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Background: Computed tomography attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only utilized for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-based approach to obtain volumetric measurements of chest body composition from CTAC scans and evaluate these measures for all-cause mortality (ACM) risk stratification. Methods: We applied AI-based segmentation and image-processing techniques on CTAC scans from a large international image-based registry (four sites), to define chest rib cage and multiple tissues. Volumetric measures of bone, skeletal muscle (SM), subcutaneous, intramuscular (IMAT), visceral (VAT), and epicardial (EAT) adipose tissues were quantified between automatically-identified T5 and T11 vertebrae. The independent prognostic value of volumetric attenuation, and indexed volumes were evaluated for predicting ACM, adjusting for established risk factors and 18 other body compositions measures via Cox regression models and Kaplan-Meier curves. Findings: End-to-end processing time was <2 minutes/scan with no user interaction. Of 9918 patients studied, 5451(55%) were male. During median 2.5 years follow-up, 610 (6.2%) patients died. High VAT, EAT and IMAT attenuation were associated with increased ACM risk (adjusted hazard ratio (HR) [95% confidence interval] for VAT: 2.39 [1.92, 2.96], p<0.0001; EAT: 1.55 [1.26, 1.90], p<0.0001; IMAT: 1.30 [1.06, 1.60], p=0.0124). Patients with high bone attenuation were at lower risk of death as compared to subjects with lower bone attenuation (adjusted HR 0.77 [0.62, 0.95], p=0.0159). Likewise, high SM volume index was associated with a lower risk of death (adjusted HR 0.56 [0.44, 0.71], p<0.0001). Interpretations: CTAC scans obtained routinely during cardiac perfusion imaging contain important volumetric body composition biomarkers which can be automatically measured and offer important additional prognostic value. Research in context: Evidence before this study: Fully automated volumetric body composition analysis of chest computed tomography attenuation correction (CTAC) can be obtained in patients undergoing myocardial perfusion imaging. This new information has potential to significantly improve risk stratification and patient management. However, the CTAC scans have not been utilized for body composition analysis to date. We searched PubMed and Google Scholar for existing body composition related literature on June 5, 2024, using the search term ("mortality") AND ("risk stratification" OR "survival analysis" OR "prognostic prediction" OR "prognosis") AND ("body composition quantification" OR "body composition analysis" OR "body composition segmentation"). We identified 34 articles either exploring body composition segmentation or evaluating clinical value of body composition quantification. However, to date, all the prognostic evaluation is performed for quantification of three or fewer types of body composition tissues. Within the prognostic studies, only one used chest CT scans but utilized only a few specified slices selected from the scans, and not a standardized volumetric analysis. None of these previous efforts utilized CTAC scans, and none included epicardial adipose tissue in comprehensive body composition analysis.Added value of this study: In this international multi-center study, we demonstrate a novel artificial intelligence-based annotation-free approach for segmenting six key body composition tissues (bone, skeletal muscle, subcutaneous adipose tissue, intramuscular adipose tissue, epicardial adipose tissue, and visceral adipose tissue) from low-dose ungated CTAC scans, by exploiting existing CT segmentation models and image processing techniques. We evaluate the prognostic value of metrics derived from volumetric quantification of CTAC scans obtained during cardiac imaging, for all-cause mortality prediction in a large cohort of patients. We reveal strong and independent associations between several volumetric body composition metrics and all-cause mortality after adjusting for existing clinical factors, and available cardiac perfusion and atherosclerosis biomarkers.Implications of all the available evidence: The comprehensive body composition analysis can be routinely performed, at the point of care, for all cardiac perfusion scans utilizing CTAC. Automatically-obtained volumetric body composition quantification metrics provide added value over existing risk factors, using already-obtained scans to significantly improve the risk stratification of patients and clinical decision-making.
