [hazard ratio (HR) 1.57, 95% confidence interval (CI): 1.29-1.90], which was modified after adjusting for clinical predictors and CAD severity (HR 1.26, 95% CI: 1.02-1.55). Conversely, when stratified by CAD severity, dyspnoea did not provide incremental prognostic value in one-, two-, or three-vessel/LM obstructive CAD, but dyspnoea did provide incremental prognostic value in non-obstructive CAD. CONCLUSION: In patients with suspected CAD, dyspnoea was independently associated with severe obstructive CAD on CCTA. The severity of obstructive CAD explained the elevated MACE rates in patients presenting with dyspnoea, but in patients with non-obstructive CAD, dyspnoea portended additional risk.

Topological Data Analysis of Coronary Plaques Demonstrates the Natural History of Coronary Atherosclerosis.

OBJECTIVES: This study sought to identify distinct patient groups and their association with outcome based on the patient similarity network using quantitative coronary plaque characteristics from coronary computed tomography angiography (CTA). BACKGROUND: Coronary CTA can noninvasively assess coronary plaques quantitatively. METHODS: Patients who underwent 2 coronary CTAs at a minimum of 24 months' interval were analyzed (n = 1,264). A similarity Mapper network of patients was built by topological data analysis (TDA) based on the whole-heart quantitative coronary plaque analysis on coronary CTA to identify distinct patient groups and their association with outcome. RESULTS: Three distinct patient groups were identified by TDA, and the patient similarity network by TDA showed a closed loop, demonstrating a continuous trend of coronary plaque progression. Group A had the least coronary plaque amount (median 12.4 mm3 [interquartile range (IQR): 0.0 to 39.6 mm3]) in the entire coronary tree. Group B had a moderate coronary plaque amount (31.7 mm3 [IQR: 0.0 to 127.4 mm3]) with relative enrichment of fibrofatty and necrotic core (32.6% [IQR: 16.7% to 46.2%] and 2.7% [IQR: 0.1% to 6.9%] of the total plaque, respectively) components. Group C had the largest coronary plaque amount (187.0 mm3 [IQR: 96.7 to 306.4 mm3]) and was enriched for dense calcium component (46.8% [IQR: 32.0% to 63.7%] of the total plaque). At follow-up, total plaque volume, fibrous, and dense calcium volumes increased in all groups, but the proportion of fibrofatty component decreased in groups B and C, whereas the necrotic core portion decreased in only group B (all p < 0.05). Group B showed a higher acute coronary syndrome incidence than other groups (0.3% vs. 2.6% vs. 0.6%; p = 0.009) but both group B and C had a higher revascularization incidence than group A (3.1% vs. 15.5% vs. 17.8%; p < 0.001). Incorporating group information from TDA demonstrated increase of model fitness for predicting acute coronary syndrome or revascularization compared with that incorporating clinical risk factors, percentage diameter stenosis, and high-risk plaque features. CONCLUSIONS: The TDA of quantitative whole-heart coronary plaque characteristics on coronary CTA identified distinct patient groups with different plaque dynamics and clinical outcomes. (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging [PARADIGM]; NCT02803411).

Progression of whole-heart Atherosclerosis by coronary CT and major adverse cardiovascular events.

