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Prognostic value of coronary artery calcium score in symptomatic individuals: A meta-analysis of 34,000 subjects.
Lo-Kioeng-Shioe, MS, Rijlaarsdam-Hermsen, D, van Domburg, RT, Hadamitzky, M, Lima, JAC, Hoeks, SE, Deckers, JW
International journal of cardiology. 2020;:56-62
Abstract
BACKGROUND Coronary artery calcium (CAC) scanning has evolved into an important subclinical prediction method for cardiovascular diseases in asymptomatic subjects. However, the prognostic implication of CAC scanning in symptomatic individuals is less clear. OBJECTIVES To assess the prognostic utility of CAC in predicting risk of major adverse cardiac events (MACE) in stable patients with suspected CAD. METHODS We did a systematic electronic literature search for studies presenting original data in CAC score, and reporting cardiovascular events in stable, symptomatic patients as primary outcome. Primary outcome of the meta-analysis was the occurrence of MACE, a composite of late coronary revascularization, hospitalization for unstable angina or heart failure, nonfatal myocardial infarction, and cardiac death or all-cause mortality. Using random effects models, we pooled relative risk ratios of CAC for MACE, and adjusted hazard ratios (HR) of the associations between different CAC strata (CAC 0-100,100-400, and ≥ 400, versus CAC = 0) and incident MACE. RESULTS We included 19 observational studies (n = 34,041). In total, 1601 events were analyzed, of which 158 in patients with CAC = 0. The pooled relative risk ratio was 5.71 (95%-CI: 3.98;8.19) for subjects with CAC > 0. The pooled estimate of adjusted HRs demonstrated increasing, positive associations, with the strongest association for CAC > 400 (HR: 4.88; 95%-CI: 2.44;9.27). CONCLUSIONS This meta-analysis demonstrated that increased levels of CAC are strongly and independently associated with increased risk for MACE in stable, symptomatic patients with suspected CAD, showing increasing risk with greater CAC scores. Application of CAC scanning as a prediction method could be useful for a considerable number of such patients.
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Randomized Comparison Between Everolimus-Eluting Bioresorbable Scaffold and Metallic Stent: Multimodality Imaging Through 3 Years.
Onuma, Y, Honda, Y, Asano, T, Shiomi, H, Kozuma, K, Ozaki, Y, Namiki, A, Yasuda, S, Ueno, T, Ando, K, et al
JACC. Cardiovascular interventions. 2020;(1):116-127
Abstract
OBJECTIVES The aim of this study was to investigate the vascular responses and fates of the scaffold after bioresorbable vascular scaffold (BVS) implantation using multimodality imaging. BACKGROUND Serial comprehensive image assessments after BVS implantation in the context of a randomized trial have not yet been reported. METHODS In the ABSORB Japan trial, 400 patients were randomized to a BVS (n = 266) or a cobalt-chromium everolimus-eluting stent (n = 134). Through 3 years, patients underwent serial angiography and intravascular ultrasound or optical coherence tomography (OCT). RESULTS Luminal dimension at 3 years was consistently smaller with the BVS than with the cobalt-chromium everolimus-eluting stent (mean angiographic minimal luminal diameter 2.04 ± 0.63 mm vs. 2.40 ± 0.56 mm, mean difference -0.37 mm [95% confidence interval: -0.50 to -0.24 mm]; p < 0.001), mainly because of smaller device area (6.13 ± 2.03 mm2 vs. 7.15 ± 2.16 mm2, mean difference -1.04 mm2 [95% confidence interval: -1.66 to -0.42 mm2]; p < 0.001), and larger neointimal area (2.10 ± 0.61 mm2 vs. 1.86 ± 0.64 mm2, mean difference 0.24 mm2 [95% confidence interval: 0.06 to 0.43 mm2]; p = 0.01) by OCT. BVS-treated vessels did not show previously reported favorable vessel responses, such as positive vessel remodeling, late luminal enlargement, and restoration of vasomotion, although the OCT-based healing score was on average zero (interquartile range: 0.00 to 0.00). At 3 years, intraluminal scaffold dismantling (ISD) was observed in 14% of BVS. On serial OCT, ISD was observed in 6 lesions at 2 years, where the struts had been fully apposed at post-procedure, while ISD was observed in 12 lesions at 3 years, where 8 lesions were free from ISD on 2-year OCT. In 5 cases of very late scaffold thrombosis, strut discontinuities were detected in all 4 cases with available OCT immediately before reintervention. CONCLUSIONS In this multimodality serial imaging study, luminal dimension at 3 years was smaller with the BVS than with the cobalt-chromium everolimus-eluting stent. ISD, suspected to be one of the mechanisms of very late BVS thrombosis, was observed in a substantial proportion of cases at 3 years, which developed between post-procedure and 2 years and even beyond 2 years. (AVJ-301 Clinical Trial: A Clinical Evaluation of AVJ-301 [Absorb™ BVS] in Japanese Population [ABSORB JAPAN]; NCT01844284).