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Background Quantifying the fibrotic and calcific composition of the aortic valve at CT angiography (CTA) can be useful for assessing disease severity and outcomes of patients with aortic stenosis (AS); however, it has not yet been validated against quantitative histologic findings. Purpose To compare quantification of aortic valve fibrotic and calcific tissue composition at CTA versus histologic examination. Materials and Methods This prospective study included patients who underwent CTA before either surgical aortic valve replacement for AS or orthotopic heart transplant (controls) at two centers between January 2022 and April 2023. At CTA, fibrotic and calcific tissue composition were quantified using automated Gaussian mixture modeling applied to the density of aortic valve tissue components, calculated as [(volume/total tissue volume) × 100]. For histologic evaluation, explanted valve cusps were stained with Movat pentachrome as well as hematoxylin and eosin. For each cusp, three 5-µm slices were obtained. Fibrotic and calcific tissue composition were quantified using a validated artificial intelligence tool and averaged across the aortic valve. Correlations were assessed using the Spearman rank correlation coefficient. Intermodality and interobserver variability were measured using the intraclass correlation coefficient (ICC) and Bland-Altman plots. Results Twenty-nine participants (mean age, 63 years ± 10 [SD]; 23 male) were evaluated: 19 with severe AS, five with moderate AS, and five controls. Fibrocalcific tissue composition strongly correlated with histologic findings (r = 0.92; P < .001). The agreement between CTA and histologic findings for fibrocalcific tissue quantification was excellent (ICC, 0.94; P = .001), with underestimation of fibrotic composition at CTA (bias, -4.9%; 95% limits of agreement [LoA]: -18.5%, 8.7%). Finally, there was excellent interobserver repeatability for fibrotic (ICC, 0.99) and calcific (ICC, 0.99) aortic valve tissue volume measurements, with no evidence of a difference in measurements between readers (bias, -0.04 cm3 [95% LoA: -0.27 cm3, 0.19 cm3] and 0.02 cm3 [95% LoA: -0.14 cm3, 0.19 cm3], respectively). Conclusion In a direct comparison, standardized quantitative aortic valve tissue characterization at CTA showed excellent concordance with histologic findings and demonstrated interobserver reproducibility. Clinical trial registration no. NCT06136689 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Almeida in this issue.
Subject(s)
Aortic Valve Stenosis , Aortic Valve , Calcinosis , Computed Tomography Angiography , Fibrosis , Humans , Male , Prospective Studies , Female , Aortic Valve/diagnostic imaging , Aortic Valve/pathology , Middle Aged , Aortic Valve Stenosis/diagnostic imaging , Aortic Valve Stenosis/pathology , Aortic Valve Stenosis/surgery , Calcinosis/diagnostic imaging , Calcinosis/pathology , Fibrosis/diagnostic imaging , Computed Tomography Angiography/methods , AgedABSTRACT
INTRODUCTION: There are sex differences in the extent, severity, and outcomes of coronary artery disease. We aimed to assess the influence of sex on coronary atherosclerotic plaque activity measured using coronary 18F-sodium fluoride (18F-NaF) positron emission tomography (PET), and to determine whether 18F-NaF PET has prognostic value in both women and men. METHODS: In a post-hoc analysis of observational cohort studies of patients with coronary atherosclerosis who had undergone 18F-NaF PET CT angiography, we compared the coronary microcalcification activity (CMA) in women and men. RESULTS: Baseline 18F-NaF PET CT angiography was available in 999 participants (151 (15%) women) with 4282 patient-years of follow-up. Compared to men, women had lower coronary calcium scores (116 [interquartile range, 27-434] versus 205 [51-571] Agatston units; p = 0.002) and CMA values (0.0 [0.0-1.12] versus 0.53 [0.0-2.54], p = 0.01). Following matching for plaque burden by coronary calcium scores and clinical comorbidities, there was no sex-related difference in CMA values (0.0 [0.0-1.12] versus 0.0 [0.0-1.23], p = 0.21) and similar proportions of women and men had no 18F-NaF uptake (53.0% (n = 80) and 48.3% (n = 73); p = 0.42), or CMA values > 1.56 (21.8% (n = 33) and 21.8% (n = 33); p = 1.00). Over a median follow-up of 4.5 [4.0-6.0] years, myocardial infarction occurred in 6.6% of women (n = 10) and 7.8% of men (n = 66). Coronary microcalcification activity greater than 0 was associated with a similarly increased risk of myocardial infarction in both women (HR: 3.83; 95% CI:1.10-18.49; p = 0.04) and men (HR: 5.29; 95% CI:2.28-12.28; p < 0.001). CONCLUSION: Although men present with more coronary atherosclerotic plaque than women, increased plaque activity is a strong predictor of future myocardial infarction regardless of sex.
