Relationship Between Coronary Artery Calcium and Atherosclerosis Progression Among Patients With Suspected Coronary Artery Disease

BackgroundAmong symptomatic patients, it remains unclear whether a coronary artery calcium (CAC) score alone is sufficient or misses a sizeable burden and progressive risk associated with obstructive and nonobstructive atherosclerotic plaque.ObjectivesAmong patients with low to high CAC scores, our aims were to quantify co-occurring obstructive and nonobstructive noncalcified plaque and serial progression of atherosclerotic plaque volume.MethodsA total of 698 symptomatic patients with suspected coronary artery disease (CAD) underwent serial coronary computed tomographic angiography (CTA) performed 3.5 to 4.0 years apart. Atherosclerotic plaque was quantified, including by compositional subgroups. Obstructive CAD was defined as ≥50% stenosis. Multivariate linear regression models were used to measure atherosclerotic plaque progression by CAC scores. Cox proportional hazard models estimated CAD event risk (median of 10.7 years of follow-up).ResultsAcross baseline CAC scores from 0 to ≥400, total plaque volume ranged from 30.4 to 522.4 mm³ (P < 0.001) and the prevalence of obstructive CAD increased from 1.4% to 49.1% (P < 0.001). Of those with a 0 CAC score, 97.9% of total plaque was noncalcified. Among patients with baseline CAC <100, nonobstructive CAD was prevalent (40% and 89% in CAC scores of 0 and 1-99), with plaque largely being noncalcified. On the follow-up coronary CTA, volumetric plaque growth (P < 0.001) and the development of new or worsening stenosis (P < 0.001) occurred more among patients with baseline CAC ≥100. Progression varied compositionally by baseline CAC scores. Patients with no CAC had disproportionate growth in noncalcified plaque, and for every 1 mm³ increase in calcified plaque, there was a 5.5 mm³ increase in noncalcified plaque volume. By comparison, patients with CAC scores of ≥400 exhibited disproportionate growth in calcified plaque with a volumetric increase 15.7-fold that of noncalcified plaque. There was a graded increase in CAD event risk by the CAC with rates from 3.3% for no CAC to 21.9% for CAC ≥400 (P < 0.001).ConclusionsCAC imperfectly characterizes atherosclerotic disease burden, but its subgroups exhibit pathogenic patterns of early to advanced disease progression and stratify long-term prognostic risk.     

Machine Learning Adds to Clinical and CAC Assessments in Predicting 10-Year CHD and CVD Deaths

ObjectivesThe aim of this study was to evaluate whether machine learning (ML) of noncontrast computed tomographic (CT) and clinical variables improves the prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) deaths compared with coronary artery calcium (CAC) Agatston scoring and clinical data.BackgroundThe CAC score provides a measure of the global burden of coronary atherosclerosis, and its long-term prognostic utility has been consistently shown to have incremental value over clinical risk assessment. However, current approaches fail to integrate all available CT and clinical variables for comprehensive risk assessment.MethodsThe study included data from 66,636 asymptomatic subjects (mean age 54 ± 11 years, 67% men) without established ASCVD undergoing CAC scanning and followed for cardiovascular disease (CVD) and CHD deaths at 10 years. Clinical risk assessment incorporated the ASCVD risk score. For ML, an ensemble boosting approach was used to fit a predictive classifier for outcomes, followed by automated feature selection using information gain ratio. The model-building process incorporated all available clinical and CT data, including the CAC score; the number, volume, and density of CAC plaques; and extracoronary scores; comprising a total of 77 variables. The overall proposed model (ML all) was evaluated using a 10-fold cross-validation framework on the population data and area under the curve (AUC) as metrics. The prediction performance was also compared with 2 traditional scores (ASCVD risk and CAC score) and 2 additional models that were trained using all the clinical data (ML clinical) and CT variables (ML CT).ResultsThe AUC by ML all (0.845) for predicting CVD death was superior compared with those obtained by ASCVD risk alone (0.821), CAC score alone (0.781), and ML CT alone (0.804) (p < 0.001 for all). Similarly, for predicting CHD death, AUC by ML all (0.860) was superior to the other analyses (0.835 for ASCVD risk, 0.816 for CAC, and 0.827 for ML CT; p < 0.001).ConclusionsThe comprehensive ML model was superior to ASCVD risk, CAC score, and an ML model fitted using CT variables alone in the prediction of both CVD and CHD death.     