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Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study.
Zhang, Y, van der Werf, NR, Jiang, B, van Hamersvelt, R, Greuter, MJW, Xie, X
European radiology. 2020;(2):1285-1294
Abstract
OBJECTIVE To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts. METHODS Three artificial coronary arteries containing nine calcified plaques of different densities (high, medium, and low) and sizes (large, medium, and small) were attached to a moving robotic arm. The artificial arteries moving at 0-90 mm/s were scanned to generate nine categories (each from one calcified plaque) of images with motion artifacts. An inception v3 CNN was fine-tuned and validated. Agatston scores of the predicted classification by CNN were considered as corrected scores. Variation of Agatston scores on moving plaque and by CNN correction was calculated using the scores at rest as reference. RESULTS The overall accuracy of CNN classification was 79.2 ± 6.1% for nine categories. The accuracy was 88.3 ± 4.9%, 75.9 ± 6.4%, and 73.5 ± 5.0% for the high-, medium-, and low-density plaques, respectively. Compared with the Agatston score at rest, the overall median score variation was 37.8% (1st and 3rd quartile, 10.5% and 68.8%) in moving plaques. CNN correction largely decreased the variation to 3.7% (1.9%, 9.1%) (p < 0.001, Mann-Whitney U test) and improved the sensitivity (percentage of non-zero scores among all the scores) from 65 to 85% for detection of coronary calcifications. CONCLUSIONS In this experimental study, CNN showed the ability to classify motion-induced blurred images and correct calcium scores derived from nontriggered chest CT. CNN correction largely reduces the overall Agatston score variation and increases the sensitivity to detect calcifications. KEY POINTS • A deep CNN architecture trained by CT images of motion artifacts showed the ability to correct coronary calcium scores from blurred images. • A correction algorithm based on deep CNN can be used for a tenfold reduction in Agatston score variations from 38 to 3.7% of moving coronary calcified plaques and to improve the sensitivity from 65 to 85% for the detection of calcifications. • This experimental study provides a method to improve its accuracy for coronary calcium scores that is a fundamental step towards a real clinical scenario.
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The Relationship of Coronary Artery Calcium and Clinical Coronary Artery Disease with Cognitive Function: A Systematic Review and Meta-Analysis.
Xia, C, Vonder, M, Sidorenkov, G, Oudkerk, M, de Groot, JC, van der Harst, P, de Bock, GH, De Deyn, PP, Vliegenthart, R
Journal of atherosclerosis and thrombosis. 2020;(9):934-958
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Abstract
AIM: Coronary artery disease (CAD) and cognitive impairment are common in the elderly, with evidence for shared risk factors and pathophysiological processes. The coronary artery calcium (CAC) score is a marker of subclinical CAD, which may allow early detection of individuals prone to cognitive decline. Prior studies on associations of CAC and clinical CAD with cognitive impairment had discrepant results. This systematic review aims to evaluate the association of (sub)clinical CAD with cognitive function, cognitive decline, and diagnosis of mild cognitive impairment (MCI) or dementia. METHODS A systematic search was conducted in MEDLINE, Embase, and Web of Science until February 2019, supplemented with citations tracking. Two reviewers independently screened studies and extracted information including odds ratios (ORs) and hazard ratios (HRs). RESULTS Forty-six studies, 10 on CAC and 36 on clinical CAD, comprising 1,248,908 participants were included in the systematic review. Studies about associations of (sub)clinical CAD with cognitive function and cognitive decline had heterogeneous methodology and inconsistent findings. Two population-based studies investigated the association between CAC and risk of dementia over 6-12.2 years using different CAC scoring methods. Both found a tendency toward higher risk of dementia as CAC severity increased. Meta-analysis in 15 studies (663,250 individuals) showed an association between CAD and MCI/dementia (pooled OR 1.32, 95%CI 1.17-1.48) with substantial heterogeneity (I2=87.0%, p<0.001). Pooled HR of CAD for incident MCI/dementia over 3.2-25.5 years in six longitudinal studies (70,060 individuals) was 1.51 (95%CI 1.24-1.85), with low heterogeneity (I2=14.1%, p=0.32). Sensitivity analysis did not detect any study that was of particular influence on the pooled OR or HR. CONCLUSIONS Limited evidence suggests the CAC score is associated with risk of dementia. In clinical CAD, risk of MCI and dementia is increased by 50%, as supported by stronger evidence.