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BACKGROUND: Total coronary atherosclerotic plaque activity across the entire coronary arterial tree is associated with patient-level clinical outcomes. OBJECTIVES: We aimed to investigate whether vessel-level coronary atherosclerotic plaque activity is associated with vessel-level myocardial infarction. METHODS: In this secondary analysis of an international multicenter study of patients with recent myocardial infarction and multivessel coronary artery disease, we assessed vessel-level coronary atherosclerotic plaque activity using coronary 18F-sodium fluoride positron emission tomography to identify vessel-level myocardial infarction. RESULTS: Increased 18F-sodium fluoride uptake was found in 679 of 2,094 coronary arteries and 414 of 691 patients. Myocardial infarction occurred in 24 (4%) vessels with increased coronary atherosclerotic plaque activity and in 25 (2%) vessels without increased coronary atherosclerotic plaque activity (HR: 2.08; 95% CI: 1.16-3.72; P = 0.013). This association was not demonstrable in those treated with coronary revascularization (HR: 1.02; 95% CI: 0.47-2.25) but was notable in untreated vessels (HR: 3.86; 95% CI: 1.63-9.10; Pinteraction = 0.024). Increased coronary atherosclerotic plaque activity in multiple coronary arteries was associated with heightened patient-level risk of cardiac death or myocardial infarction (HR: 2.43; 95% CI: 1.37-4.30; P = 0.002) as well as first (HR: 2.19; 95% CI: 1.18-4.06; P = 0.013) and total (HR: 2.50; 95% CI: 1.42-4.39; P = 0.002) myocardial infarctions. CONCLUSIONS: In patients with recent myocardial infarction and multivessel coronary artery disease, coronary atherosclerotic plaque activity prognosticates individual coronary arteries and patients at risk for myocardial infarction.
Subject(s)
Coronary Artery Disease , Myocardial Infarction , Plaque, Atherosclerotic , Humans , Plaque, Atherosclerotic/diagnostic imaging , Plaque, Atherosclerotic/complications , Myocardial Infarction/epidemiology , Myocardial Infarction/etiology , Male , Female , Middle Aged , Coronary Artery Disease/epidemiology , Coronary Artery Disease/diagnostic imaging , Aged , Positron-Emission Tomography , Coronary Vessels/diagnostic imaging , Risk FactorsABSTRACT
PURPOSE OF REVIEW: Despite recent advances, coronary artery disease remains one of the leading causes of mortality worldwide. Noninvasive imaging allows atherosclerotic phenotyping by measurement of plaque burden, morphology, activity and inflammation, which has the potential to refine patient risk stratification and guide personalized therapy. This review describes the current and emerging roles of advanced noninvasive cardiovascular imaging methods for the assessment of coronary artery disease. RECENT FINDINGS: Cardiac computed tomography enables comprehensive, noninvasive imaging of the coronary vasculature, and is used to assess luminal stenoses, coronary calcifications, and distinct adverse plaque characteristics, helping to identify patients prone to future events. Novel software tools, implementing artificial intelligence solutions, can automatically quantify and characterize atherosclerotic plaque from standard computed tomography datasets. These quantitative imaging biomarkers have been shown to improve patient risk stratification beyond clinical risk scores and current clinical interpretation of cardiac computed tomography. In addition, noninvasive molecular imaging in higher risk patients can be used to assess plaque activity and plaque thrombosis. Noninvasive imaging allows unique insight into the burden, morphology and activity of atherosclerotic coronary plaques. Such phenotyping of atherosclerosis can potentially improve individual patient risk prediction, and in the near future has the potential for clinical implementation.