Prognostic Value of Quantitative Metrics From Positron Emission Tomography in Ischemic Heart Failure

ObjectivesThe aim of this study was to investigate the prognostic and clinical value of quantitative positron emission tomographic (PET) metrics in patients with ischemic heart failure.BackgroundAlthough myocardial flow reserve (MFR) is a strong predictor of cardiac risk in patients without heart failure, it is unknown whether quantitative PET metrics improve risk stratification in patients with ischemic heart failure.MethodsThe study included 254 patients referred for stress and rest myocardial perfusion imaging and viability testing using PET. Major adverse cardiac event(s) (MACE) consisted of death, resuscitated sudden cardiac death, heart transplantation, acute coronary syndrome, hospitalization for heart failure, and late revascularization.ResultsMACE occurred in 170 patients (67%) during a median follow-up of 3.3 years. In a multivariate Cox proportional hazards model including multiple quantitative PET metrics, only MFR predicted MACE significantly (p = 0.013). Beyond age, symptom severity, diabetes mellitus, previous myocardial infarction or revascularization, 3-vessel disease, renal insufficiency, ejection fraction, as well as presence and burden of ischemia, scar, and hibernating myocardium, MFR was strongly associated with MACE (adjusted hazard ratio per increase in MFR by 1: 0.63; 95% confidence interval: 0.45 to 0.91). Incorporation of MFR into a risk assessment model incrementally improved the prediction of MACE (likelihood ratio chi-square test [16] = 48.61 vs. chi-square test [15] = 39.20; p = 0.002).ConclusionsIn this retrospective analysis of a single-center cohort, quantitative PET metrics of myocardial blood flow all improved risk stratification in patients with ischemic heart failure. However, in a hypothesis-generating analysis, MFR appears modestly superior to the other metrics as a prognostic index.     

Myocardial Flow Reserve and Coronary Calcification in Prognosis of Patients With Suspected Coronary Artery Disease

ObjectivesThe aim of this analysis is to examine the incremental prognostic value of coronary artery calcium (CAC) score and myocardial flow reserve (MFR) in patients with suspected coronary artery disease (CAD) undergoing positron emission tomography (PET) myocardial perfusion imaging (MPI).BackgroundAdvances in cardiac PET and computed tomography imaging enabled the simultaneous acquisition of anatomic and physiological data for patients suspected of CAD.MethodsConsecutive patients who underwent PET MPI and CAC score calculation at King Abdulaziz Cardiac Center, Riyadh, Saudi Arabia, between May 2011 and May 2018 were included in the study. MPI and CAC images were obtained in the same setting. The primary endpoint of the study was a composite of cardiac death and nonfatal myocardial infarction. Cox proportional hazard regression was used to assess the incremental prognostic value of CAC and MFR by sequentially adding the variables to a model that included clinical and PET variables.ResultsA total of 4,008 patients (mean age 59.7 ± 11.6 years, 55% women) were included in the analysis. Risk factors were prevalent (77.6% hypertension, 58.1% diabetes). In total, 35.9% of the cohort had CAC of 0, 16.5% had CAC ≥400, and 43.9% had MFR <2. Over a median follow up of 1.9 years, 130 (3.2%) patients had cardiac death/nonfatal myocardial infarction. CAC and MFR score added incremental prognostic value over clinical and perfusion variables (base model: c-index 0.8137; Akaike information criterion [AIC]: 1,865.877; p = 0.0011; CAC model: c-index = 0.8330; AIC: 1,850.810; p = 0.045 vs. base model; MFR model: c-index = 0.8279; AIC: 1,859.235; p = 0.024). Combining CAC and MFR did not enhance risk prediction (c-index = 0.8435; AIC: 1,846.334; p = 0.074 vs. MFR model; p = 0.21 vs. CAC model.)ConclusionsIn this large cohort of patients referred for PET MPI, both CAC and MFR independently added incremental prognostic value over clinical and MPI variables. Although combining both may have synergetic prognostic effect, this relation was not shown in multivariable model of this analysis.     