BACKGROUND: The current study aimed to examine the independent prognostic value of whole-heart atherosclerosis progression by serial coronary computed tomography angiography (CCTA) for major adverse cardiovascular events (MACE). METHODS: The multi-center PARADIGM study includes patients undergoing serial CCTA for symptomatic reasons, ≥2 years apart. Whole-heart atherosclerosis was characterized on a segmental level, with co-registration of baseline and follow-up CCTA, and summed to per-patient level. The independent prognostic significance of atherosclerosis progression for MACE (non-fatal myocardial infarction [MI], death, unplanned coronary revascularization) was examined. Patients experiencing interval MACE were not omitted. RESULTS: The study population comprised 1166 patients (age 60.5 â€‹± â€‹9.5 years, 54.7% male) who experienced 139 MACE events during 8.2 (IQR 6.2, 9.5) years of follow up (15 death, 5 non-fatal MI, 119 unplanned revascularizations). Whole-heart percent atheroma volume (PAV) increased from 2.32% at baseline to 4.04% at follow-up. Adjusted for baseline PAV, the annualized increase in PAV was independently associated with MACE: OR 1.23 (95% CI 1.08, 1.39) per 1 standard deviation increase, which was consistent in multiple subpopulations. When categorized by composition, only non-calcified plaque progression associated independently with MACE, while calcified plaque did not. Restricting to patients without events before follow-up CCTA, those with future MACE showed an annualized increase in PAV of 0.93% (IQR 0.34, 1.96) vs 0.32% (IQR 0.02, 0.90), P â€‹< â€‹0.001. CONCLUSIONS: Whole-heart atherosclerosis progression examined by serial CCTA is independently associated with MACE, with a prognostic threshold of 1.0% increase in PAV per year.

Age- and sex-related features of atherosclerosis from coronary computed tomography angiography in patients prior to acute coronary syndrome: results from the ICONIC study.

AIMS: Although there is increasing evidence supporting coronary atherosclerosis evaluation by coronary computed tomography angiography (CCTA), no data are available on age and sex differences for quantitative plaque features. The aim of this study was to investigate sex and age differences in both qualitative and quantitative atherosclerotic features from CCTA prior to acute coronary syndrome (ACS). METHODS AND RESULTS: Within the ICONIC study, in which 234 patients with subsequent ACS were propensity matched 1:1 with 234 non-event controls, our current subanalysis included only the ACS cases. Both qualitative and quantitative advance plaque analysis by CCTA were performed by a core laboratory. In 129 cases, culprit lesions identified by invasive coronary angiography at the time of ACS were co-registered to baseline CCTA precursor lesions. The study population was then divided into subgroups according to sex and age (<65 vs. ≥ 65 years old) for analysis. Older patients had higher total plaque volume than younger patients. Within specific subtypes of plaque volume, however, only calcified plaque volume was higher in older patients (135.9 ± 163.7 vs. 63.8 ± 94.2 mm3, P < 0.0001, respectively). Although no sex-related differences were recorded for calcified plaque volume, females had lower fibrous and fibrofatty plaque volume than males (Fibrofatty volume 29.6 ± 44.1 vs. 75.3 ± 98.6 mm3, P = 0.0001, respectively). No sex-related differences in the prevalence of qualitative high-risk plaque features were found, even after separate analyses considering age were performed. CONCLUSION: Our data underline the importance of age- and sex-related differences in coronary atherosclerosis presentation, which should be considered during CCTA-based atherosclerosis quantification.

Impact of age on coronary artery plaque progression and clinical outcome: A PARADIGM substudy.

BACKGROUND: The association of age with coronary plaque dynamics is not well characterized by coronary computed tomography angiography (CCTA). METHODS: From a multinational registry of patients who underwent serial CCTA, 1153 subjects (61 ± 5 years old, 61.1% male) were analyzed. Annualized volume changes of total, fibrous, fibrofatty, necrotic core, and dense calcification plaque components of the whole heart were compared by age quartile groups. Clinical events, a composite of all-cause death, acute coronary syndrome, and any revascularization after 30 days of the initial CCTA, were also analyzed. Random forest analysis was used to define the relative importance of age on plaque progression. RESULTS: With a 3.3-years' median interval between the two CCTA, the median annual volume changes of total plaque in each age quartile group was 7.8, 10.5, 10.8, and 12.1 mm3/year and for dense calcification, 2.5, 4.6, 5.4, and 7.1 mm3/year, both of which demonstrated a tendency to increase by age (p-for-trend = 0.001 and < 0.001, respectively). However, this tendency was not observed in any other plaque components. The annual volume changes of total plaque and dense calcification were also significantly different in the propensity score-matched lowest age quartile group versus the other age groups as was the composite clinical event (log-rank p = 0.003). In random forest analysis, age had comparable importance in the total plaque volume progression as other traditional factors. CONCLUSIONS: The rate of whole-heart plaque progression and dense calcification increases depending on age. Age is a significant factor in plaque growth, the importance of which is comparable to other traditional risk factors. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifiers: NCT02803411.