Subject(s)
Coronary Artery Disease , Phenotype , Plaque, Atherosclerotic , Humans , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/pathology , Coronary Artery Disease/diagnosis , Plaque, Atherosclerotic/diagnostic imaging , Plaque, Atherosclerotic/pathology , Tomography, X-Ray Computed , Computed Tomography Angiography/methods , Coronary Vessels/diagnostic imaging , Coronary Vessels/pathology , Risk Assessment/methodsABSTRACT
Atherosclerosis involving vascular beds across the human body remains the leading cause of death worldwide. Coronary and peripheral artery disease, which are almost universally a result of atherosclerotic plaque, can manifest clinically as myocardial infarctions, ischemic stroke, or acute lower-limb ischemia. Beyond imaging myocardial perfusion and blood-flow, nuclear imaging has the potential to depict the activity of the processes that are directly implicated in the atherosclerotic plaque progression and rupture. Out of several tested tracers to date, the literature is most advanced for 18F-sodium fluoride positron emission tomography. In this review, we present the latest data in the field of atherosclerotic 18F-sodium fluoride positron emission tomography imaging, discuss the advantages and limitation of the techniques, and highlight the aspects that require further research in the future.
Subject(s)
Atherosclerosis , Fluorine Radioisotopes , Positron-Emission Tomography , Sodium Fluoride , Humans , Positron-Emission Tomography/methods , Atherosclerosis/diagnostic imaging , Radiopharmaceuticals , Plaque, Atherosclerotic/diagnostic imaging , Coronary Artery Disease/diagnostic imagingABSTRACT
INTRODUCTION: Transfemoral access is a prevailing approach for transcatheter aortic valve implantation (TAVI) in contemporary practice, with a shift from surgical arteriotomy to a percutaneous arterial approach. OBJECTIVES: This study assessed long- and shortterm mortality, along with Valve Academic Research Consortium-2-defined complications in percutaneous transfemoral approach (PTA) TAVI. Furthermore, it explored the impact of a learning curve on procedural outcomes. PATIENTS AND METHODS: The study included 600 patients undergoing PTA TAVI at the National Institute of Cardiology, Warsaw, Poland, from January 2009 to September 2020. Retrospective data comparison involved 2 groups: early experience (first 200 patients) and late experience (next 400 patients). RESULTS: The primary end point (composite of lifethreatening bleeding, major vascular complication, or death at 30 days) occurred less often in the late experience group (28% vs 17.5%; P = 0.003). The late experience group also showed fewer cases of vascular complications (19% vs 10.7%; P = 0.005) and major bleeding (17.5% vs 8.5%; P = 0.001). Propensity matching yielded similar trends, including reduced frequency of pacemaker implantation (22.8% vs 10.9%; P = 0.03) and shorter median (interquartile range) hospitalization (11 [8-18] vs 7 [6-12] days; P <0.001) in the late experience group. CONCLUSIONS: The late experience group rated with PTA TAVI exhibited significantly reduced periprocedural complications, indicating a positive impact of accumulated expertise.
Subject(s)
Aortic Valve Stenosis , Femoral Artery , Postoperative Complications , Transcatheter Aortic Valve Replacement , Humans , Transcatheter Aortic Valve Replacement/adverse effects , Transcatheter Aortic Valve Replacement/methods , Female , Male , Aged , Aged, 80 and over , Retrospective Studies , Poland , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Aortic Valve Stenosis/surgery , Treatment OutcomeABSTRACT
BACKGROUND: Myocardial perfusion imaging (MPI) is one of the most common cardiac scans and is used for diagnosis of coronary artery disease and assessment of cardiovascular risk. However, the large majority of MPI patients have normal results. We evaluated whether unsupervised machine learning could identify unique phenotypes among patients with normal scans and whether those phenotypes were associated with risk of death or myocardial infarction. METHODS: Patients from a large international multicenter MPI registry (10 sites) with normal perfusion by expert visual interpretation were included in this cohort analysis. The training population included 9849 patients, and external testing population 12,528 patients. Unsupervised cluster analysis was performed, with separate training and external testing cohorts, to identify clusters, with four distinct phenotypes. We evaluated the clinical and imaging features of clusters and their associations with death or myocardial infarction. FINDINGS: Patients in Clusters 1 and 2 almost exclusively underwent exercise stress, while patients in Clusters 3 and 4 mostly required pharmacologic stress. In external testing, the risk for Cluster 4 patients (20.2% of population, unadjusted hazard ratio [HR] 6.17, 95% confidence interval [CI] 4.64-8.20) was higher than the risk associated with pharmacologic stress (HR 3.03, 95% CI 2.53-3.63), or previous myocardial infarction (HR 1.82, 95% CI 1.40-2.36). INTERPRETATION: Unsupervised learning identified four distinct phenotypes of patients with normal perfusion scans, with a significant proportion of patients at very high risk of myocardial infarction or death. Our results suggest a potential role for patient phenotyping to improve risk stratification of patients with normal imaging results. FUNDING: This work was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R35HL161195 to PS]. The REFINE SPECT database was supported by the National Heart, Lung, and Blood Institute at the National Institutes of Health [R01HL089765 to PS]. MCW was supported by the British Heart Foundation [FS/ICRF/20/26002].