On the association between circulating biomarkers and atherosclerotic calcification in a cohort of arterial disease participants

Background and aimsAtherosclerotic calcification is a powerful predictor of cardiovascular disease. This study aims to determine whether circulating levels of a local/systemic calcification inhibitor or a marker of bone formation correlate with measures of coronary or extracoronary calcification.Methods and resultsClinical computed tomography (CT) was performed on 64 arterial disease participants undergoing carotid and lower extremity endarterectomy. Coronary artery calcium (CAC) scores and volumes were acquired from the CT scans (n = 42). CAC scores and volumes were used to derive CAC density scores. Micro-CT was performed on excised carotid (n = 36) and lower extremity (n = 31) plaques to quantify the volume and volume fraction of extracoronary calcification. Circulating levels of dephospho-uncarboxylated Matrix Gla Protein (dp-ucMGP), fetuin-A, carboxylated and uncarboxylated osteocalcin (ucOC) were quantified using commercial immunoassays. Carotid participant CAC density scores were moderately negatively correlated with plasma dp-ucMGP (r_s = ?0.592, P = 0.008). A weak negative association was found between CAC scores and %ucOC for all participants (r_s = ?0.335, P = 0.040). Another weak negative correlation was observed between fetuin-A and the volume of calcification within excised carotid specimens (r_s = ?0.366, P = 0.031). Despite substantial differences in coronary and extracoronary calcium measurements, the levels of circulating biomarkers did not vary significantly between carotid and lower extremity subgroups.ConclusionCorrelations identified between circulating biomarkers and measures of coronary and extracoronary calcium were not consistent among participant subgroups. Further research is required to determine the association between circulating biomarkers, coronary and extracoronary calcium.     

Coronary Artery Calcium for Risk Stratification of Sudden Cardiac Death: The Coronary Artery Calcium Consortium

BackgroundCoronary artery calcium (CAC) is a marker of plaque burden. Whether CAC improves risk stratification for incident sudden cardiac death (SCD) beyond atherosclerotic cardiovascular disease (ASCVD) risk factors is unknown.ObjectivesSCD is a common initial manifestation of coronary heart disease (CHD); however, SCD risk prediction remains elusive.MethodsThe authors studied 66,636 primary prevention patients from the CAC Consortium. Multivariable competing risks regression and C-statistics were used to assess the association between CAC and SCD, adjusting for demographics and traditional risk factors.ResultsThe mean age was 54.4 years, 33% were women, 11% were of non-White ethnicity, and 55% had CAC >0. A total of 211 SCD events (0.3%) were observed during a median follow-up of 10.6 years, 91% occurring among those with baseline CAC >0. Compared with CAC = 0, there was a stepwise higher risk (P trend < 0.001) in SCD for CAC 100 to 399 (subdistribution hazard ratio [SHR]: 2.8; 95% CI: 1.6-5.0), CAC 400 to 999 (SHR: 4.0; 95% CI: 2.2-7.3), and CAC >1,000 (SHR: 4.9; 95% CI: 2.6-9.9). CAC provided incremental improvements in the C-statistic for the prediction of SCD among individuals with a 10-year risk <7.5% (ΔC-statistic = +0.046; P = 0.02) and 7.5% to 20% (ΔC-statistic = +0.069; P = 0.003), which were larger when compared with persons with a 10-year risk >20% (ΔC-statistic = +0.01; P = 0.54).ConclusionsHigher CAC burden strongly associates with incident SCD beyond traditional risk factors, particularly among primary prevention patients with low-intermediate risk. SCD risk stratification can be useful in the early stages of CHD through the measurement of CAC, identifying patients most likely to benefit from further downstream testing.     

Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry

ObjectivesThis study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning–based coronary computed tomography (CT) angiography (cCTA)–derived fractional flow reserve (CT-FFR).BackgroundCT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated.MethodsA total of 482 vessels from 314 patients (age 62.3 ± 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and ≥400) on a per-vessel level with invasive FFR as the reference standard.ResultsThe diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC ≥400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC ≥ 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001).ConclusionsMachine-learning–based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621).     

Interplay of Risk Factors and Coronary Artery Calcium for CHD Risk in Young Patients

ObjectivesThe aim of this study was to examine prevalence, predictors, and impact of coronary artery calcium (CAC) across different risk factor burdens on the prevalence of obstructive coronary artery disease (CAD) and future coronary heart disease (CHD) risk in young patients.BackgroundThe interplay of risk factors and CAC for predicting CHD in young patients aged ≤45 years is not clear.MethodsThe study included 3,691 symptomatic patients (18-45 years of age) from the WDHR (Western Denmark Heart Registry) undergoing coronary computed tomographic angiography. CHD events were myocardial infarction and late revascularization.ResultsDuring a median of 4.1 years of follow-up, 57 first-time CHD events occurred. In total, 3,180 patients (86.1%) had CAC = 0 and 511 patients (13.9%) had CAC >0. Presence of CAC increased with number of risk factors (odds ratio: 4.5 [95% CI: 2.7-7.3] in patients with >3 vs 0 risk factors). The prevalence of obstructive CAD at baseline and the rate of future CHD events increased in a stepwise manner with both higher CAC and number of risk factors. The CHD event rate was lowest at 0.5 (95% CI: 0.1-3.6) per 1,000 person-years in patients with 0 risk factors and CAC = 0. Among patients with >3 risk factors, the event rate was 3.1 (95% CI: 1.0-9.7) in patients with CAC = 0 compared with 36.3 (95% CI: 17.3-76.1) in patients with CAC >10.ConclusionsIn young patients, there is a strong interplay between CAC and risk factors for predicting the presence of obstructive CAD and for future CHD risk. In the presence of risk factors, even a low CAC score is a high-risk marker. These results demonstrate the importance of assessing risk factors and CAC simultaneously when assessing risk in young patients.     