The clinical utility of FFRCT stratified by age.

BACKGROUND: CT coronary angiography (CTA) with Fractional Flow Reserve as determined by CT (FFRCT) is a safe alternative to invasive coronary angiography. A negative FFRCT has been shown to have low cardiac event rates compared to those with a positive FFRCT. However, the clinical utility of FFRCT according to age is not known. METHODS: Patients' in the ADVANCE (Assessing Diagnostic Value of Non-invasive FFRCT in Coronary Care) registry, were stratified into those ≥65 or <65 years of age. The impact of FFRCT on clinical decision-making, as assessed by patient age, was determined by evaluating patient management using CTA results alone, followed by site investigators submitting a report on the treatment plan based upon the newly provided FFRCT data. Outcomes at 1-year post CTA were assessed, including major adverse cardiovascular events (myocardial infarction, all-cause mortality or unplanned hospitalization for ACS leading to revascularisation) and total revascularisation. Positive FFRCT was deemed to be â€‹≤ â€‹0.8. RESULTS: FFRCT was calculated in 1849 (40.6%) subjects aged <65 and 2704 (59.4%) â€‹≥ â€‹65 years of age. Subjects ≥65 years were more likely to have anatomic obstructive disease on CTA (≥50% stenosis), compared to those aged <65 (69.7% and 73.2% respectively, p â€‹= â€‹0.008). There was a similar graded increase in recommended and actual revascularisation with either CABG or PCI, with declining FFRCT strata for subjects above and below the age of 65. MACE and revascularisation rates were not significantly different for those â€‹≥ â€‹or <65, regardless of FFRCT positivity or stenosis severity <50% or ≥50%. With a negative FFRCT result, and anatomical stenosis ≥50%, those â€‹≥ â€‹and <65 years of age, had similar rates of MACE (0.2% for both, p â€‹= â€‹0.1) and revascularisation (8.7% and 10.4% respectively p â€‹= â€‹0.4). Logistic regression analysis, with age as a continuous variable, and adjustment for Diamond Forrester Risk, baseline FFRCT and treatment (CABG, PCI, medical therapy), indicated a statistically significant, but small increase in the odds of a MACE event with increasing age (OR 1.04, 95% CI 1.006-1.08, p â€‹= â€‹0.02). Amongst patients with a FFRCT > 0.80, there was no effect of age on the odds of revascularisation. CONCLUSION: The findings of this study point to a low risk of MACE events or need for revascularisation in those aged â€‹≥ â€‹or <65 with a FFRCT>0.80, despite the higher incidence of anatomic obstructive CAD in those ≥65 years. The findings show the clinical usefulness and outcomes of FFRCT are largely constant regardless of age.

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.

BACKGROUND: 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). METHODS: 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. RESULTS: 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. CONCLUSION: TyG index is an independent predictive marker for the progression of coronary atherosclerosis. Clinical registration ClinicalTrials.gov NCT02803411.

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

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 < 0.01), model 2 (0.532; 95% CI: 0.501 to 0.563; p < 0.01), and model 3 (0.672; 95% CI: 0.662 to 0.682; p < 0.01). When applied to the non-ACS cohort, the ML model had a specificity of 89.3% for excluding CLs. CONCLUSIONS: In a high-risk cohort, a boosted ensemble algorithm can be used to predict CL from non-CL precursors on coronary CTA.