Subject(s)
Coronary Artery Disease , Myocardial Infarction , Humans , Coronary Artery Disease/diagnostic imaging , Myocardial Infarction/diagnostic imaging , Myocardial Infarction/etiology , Perfusion , Prognosis , Risk Factors , Unsupervised Machine Learning , Retrospective StudiesSubject(s)
Coronary Artery Disease , Coronary Stenosis , Plaque, Atherosclerotic , Humans , Artificial Intelligence , Predictive Value of Tests , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/therapy , Coronary Angiography , Computed Tomography Angiography , Coronary Vessels/diagnostic imagingABSTRACT
AIMS: Transoesophageal echocardiography (TOE) is often performed before catheter ablation or cardioversion to rule out the presence of left atrial appendage thrombus (LAT) in patients on chronic oral anticoagulation (OAC), despite associated discomfort. A machine learning model [LAT-artificial intelligence (AI)] was developed to predict the presence of LAT based on clinical and transthoracic echocardiography (TTE) features. METHODS AND RESULTS: Data from a 13-site prospective registry of patients who underwent TOE before cardioversion or catheter ablation were used. LAT-AI was trained to predict LAT using data from 12 sites (n = 2827) and tested externally in patients on chronic OAC from two sites (n = 1284). Areas under the receiver operating characteristic curve (AUC) of LAT-AI were compared with that of left ventricular ejection fraction (LVEF) and CHA2DS2-VASc score. A decision threshold allowing for a 99% negative predictive value was defined in the development cohort. A protocol where TOE in patients on chronic OAC is performed depending on the LAT-AI score was validated in the external cohort. In the external testing cohort, LAT was found in 5.5% of patients. LAT-AI achieved an AUC of 0.85 [95% confidence interval (CI): 0.82-0.89], outperforming LVEF (0.81, 95% CI 0.76-0.86, P < .0001) and CHA2DS2-VASc score (0.69, 95% CI: 0.63-0.7, P < .0001) in the entire external cohort. Based on the proposed protocol, 40% of patients on chronic OAC from the external cohort would safely avoid TOE. CONCLUSION: LAT-AI allows accurate prediction of LAT. A LAT-AI-based protocol could be used to guide the decision to perform TOE despite chronic OAC.
Subject(s)
Atrial Appendage , Atrial Fibrillation , Heart Diseases , Thrombosis , Humans , Echocardiography, Transesophageal/methods , Atrial Appendage/diagnostic imaging , Stroke Volume , Artificial Intelligence , Atrial Fibrillation/complications , Ventricular Function, Left , Echocardiography , Heart Diseases/diagnosis , Thrombosis/diagnosis , Risk FactorsABSTRACT
Coronary artery disease is the leading cause of morbidity and mortality worldwide. Despite remarkable advances in the management of coronary artery disease, the prediction of adverse coronary events remains challenging. Over the preceding decades, considerable effort has been made to improve risk stratification using noninvasive imaging. Recently, these efforts have increasingly focused on the direct imaging of coronary atherosclerotic plaque. Modern imaging now allows imaging of coronary plaque burden, plaque type, atherosclerotic plaque activity, and plaque thrombosis, which have major potential to refine patient risk stratification, aid decision making, and advance future clinical practice.