Warranty Period of a Calcium Score of Zero: Comprehensive Analysis From MESA

ObjectivesThis study sought to quantify and model conversion of a normal coronary artery calcium (CAC) scan to an abnormal CAC scan.BackgroundAlthough the absence of CAC is associated with excellent prognosis, progression to CAC >0 confers increased risk. The time interval for repeated scanning remains poorly defined.MethodsThis study included 3,116 participants from the MESA (Multi-Ethnic Study of Atherosclerosis) with baseline CAC = 0 and follow-up scans over 10 years after baseline. Prevalence of incident CAC, defined by thresholds of CAC >0, CAC >10, or CAC >100, was calculated and time to progression was derived from a Weibull parametric survival model. Warranty periods were modeled as a function of sex, race/ethnicity, cardiovascular risk, and desired yield of repeated CAC testing. Further analysis was performed of the proportion of coronary events occurring in participants with baseline CAC = 0 that preceded and followed repeated CAC testing at different time intervals.ResultsMean participants’ age was 58 ± 9 years, with 63% women, and mean 10-year cardiovascular risk of 14%. Prevalence of CAC >0, CAC >10, and CAC >100 was 53%, 36%, and 8%, respectively, at 10 years. Using a 25% testing yield (number needed to scan [NNS] = 4), the estimated warranty period of CAC >0 varied from 3 to 7 years depending on sex and race/ethnicity. Approximately 15% of participants progressed to CAC >10 in 5 to 8 years, whereas 10-year progression to CAC >100 was rare. Presence of diabetes was associated with significantly shorter warranty period, whereas family history and smoking had small effects. A total of 19% of all 10-year coronary events occurred in CAC = 0 prior to performance of a subsequent scan at 3 to 5 years, whereas detection of new CAC >0 preceded 55% of future events and identified individuals at 3-fold higher risk of coronary events.ConclusionsIn a large population of individuals with baseline CAC = 0, study data provide a robust estimation of the CAC = 0 warranty period, considering progression to CAC >0, CAC >10, and CAC >100 and its impact on missed versus detectable 10-year coronary heart disease events. Beyond age, sex, race/ethnicity, diabetes also has a significant impact on the warranty period. The study suggests that evidence-based guidance would be to consider rescanning in 3 to 7 years depending on individual demographics and risk profile.     

Development of a risk score for patients with ischaemic cardiomyopathy

BackgroundIschaemic cardiomyopathy is a leading cause of heart failure and is associated with a poor prognosis.AimTo evaluate predictors of major adverse cardiovascular events (MACE) and to develop a risk score for the disease.MethodsAll patients with ischaemic cardiomyopathy referred to a tertiary hospital between 2010 and 2018 for stress-rest gated single-photon emission computed tomography (SPECT) were included retrospectively (n = 747). Clinical and gated SPECT-derived variables were analysed as predictors of MACE, a combined endpoint of cardiovascular mortality, heart failure hospitalization or myocardial infarction during follow-up. A multivariable Cox model using backwards stepwise regression with competing risks was used to select the best parsimonious model.ResultsAfter a median follow-up of 4.7 years, 313 patients had MACE (41.9%). Independent predictors of MACE were previous heart failure admission, worsening angina or dyspnoea, estimated glomerular filtration rate ≤60 mL/min/1.73 m², age > 73 years, diabetes, atrial fibrillation, end-diastolic volume index > 83 mL/m² and > 12% of scarred myocardium. A risk score ranging from 0 to 12 classified patients as at intermediate risk (event rate of 4.0 MACE per 100 person-years), high risk (11.3 MACE per 100 person-years) or very high risk (27.8 MACE per 100 person-years). The internally validated area under the curve was 0.720 (95% confidence interval 0.660–0.740) and calibration was adequate (Hosmer-Lemeshow test P = 0.28) for MACE.ConclusionsIn patients with ischaemic cardiomyopathy, a simple risk score using dichotomic and readily available variables obtained from clinical assessment and gated SPECT accurately predicts the risk of MACE.     