Non-obstructive high-risk plaques increase the risk of future culprit lesions comparable to obstructive plaques without high-risk features: the ICONIC study.

AIMS: High-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 RESULTS: Within 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 (<50%) 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 < 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). CONCLUSIONS: While 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.

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

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.

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

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.

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.

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.

Percent atheroma volume: Optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study.

BACKGROUND AND AIMS: Different methodologies to report whole-heart atherosclerotic plaque on coronary computed tomography angiography (CCTA) have been utilized. We examined which of the three commonly used plaque burden definitions was least affected by differences in body surface area (BSA) and sex. METHODS: The PARADIGM study includes symptomatic patients with suspected coronary atherosclerosis who underwent serial CCTA >2 years apart. Coronary lumen, vessel, and plaque were quantified from the coronary tree on a 0.5 mm cross-sectional basis by a core-lab, and summed to per-patient. Three quantitative methods of plaque burden were employed: (1) total plaque volume (PV) in mm3, (2) percent atheroma volume (PAV) in % [which equaled: PV/vessel volume * 100%], and (3) normalized total atheroma volume (TAVnorm) in mm3 [which equaled: PV/vessel length * mean population vessel length]. Only data from the baseline CCTA were used. PV, PAV, and TAVnorm were compared between patients in the top quartile of BSA vs the remaining, and between sexes. Associations between vessel volume, BSA, and the three plaque burden methodologies were assessed. RESULTS: The study population comprised 1479 patients (age 60.7 ± 9.3 years, 58.4% male) who underwent CCTA. A total of 17,649 coronary artery segments were evaluated with a median of 12 (IQR 11-13) segments per-patient (from a 16-segment coronary tree). Patients with a large BSA (top quartile), compared with the remaining patients, had a larger PV and TAVnorm, but similar PAV. The relation between larger BSA and larger absolute plaque volume (PV and TAVnorm) was mediated by the coronary vessel volume. Independent from the atherosclerotic cardiovascular disease risk (ASCVD) score, vessel volume correlated with PV (P < 0.001), and TAVnorm (P = 0.003), but not with PAV (P = 0.201). The three plaque burden methods were equally affected by sex. CONCLUSIONS: PAV was less affected by patient's body surface area then PV and TAVnorm and may be the preferred method to report coronary atherosclerotic burden.

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

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.

Increased long-term mortality in women with high left ventricular ejection fraction: data from the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) long-term registry.

AIMS: There are significant sex-specific differences in left ventricular ejection fraction (LVEF), with a higher LVEF being observed in women. We sought to assess the clinical relevance of an increased LVEF in women and men. METHODS AND RESULTS: A total of 4632 patients from the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry (44.8% women; mean age 58.7 ± 13.2 years in men and 59.5 ± 13.3 years in women, P = 0.05), in whom LVEF was measured by cardiac computed tomography, were categorized according to LVEF (low <55%, normal 55-65%, and high >65%). The prevalence of high LVEF was similar in both sexes (33.5% in women and 32.5% in men, P = 0.46). After 6 years of follow-up, no difference in mortality was observed in patients with high LVEF in the overall cohort (P = 0.41). When data were stratified by sex, women with high LVEF died more often from any cause as compared to women with normal LVEF (8.6% vs. 7.1%, log rank P = 0.032), while an opposite trend was observed in men (5.8% vs. 6.8% in normal LVEF, log rank P = 0.89). Accordingly, a first order interaction term of male sex and high LVEF was significant (hazard ratios 0.63, 95% confidence intervals 0.41-0.98, P = 0.043) in a Cox regression model of all-cause mortality adjusted for age, cardiovascular risk factors, and severity of coronary artery disease (CAD). CONCLUSION: Increased LVEF is highly prevalent in patients referred for evaluation of CAD and is associated with an increased risk of death in women, but not in men. Differentiating between normal and hyperdynamic left ventricles might improve risk stratification in women with CAD. CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT01443637.

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.

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.