Subject(s)
Coronary Artery Disease , Plaque, Atherosclerotic , Humans , Coronary Artery Disease/diagnostic imaging , Coronary Artery Disease/therapy , Coronary Angiography/methods , Computed Tomography Angiography/methods , Predictive Value of Tests , Coronary Vessels/diagnostic imaging , Adipose TissueABSTRACT
BACKGROUND AND AIMS: Myocardial perfusion imaging (MPI) and anatomical imaging with coronary computed tomography angiography (CCTA) can play an important role in the preprocedural planning of a chronic total occlusion (CTO) percutaneous coronary intervention (PCI). We aimed to establish the feasibility of a novel dynamic computed tomography perfusion (CTP) analysis for the assessment of myocardial perfusion before and after a successful recanalization of CTO in patients undergoing CCTA as part of a standard preprocedural workup. METHODS: In a prospective observational study symptomatic patients underwent dynamic CTP on a dual-source CT scanner both before and 3 months after successful CTO PCI. RESULTS: Twenty-seven patients completed the study (63 ± 8 years old, 78% male). Following successful CTO PCI, there was a significant reduction in the ischemic burden (5 [5-7] versus 1 [0-2] segments, p < 0.001), and improvement in myocardial blood flow (85.3 [71.7-94.1] versus 134.6 [123.8-156.9] mL/min, p < 0.001) resulting in an increase in the relative flow reserve (0.49 [0.41-0.57] versus 0.88 [0.74-0.95], p < 0.001). CONCLUSIONS: CTP emerges as a robust and safe method for MPI in CTO patients. The single imaging session assessment of both coronary anatomy and perfusion with CT lends itself to precise disease phenotyping in the challenging population of CTO patients.
Subject(s)
Coronary Occlusion , Myocardial Perfusion Imaging , Percutaneous Coronary Intervention , Vascular Diseases , Humans , Male , Middle Aged , Aged , Female , Coronary Angiography/methods , Predictive Value of Tests , Tomography, X-Ray Computed , Computed Tomography Angiography , Coronary Occlusion/diagnostic imaging , Coronary Occlusion/surgery , Chronic Disease , Myocardial Perfusion Imaging/methods , Treatment OutcomeABSTRACT
Importance: Recurrent coronary events in patients with recent myocardial infarction remain a major clinical problem. Noninvasive measures of coronary atherosclerotic disease activity have the potential to identify individuals at greatest risk. Objective: To assess whether coronary atherosclerotic plaque activity as assessed by noninvasive imaging is associated with recurrent coronary events in patients with myocardial infarction. Design, Setting, and Participants: This prospective, longitudinal, international multicenter cohort study recruited participants aged 50 years or older with multivessel coronary artery disease and recent (within 21 days) myocardial infarction between September 2015 and February 2020, with a minimum 2 years' follow-up. Intervention: Coronary 18F-sodium fluoride positron emission tomography and coronary computed tomography angiography. Main Outcomes and Measures: Total coronary atherosclerotic plaque activity was assessed by 18F-sodium fluoride uptake. The primary end point was cardiac death or nonfatal myocardial infarction but was expanded during study conduct to include unscheduled coronary revascularization due to lower than anticipated primary event rates. Results: Among 2684 patients screened, 995 were eligible, 712 attended for imaging, and 704 completed an interpretable scan and comprised the study population. The mean (SD) age of participants was 63.8 (8.2) years, and most were male (601 [85%]). Total coronary atherosclerotic plaque activity was identified in 421 participants (60%). After a median follow-up of 4 years (IQR, 3-5 years), 141 participants (20%) experienced the primary end point: 9 had cardiac death, 49 had nonfatal myocardial infarction, and 83 had unscheduled coronary revascularizations. Increased coronary plaque activity was not associated with the primary end point (hazard ratio [HR], 1.25; 95% CI, 0.89-1.76; P = .20) or unscheduled revascularization (HR, 0.98; 95% CI, 0.64-1.49; P = .91) but was associated with the secondary end point of cardiac death or nonfatal myocardial infarction (47 of 421 patients with high plaque activity [11.2%] vs 19 of 283 with low plaque activity [6.7%]; HR, 1.82; 95% CI, 1.07-3.10; P = .03) and all-cause mortality (30 of 421 patients with high plaque activity [7.1%] vs 9 of 283 with low plaque activity [3.2%]; HR, 2.43; 95% CI, 1.15-5.12; P = .02). After adjustment for differences in baseline clinical characteristics, coronary angiography findings, and Global Registry of Acute Coronary Events score, high coronary plaque activity was associated with cardiac death or nonfatal myocardial infarction (HR, 1.76; 95% CI, 1.00-3.10; P = .05) but not with all-cause mortality (HR, 2.01; 95% CI, 0.90-4.49; P = .09). Conclusions and Relevance: In this cohort study of patients with recent myocardial infarction, coronary atherosclerotic plaque activity was not associated with the primary composite end point. The findings suggest that risk of cardiovascular death or myocardial infarction in patients with elevated plaque activity warrants further research to explore its incremental prognostic implications.