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Ischemia and outcome prediction by cardiac CT based machine learning.
Brandt, V, Emrich, T, Schoepf, UJ, Dargis, DM, Bayer, RR, De Cecco, CN, Tesche, C
The international journal of cardiovascular imaging. 2020;(12):2429-2439
Abstract
Cardiac CT using non-enhanced coronary artery calcium scoring (CACS) and coronary CT angiography (cCTA) has been proven to provide excellent evaluation of coronary artery disease (CAD) combining anatomical and morphological assessment of CAD for cardiovascular risk stratification and therapeutic decision-making, in addition to providing prognostic value for the occurrence of adverse cardiac outcome. In recent years, artificial intelligence (AI) and, in particular, the application of machine learning (ML) algorithms, have been promoted in cardiovascular CT imaging for improved decision pathways, risk stratification, and outcome prediction in a more objective, reproducible, and rational manner. AI is based on computer science and mathematics that are based on big data, high performance computational infrastructure, and applied algorithms. The application of ML in daily routine clinical practice may hold potential to improve imaging workflow and to promote better outcome prediction and more effective decision-making in patient management. Moreover, CT represents a field wherein ML may be particularly useful, such as CACS and cCTA. Thus, the purpose of this review is to give a short overview about the contemporary state of ML based algorithms in cardiac CT, as well as to provide clinicians with currently available scientific data on clinical validation and implementation of these algorithms for the prediction of ischemia-specific CAD and cardiovascular outcome.
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Association between debulking area of rotational atherectomy and platform revolution speed-Frequency domain optical coherence tomography analysis.
Mizutani, K, Hara, M, Nakao, K, Yamaguchi, T, Okai, T, Nomoto, Y, Kajio, K, Kaneno, Y, Yamazaki, T, Ehara, S, et al
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions. 2020;(1):E1-E7
Abstract
OBJECTIVES In this study, we sought to investigate the association between revolution speed of rotational atherectomy (RA) and debulking area assessed by frequency domain-optical coherence tomography (FD-OCT). BACKGROUND The number of patients with severe calcified coronary artery disease requiring treatment with calcium ablation, such as RA, is increasing. However, there is little evidence available regarding the association between debulking area and revolution speed during RA. METHODS We retrospectively investigated 30 consecutive severely calcified coronary lesions in 29 patients who underwent RA under FD-OCT guidance. The association between preset revolution speed of RA and burr size-corrected debulking area of the calcified lesion was evaluated using a multivariable regression model with nonlinear restricted-cubic-spline, which can help assess nonlinear associations between variables. RESULTS The median age of study participants was 73 years (quartile 65-78); 82.8% were male. The median burr size was 1.5 mm (1.5-1.75); median total duration of ablation was 120 s (100-180). FD-OCT revealed that the post-procedural minimum lumen area increased significantly from 1.64 mm2 (1.40-2.09) to 2.45 mm2 (2.11-2.98) (p < .001). In addition, the burr size-corrected debulking area increased significantly as the preset revolution speed decreased (p = .018), especially when the revolution speed was less than 150,000 rpm. This result implies that additional lumen gain will be obtained by decreasing rpm when the burr speed is set at <150,000 rpm. CONCLUSIONS FD-OCT demonstrated that RA with lower revolution speed, below 150,000 rpm, has the potential to achieve greater calcium debulking effect in patients with severe calcified coronary lesions.
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Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects.