Diagnostic Accuracy of FDG PET/CT in Suspected LVAD Infections: A Case Series,Systematic Review,and Meta-Analysis

ObjectivesThe purpose of this study was to describe our experience with fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography computed tomography (PET/CT) in diagnosing left ventricular assist device (LVAD) infections and perform a meta-analysis of published studies to determine overall diagnostic accuracy.BackgroundDevice-related infections are a common complication of LVADs and are linked to worse outcomes. Diagnosis of LVAD infections remains challenging. FDG PET/CT has demonstrated good diagnostic accuracy in several other infectious conditions.MethodsThis was a single-center, retrospective case series of FDG PET/CT scans in suspected LVAD infection between September 2015 and February 2018. A systematic review of PubMed from database inception through March 2018 was also conducted to identify additional studies.ResultsNineteen FDG PET/CT scans were identified for the retrospective case series. The systematic review identified an additional 3 publications, for a total of 4 studies involving 119 scans assessing diagnostic performance. Axial (n = 36) and centrifugal (n = 83) flow LVADs were represented. Pooled sensitivity was 92% (95% confidence interval [CI]: 82% to 97%) and specificity was 83% (95% CI: 24% to 99%) for FDG PET/CT in diagnosing LVAD infections. Summary receiver-operating characteristic curve analysis demonstrated an AUC of 0.94 (95% CI: 0.91 to 0.95).ConclusionsFDG PET/CT for suspected LVAD infections demonstrates good diagnostic accuracy, with overall high sensitivity but variable specificity.     

Mean Versus Peak Coronary Calcium Density on Non-Contrast CT: Calcium Scoring and ASCVD Risk Prediction

ObjectivesThis study sought to assess the relationship between mean vs peak calcified plaque density and their impact on calculating coronary artery calcium (CAC) scores and to compare the corresponding differential prediction of atherosclerotic cardiovascular disease (ASCVD) and coronary heart disease (CHD) mortality.BackgroundThe Agatston CAC score is quantified per lesion as the product of plaque area and a 4-level categorical peak calcium density factor. However, mean calcium density may more accurately measure the heterogenous mixture of lipid-rich, fibrous, and calcified plaque reflective of ASCVD risk.MethodsWe included 10,373 individuals from the CAC Consortium who had CAC >0 and per-vessel measurements of peak calcium density factor and mean calcium density. Area under the curve and continuous net reclassification improvement analyses were performed for CHD and ASCVD mortality to compare the predictive abilities of mean calcium density vs peak calcium density factor when calculating the Agatston CAC score.ResultsParticipants were on average 53.4 years of age, 24.4% were women, and the median CAC score was 68 Agatston units. The average values for mean calcium density and peak calcium density factor were 210 ± 50 HU and 3.1 ± 0.5, respectively. Individuals younger than 50 years of age and/or those with a total plaque area <100 mm² had the largest differences between the peak and mean density measures. Among persons with CAC 1-99, the use of mean calcium density resulted in a larger improvement in ASCVD mortality net reclassification improvement (NRI) (NRI = 0.49; P < 0.001 vs. NRI = 0.18; P = 0.08) and CHD mortality discrimination (Δ area under the curve (AUC) = +0.169 vs +0.036; P < 0.001) compared with peak calcium density factor. Neither peak nor mean calcium density improved mortality prediction at CAC scores >100.ConclusionMean and peak calcium density may differentially describe plaque composition early in the atherosclerotic process. Mean calcium density performs better than peak calcium density factor when combined with plaque area for ASCVD mortality prediction among persons with Agatston CAC 1-99.     