Subject(s)
Coronary Artery Disease , Myocardial Infarction , Plaque, Atherosclerotic , Humans , Male , Female , Plaque, Atherosclerotic/complications , Plaque, Atherosclerotic/diagnostic imaging , Prospective Studies , Cohort Studies , Sodium Fluoride , Coronary Artery Disease/complications , Myocardial Infarction/complications , DeathABSTRACT
OBJECTIVE: Inflammatory activity is one of the potential mechanisms of spontaneous coronary artery dissection (SCAD). Recently, the pericoronary adipose tissue attenuation (PCAT) derived from CT angiography (CTA) has been established as a method for measuring vascular inflammation. We aimed to characterise the pancoronary and vessel-specific PCAT in patients with and without recent SCAD. METHODS: The study comprised patients with SCAD referred to a tertiary centre between 2017 and 2022 who underwent CTA and were compared with individuals with no prior SCAD. PCAT was analysed on end-diastolic CTA reconstructions along proximal 40 mm of all major coronary vessels as well as the SCAD-related vessel. We analysed 48 patients with recent SCAD (median 6.1 (IQR 3.5-14.9) months since SCAD, 95.8% female) and 48 patients in the group without SCAD. RESULTS: Pancoronary PCAT was higher in patients with SCAD compared with those without SCAD (-80.6±7.9 vs -85.3 HU±6.1, p=0.002). Vessel-specific PCAT in patients with SCAD compared with patients without SCAD was higher for both the RCA (-80.9±9.5 vs -87.1±6.9 HU, p=0.001) and the LCA (-80.3±7.8 vs -83.4±7.2 HU, p=0.04). In patients with SCAD, PCAT of the SCAD-related vessel was not significantly different from averaged PCAT of unaffected vessels (-81.2±9.2 vs -80.6±7.6, p=0.74). There was no association between PCAT and the interval from SCAD to CTA. CONCLUSIONS: Patients with recent SCAD have higher PCAT compared with patients without SCAD, suggesting an increased perivascular inflammatory activity. This association is not restricted to the dissected vessel.
Subject(s)
Coronary Artery Disease , Humans , Female , Male , Coronary Artery Disease/diagnostic imaging , Coronary Angiography/methods , Heart , Computed Tomography Angiography/methods , Coronary Vessels/diagnostic imaging , Adipose Tissue/diagnostic imagingABSTRACT
BACKGROUND: Assessments of coronary disease activity with 18F-sodium fluoride positron emission tomography and radiomics-based precision coronary plaque phenotyping derived from coronary computed tomography angiography may enhance risk stratification in patients with coronary artery disease. We sought to investigate whether the prognostic information provided by these 2 approaches is complementary in the prediction of myocardial infarction. METHODS: Patients with known coronary artery disease underwent coronary 18F-sodium fluoride positron emission tomography and coronary computed tomography angiography on a hybrid positron emission tomography/computed tomography scanner. Coronary 18F-NaF uptake was determined by the coronary microcalcification activity. We performed quantitative plaque analysis of coronary computed tomography angiography datasets and extracted 1103 radiomic features for each plaque. Using weighted correlation network analysis, we derived latent morphological features of coronary lesions which were aggregated to patient-level radiomics nomograms to predict myocardial infarction. RESULTS: Among 260 patients with established coronary artery disease (age, 65±9 years; 83% men), 179 (69%) participants showed increased coronary 18F-NaF activity (coronary microcalcification activity>0). Over 53 (40-59) months of follow-up, 18 patients had a myocardial infarction. Using weighted correlation network analysis, we derived 15 distinct eigen radiomic features representing latent morphological coronary plaque patterns in an unsupervised fashion. Following adjustments for calcified, noncalcified, and low-density noncalcified plaque volumes and 18F-NaF coronary microcalcification activity, 4 radiomic features remained independent predictors of myocardial infarction (hazard ratio, 1.46 [95% CI, 1.03-2.08]; P=0.03; hazard ratio, 1.62 [95% CI, 1.04-2.54]; P=0.02; hazard ratio, 1.49 [95% CI, 1.07-2.06]; P=0.01; and hazard ratio, 1.50 (95% CI, 1.05-2.13); P=0.02). CONCLUSIONS: In patients with established coronary artery disease, latent coronary plaque morphological features, quantitative plaque volumes, and disease activity on 18F-sodium fluoride positron emission tomography are additive predictors of myocardial infarction.