Eisenberg, E, McElhinney, PA, Commandeur, F, Chen, X, Cadet, S, Goeller, M, Razipour, A, Gransar, H, Cantu, S, Miller, RJH, et al
Circulation. Cardiovascular imaging. 2020;(2):e009829
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BACKGROUND Epicardial adipose tissue (EAT) volume (cm3) and attenuation (Hounsfield units) may predict major adverse cardiovascular events (MACE). We aimed to evaluate the prognostic value of fully automated deep learning-based EAT volume and attenuation measurements quantified from noncontrast cardiac computed tomography. METHODS Our study included 2068 asymptomatic subjects (56±9 years, 59% male) from the EISNER trial (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) with long-term follow-up after coronary artery calcium measurement. EAT volume and mean attenuation were quantified using automated deep learning software from noncontrast cardiac computed tomography. MACE was defined as myocardial infarction, late (>180 days) revascularization, and cardiac death. EAT measures were compared to coronary artery calcium score and atherosclerotic cardiovascular disease risk score for MACE prediction. RESULTS At 14±3 years, 223 subjects suffered MACE. Increased EAT volume and decreased EAT attenuation were both independently associated with MACE. Atherosclerotic cardiovascular disease risk score, coronary artery calcium, and EAT volume were associated with increased risk of MACE (hazard ratio [95%CI]: 1.03 [1.01-1.04]; 1.25 [1.19-1.30]; and 1.35 [1.07-1.68], P<0.01 for all) and EAT attenuation was inversely associated with MACE (hazard ratio, 0.83 [95% CI, 0.72-0.96]; P=0.01), with corresponding Harrell C statistic of 0.76. MACE risk progressively increased with EAT volume ≥113 cm3 and coronary artery calcium ≥100 AU and was highest in subjects with both (P<0.02 for all). In 1317 subjects, EAT volume was correlated with inflammatory biomarkers C-reactive protein, myeloperoxidase, and adiponectin reduction; EAT attenuation was inversely related to these biomarkers. CONCLUSIONS Fully automated EAT volume and attenuation quantification by deep learning from noncontrast cardiac computed tomography can provide prognostic value for the asymptomatic patient, without additional imaging or physician interaction.
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Nonculprit Lesion Plaque Morphology in Patients With ST-Segment-Elevation Myocardial Infarction: Results From the COMPLETE Trial Optical Coherence Tomography Substudys.
Pinilla-Echeverri, N, Mehta, SR, Wang, J, Lavi, S, Schampaert, E, Cantor, WJ, Bainey, KR, Welsh, RC, Kassam, S, Mehran, R, et al
Circulation. Cardiovascular interventions. 2020;(7):e008768
Abstract
BACKGROUND Complete revascularization with routine percutaneous coronary intervention of nonculprit lesions after primary percutaneous coronary intervention improves outcomes in ST-segment-elevation myocardial infarction. Whether this benefit is associated with nonculprit lesion vulnerability is unknown. METHODS In a prospective substudy of the COMPLETEs trial (Complete vs Culprit-Only Revascularization to Treat Multi-Vessel Disease After Early PCI for STEMI), we performed optical coherence tomography of at least 2 coronary arteries before nonculprit lesion percutaneous coronary intervention in 93 patients with ST-segment-elevation myocardial infarction and multivessel disease; and the ST-segment-elevation myocardial infarction culprit vessel if there was unstented segment amenable to imaging. Nonculprit lesions were categorized as obstructive (≥70% stenosis by visual angiographic assessment) or nonobstructive, and as thin-cap fibroatheroma (TCFA) or non-TCFA by optical coherence tomography criteria. TCFA was defined as a lesion with mean fibrous cap thickness <65 μm overlying a lipid arc >90°. RESULTS On a patient level, at least one obstructive TCFA was observed in 44/93 (47%) of patients. On a lesion level, there were 58 TCFAs among 150 obstructive nonculprit lesions compared with 74 TCFAs among 275 nonculprit lesions (adjusted TCFA prevalence: 35.4% versus 23.2%, P=0.022). Compared with obstructive non-TCFAs, obstructive TCFAs had similar lesion length (23.1 versus 20.8 mm, P=0.16) but higher lipid quadrants (55.2 versus 19.2, P<0.001), greater mean lipid arc (203.8° versus 84.5°, P<0.001), and more macrophages (97.1% versus 54.4%, P<0.001) and cholesterol crystals (85.8% versus 44.3%, P<0.001). For nonobstructive lesions, TCFA lesions had similar lesion length (16.7 versus 14.6 mm, P=0.11), but more lipid quadrants (36.4 versus 13.5, P<0.001), and greater mean lipid arc (191.8° versus 84.2°, P<0.001) compared with non-TCFA. CONCLUSIONS Among patients who underwent optical coherence tomography imaging in the COMPLETE trial, nearly 50% had at least one obstructive nonculprit lesion containing complex vulnerable plaque. Obstructive lesions more commonly harbored vulnerable plaque morphology than nonobstructive lesions. This may help explain the benefit of routine percutaneous coronary intervention of obstructive nonculprit lesions in patients with ST-segment-elevation myocardial infarction and multivessel disease. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01740479s.