Thoracic Aortic 18F-Sodium Fluoride Activity and Ischemic Stroke in Patients With Established Cardiovascular Disease

BackgroundAortic atherosclerosis represents an important contributor to ischemic stroke risk. Identifying patients with high-risk aortic atheroma could improve preventative treatment strategies for future ischemic stroke.ObjectivesThe purpose of this study was to investigate whether thoracic ¹⁸F-sodium fluoride positron emission tomography (PET) could improve the identification of patients at the highest risk of ischemic stroke.MethodsIn a post hoc observational cohort study, we quantified thoracic aortic and coronary ¹⁸F-sodium fluoride activity in 461 patients with stable cardiovascular disease undergoing PET combined with computed tomography (CT). Progression of atherosclerosis was assessed by change in aortic and coronary CT calcium volume. Clinical outcomes were determined by the occurrence of ischemic stroke and myocardial infarction. We compared the prognostic utility of ¹⁸F-sodium fluoride activity for predicting stroke to clinical risk scores and CT calcium quantification using survival analysis and multivariable Cox regression.ResultsAfter 12.7 ± 2.7 months, progression of thoracic aortic calcium volume correlated with baseline thoracic aortic ¹⁸F-sodium fluoride activity (n = 140; r = 0.31; P = 0.00016). In 461 patients, 23 (5%) patients experienced an ischemic stroke and 32 (7%) a myocardial infarction after 6.1 ± 2.3 years of follow-up. High thoracic aortic ¹⁸F-sodium fluoride activity was strongly associated with ischemic stroke (HR: 10.3 [95% CI: 3.1-34.8]; P = 0.00017), but not myocardial infarction (P = 0.40). Conversely, high coronary ¹⁸F-sodium fluoride activity was associated with myocardial infarction (HR: 4.8 [95% CI: 1.9-12.2]; P = 0.00095) but not ischemic stroke (P = 0.39). In a multivariable Cox regression model including imaging and clinical risk factors, thoracic aortic ¹⁸F-sodium fluoride activity was the only variable associated with ischemic stroke (HR: 8.19 [95% CI: 2.33-28.7], P = 0.0010).ConclusionsIn patients with established cardiovascular disease, thoracic aortic ¹⁸F-sodium fluoride activity is associated with the progression of atherosclerosis and future ischemic stroke. Arterial ¹⁸F-sodium fluoride activity identifies localized areas of atherosclerotic disease activity that are directly linked to disease progression and downstream regional clinical atherothrombotic events. (DIAMOND–Dual Antiplatelet Therapy to Reduce Myocardial Injury [DIAMOND], NCT02110303; Study Investigating the Effect of Drugs Used to Treat Osteoporosis on the Progression of Calcific Aortic Stenosis [SALTIRE II], NCT02132026; Novel Imaging Approaches To Identify Unstable Coronary Plaques, NCT01749254; and Role of Active Valvular Calcification and Inflammation in Patients With Aortic Stenosis, NCT01358513)     

Somatostatin Receptor PET/MR Imaging of Inflammation in Patients With Large Vessel Vasculitis and Atherosclerosis

BackgroundAssessing inflammatory disease activity in large vessel vasculitis (LVV) can be challenging by conventional measures.ObjectivesWe aimed to investigate somatostatin receptor 2 (SST₂) as a novel inflammation-specific molecular imaging target in LVV.MethodsIn a prospective, observational cohort study, in vivo arterial SST₂ expression was assessed by positron emission tomography/magnetic resonance imaging (PET/MRI) using ⁶⁸Ga-DOTATATE and ¹⁸F-FET-βAG-TOCA. Ex vivo mapping of the imaging target was performed using immunofluorescence microscopy; imaging mass cytometry; and bulk, single-cell, and single-nucleus RNA sequencing.ResultsSixty-one participants (LVV: n = 27; recent atherosclerotic myocardial infarction of ≤2 weeks: n = 25; control subjects with an oncologic indication for imaging: n = 9) were included. Index vessel SST₂ maximum tissue-to-blood ratio was 61.8% (P < 0.0001) higher in active/grumbling LVV than inactive LVV and 34.6% (P = 0.0002) higher than myocardial infarction, with good diagnostic accuracy (area under the curve: ≥0.86; P < 0.001 for both). Arterial SST₂ signal was not elevated in any of the control subjects. SST₂ PET/MRI was generally consistent with ¹⁸F-fluorodeoxyglucose PET/computed tomography imaging in LVV patients with contemporaneous clinical scans but with very low background signal in the brain and heart, allowing for unimpeded assessment of nearby coronary, myocardial, and intracranial artery involvement. Clinically effective treatment for LVV was associated with a 0.49 ± 0.24 (standard error of the mean [SEM]) (P = 0.04; 22.3%) reduction in the SST₂ maximum tissue-to-blood ratio after 9.3 ± 3.2 months. SST₂ expression was localized to macrophages, pericytes, and perivascular adipocytes in vasculitis specimens, with specific receptor binding confirmed by autoradiography. SSTR2-expressing macrophages coexpressed proinflammatory markers.ConclusionsSST₂ PET/MRI holds major promise for diagnosis and therapeutic monitoring in LVV. (PET Imaging of Giant Cell and Takayasu Arteritis [PITA], NCT04071691; Residual Inflammation and Plaque Progression Long-Term Evaluation [RIPPLE], NCT04073810)     