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The effect of Shexiang Tongxin Dropping Pills on coronary microvascular dysfunction (CMVD) among those with a mental disorder and non-obstructive coronary artery disease based on stress cardiac magnetic resonance images: A study protocol.
Tian, J, Zhang, L, Yang, X, Zuo, H, Zhao, X, Yong, J, He, Y, Song, X
Medicine. 2020;(21):e20099
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Abstract
INTRODUCTION Coronary microvascular dysfunction (CMVD), highly prevalent among patients with a mental disorder (anxiety or depression), is closely related to adverse cardiac events, including hospitalization, sudden cardiac death, and myocardial infarction. Shexiang Tongxin Dropping Pills (STDP), a traditional Chinese medicine, exerts endothelial protective function by anti-inflammation, anti-oxidative stress, and promoting blood circulation. STDP protects against CMVD in previous fundamental studies. The present trial is aiming at evaluating the effect of STDP on CMVD among depressed or anxious patients with non-obstructive coronary artery disease (NOCAD). METHODS AND ANALYSIS Seventy-two depressed or anxious patients diagnosed with NOCAD combined with CMVD utilizing coronary artery angiography and stress cardiac magnetic resonance (CMR) will be recruited in the present study. These patients will be randomized into two groups, namely, Nicorandil group (Nicorandil combined with routine medicine), and STDP groups (STDP combined with routine medicine). The change of CMVD status by assessing absolute myocardial blood flow and myocardial reperfusion using stress CMR 3-month after discharge is defined as the primary endpoint. Major adverse cardiac events (MACEs), quality of life (QOL), and metal disorder improvement are defined as the secondary endpoints. Seattle angina questionnaire (SAQ) which is used to assess angina pectoris and QOL will be recorded at 1-, 3-, 6-, 9-, 12-month of follow-up. Seven-item Generalized Anxiety Disorder Scale (GAD-7) and 9-item depression module from the Patient Health Questionnaire (PHQ9) which utilized to evaluate anxiety and depression, respectively, will be recorded at 1-, 3-, 6-, 9-, 12-month of follow-up. This study will first evaluate the efficacy of STDP on CMVD among patients with a mental disorder and NOCAD, and discuss the potential mechanisms, providing therapeutic evidence for the STDP for these patients.
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Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.
Muscogiuri, G, Van Assen, M, Tesche, C, De Cecco, CN, Chiesa, M, Scafuri, S, Guglielmo, M, Baggiano, A, Fusini, L, Guaricci, AI, et al
BioMed research international. 2020;:6649410
Abstract
Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA analysis can be time consuming, often requiring advanced postprocessing techniques. In consideration of the most recent ESC guidelines on CAD management, which will likely increase CCTA volume over the next years, new tools are necessary to shorten reporting time and improve the accuracy for the detection of ischemia-inducing coronary lesions. The application of artificial intelligence (AI) may provide a helpful tool in CCTA, improving the evaluation and quantification of coronary stenosis, plaque characterization, and assessment of myocardial ischemia. Furthermore, in comparison with existing risk scores, machine-learning algorithms can better predict the outcome utilizing both imaging findings and clinical parameters. Medical AI is moving from the research field to daily clinical practice, and with the increasing number of CCTA examinations, AI will be extensively utilized in cardiac imaging. This review is aimed at illustrating the state of the art in AI-based CCTA applications and future clinical scenarios.