Risk Assessment of Coronary Obstruction During Transcatheter Aortic Valve Replacement: Insights From Post-BASILICA Computed Tomography

ObjectivesThe aim of this study was to examine the predictive value of preprocedural computed tomography (CT)–based risk stratification of coronary obstruction during transcatheter aortic valve replacement (TAVR) on the basis of geometric measurements on postprocedural CT.BackgroundProper patient selection for additional procedures to prevent coronary obstruction during TAVR has not been adequately evaluated.MethodsPre- and postprocedural computed tomographic scans of 28 patients treated using bioprosthetic or native aortic scallop intentional laceration to prevent iatrogenic coronary artery obstruction (BASILICA) and TAVR were analyzed. Using the postprocedural computed tomographic images, threatened coronary obstruction (TCO) was defined as: 1) ostial obstruction (adherence of the transcatheter heart valve [THV] to the coronary ostium with leaflet extension above the ostium); and/or 2) sinus sequestration (THV adherence to the sinotubular junction [STJ] with leaflet extension above the STJ) and was substratified into complete and incomplete types.ResultsA total of 51 leaflets were evaluated (88% surgical tissue valves) after excluding leaflets not visible on CT (n = 5). On postprocedural CT, complete TCO was observed in 25.4% (13 of 51 leaflets). On preprocedural CT, leaflets were at high risk for complete TCO (incidence 53%) if the virtual THV–to–coronary distance (VTC) was <3.0 mm, or if the virtual THV–to–STJ distance (VTSTJ) was <1.0 mm with STJ height ? leaflet length <0 mm (leaflet-STJ mismatch). Leaflets were at low risk (incidence 0%) if the VTC was ≥3 mm and VTSTJ was ≥3.0 mm or STJ height ? leaflet length was ≥+2.0 mm. Of 28 leaflets treated using BASILICA, complete TCO was seen in 35.7% (n = 10), due to sinus sequestration (100%) with coexisting ostial obstruction (30%). Actual coronary events occurred in 7.1% (n = 2) because of leaflet prolapse, corresponding to an absolute risk reduction by BASILICA of 29% (P = 0.021).ConclusionsRisk assessment of coronary obstruction after TAVR may improve with a multiparametric approach incorporating VTC, VTSTJ, and leaflet-STJ mismatch. BASILICA appeared to reduce actual coronary events even in leaflets with anticipated coronary obstruction.     

Noninvasive In Vivo Coronary Artery Thrombus Imaging

BackgroundThe diagnosis and management of myocardial infarction are increasingly complex, and establishing the presence of intracoronary thrombosis has major implications for both the classification and treatment of myocardial infarction.ObjectivesThe aim of this study was to investigate whether positron emission tomographic (PET) and computed tomographic (CT) imaging could noninvasively detect in vivo thrombus formation in human coronary arteries using a novel glycoprotein IIb/IIIa receptor antagonist–based radiotracer, ¹⁸F-GP1.MethodsIn a single-center observational case-control study, patients with or without acute myocardial infarction underwent coronary ¹⁸F-GP1 PET/CT angiography. Coronary artery ¹⁸F-GP1 uptake was assessed visually and quantified using maximum target-to-background ratios.Results¹⁸F-GP1 PET/CT angiography was performed in 49 patients with and 50 patients without acute myocardial infarction (mean age: 61 ± 9 years, 75% men). Coronary ¹⁸F-GP1 uptake was apparent in 39 of the 49 culprit lesions (80%) in patients with acute myocardial infarction. False negative results appeared to relate to time delays to scan performance and low thrombus burden in small-caliber distal arteries. On multivariable regression analysis, culprit vessel status was the only independent variable associated with higher ¹⁸F-GP1 uptake. Extracoronary cardiac ¹⁸F-GP1 findings included a high frequency of infarct-related intramyocardial uptake (35%) as well as left ventricular (8%) or left atrial (2%) thrombus.ConclusionsCoronary ¹⁸F-GP1 PET/CT angiography is the first noninvasive selective technique to identify in vivo coronary thrombosis in patients with acute myocardial infarction. This novel approach can further define the role and location of thrombosis within the heart and has the potential to inform the diagnosis, management, and treatment of patients with acute myocardial infarction. (In-Vivo Thrombus Imaging With ¹⁸F-GP1, a Novel Platelet PET Radiotracer [iThrombus]; NCT03943966)     

Acute Response in the Noninfarcted Myocardium Predicts Long-Term Major Adverse Cardiac Events After STEMI

BackgroundAcute ST-segment elevation myocardial infarction (STEMI) has effects on the myocardium beyond the immediate infarcted territory. However, pathophysiologic changes in the noninfarcted myocardium and their prognostic implications remain unclear.ObjectivesThe purpose of this study was to evaluate the long-term prognostic value of acute changes in both infarcted and noninfarcted myocardium post-STEMI.MethodsPatients with acute STEMI undergoing primary percutaneous coronary intervention underwent evaluation with blood biomarkers and cardiac magnetic resonance (CMR) at 2 days and 6 months, with long-term follow-up for major adverse cardiac events (MACE). A comprehensive CMR protocol included cine, T2-weighted, T21, T1-mapping, and late gadolinium enhancement (LGE) imaging. Areas without LGE were defined as noninfarcted myocardium. MACE was a composite of cardiac death, sustained ventricular arrhythmia, and new-onset heart failure.ResultsTwenty-two of 219 patients (10%) experienced an MACE at a median of 4 years (IQR: 2.5-6.0 years); 152 patients returned for the 6-month visit. High T1 (>1250 ms) in the noninfarcted myocardium was associated with lower left ventricular ejection fraction (LVEF) (51% ± 8% vs 55% ± 9%; P = 0.002) and higher NT-pro-BNP levels (290 pg/L [IQR: 103-523 pg/L] vs 170 pg/L [IQR: 61-312 pg/L]; P = 0.008) at 6 months and a 2.5-fold (IQR: 1.03-6.20) increased risk of MACE (2.53 [IQR: 1.03-6.22]), compared with patients with normal T1 in the noninfarcted myocardium (P = 0.042). A lower T1 (<1,300 ms) in the infarcted myocardium was associated with increased MACE (3.11 [IQR: 1.19-8.13]; P = 0.020). Both noninfarct and infarct T1 were independent predictors of MACE (both P = 0.001) and significantly improved risk prediction beyond LVEF, infarct size, and microvascular obstruction (C-statistic: 0.67 ± 0.07 vs 0.76 ± 0.06, net-reclassification index: 40% [IQR: 12%-64%]; P = 0.007).ConclusionsThe acute responses post-STEMI in both infarcted and noninfarcted myocardium are independent incremental predictors of long-term MACE. These insights may provide new opportunities for treatment and risk stratification in STEMI.     

18F-FDG-Based Radiomics and Machine Learning: Useful Help for Aortic Prosthetic Valve Infective Endocarditis Diagnosis?

BackgroundFluorine-18 fluorodeoxyglucose (¹⁸F-FDG)-positron emission tomography (PET)/computed tomography (CT) results in better sensitivity for prosthetic valve endocarditis (PVE) diagnosis, but visual image analysis results in relatively weak specificity and significant interobserver variability.ObjectivesThe primary objective of this study was to evaluate the performance of a radiomics and machine learning–based analysis of ¹⁸F-FDG PET/CT (PET-ML) as a major criterion for the European Society of Cardiology score using machine learning as a major imaging criterion (ESC-ML) in PVE diagnosis. The secondary objective was to assess performance of PET-ML as a standalone examination.MethodsAll ¹⁸F-FDG-PET/CT scans performed for suspected aortic PVE at a single center from 2015 to 2021 were retrospectively included. The gold standard was expert consensus after at least 3 months’ follow-up. The machine learning (ML) method consisted of manually segmenting each prosthetic valve, extracting 31 radiomics features from the segmented region, and training a ridge logistic regressor to predict PVE. Training and hyperparameter tuning were done with a cross-validation approach, followed by an evaluation on an independent test database.ResultsA total of 108 patients were included, regardless of myocardial uptake, and were divided into training (n = 68) and test (n = 40) cohorts. Considering the latter, PET-ML findings were positive for 13 of 22 definite PVE cases and 3 of 18 rejected PVE cases (59% sensitivity, 83% specificity), thus leading to an ESC-ML sensitivity of 72% and a specificity of 83%.ConclusionsThe use of ML for analyzing ¹⁸F-FDG-PET/CT images in PVE diagnosis was feasible and beneficial, particularly when ML was included in the ESC 2015 criteria. Despite some limitations and the need for future developments, this approach seems promising to optimize the role of ¹⁸F-FDG PET/CT in PVE diagnosis.