Subject(s)
Calcinosis , Coronary Artery Disease , Myocardial Infarction , Plaque, Atherosclerotic , Male , Humans , Middle Aged , Aged , Female , Coronary Artery Disease/diagnostic imaging , Computed Tomography Angiography , Sodium Fluoride , Fluorine Radioisotopes , Radiopharmaceuticals , Positron-Emission Tomography/methods , Positron Emission Tomography Computed Tomography/methods , Myocardial Infarction/diagnostic imaging , Myocardial Infarction/etiology , Coronary Angiography/methodsABSTRACT
Aortic stenosis is the most common form of valve disease in the Western world and a major healthcare burden. Although echocardiography remains the central modality for the diagnosis and assessment of aortic stenosis, recently, advanced cardiac imaging with cardiovascular magnetic resonance, computed tomography, and positron emission tomography have provided invaluable pathological insights that may guide the personalized management of the disease. In this review, we discuss applications of these novel non-invasive imaging modalities for establishing the diagnosis, monitoring disease progression, and eventually planning the invasive treatment of aortic stenosis.
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Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. For developing new therapies, a better understanding of the underlying pathology is required. Historically, such insights have been primarily derived from pathological studies. In the 21st century, thanks to the advent of cardiovascular positron emission tomography (PET), which depicts the presence and activity of pathophysiological processes, it is now feasible to assess disease activity in vivo. By targeting distinct biological pathways, PET elucidates the activity of the processes which drive disease progression, adverse outcomes or, on the contrary, those that can be considered as a healing response. Given the insights provided by PET, this non-invasive imaging technology lends itself to the development of new therapies, providing a hope for the emergence of strategies that could have a profound impact on patient outcomes. In this narrative review, we discuss recent advances in cardiovascular PET imaging which have greatly advanced our understanding of atherosclerosis, ischemia, infection, adverse myocardial remodeling and degenerative valvular heart disease.
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Standard clinical interpretation of myocardial perfusion imaging (MPI) has proven prognostic value for predicting major adverse cardiovascular events (MACE). However, personalizing predictions to a specific event type and time interval is more challenging. We demonstrate an explainable deep learning model that predicts the time-specific risk separately for all-cause death, acute coronary syndrome (ACS), and revascularization directly from MPI and 15 clinical features. We train and test the model internally using 10-fold hold-out cross-validation (n = 20,418) and externally validate it in three separate sites (n = 13,988) with MACE follow-ups for a median of 3.1 years (interquartile range [IQR]: 1.6, 3.6). We evaluate the model using the cumulative dynamic area under receiver operating curve (cAUC). The best model performance in the external cohort is observed for short-term prediction - in the first six months after the scan, mean cAUC for ACS and all-cause death reaches 0.76 (95% confidence interval [CI]: 0.75, 0.77) and 0.78 (95% CI: 0.78, 0.79), respectively. The model outperforms conventional perfusion abnormality measures at all time points for the prediction of death in both internal and external validations, with improvement increasing gradually over time. Individualized patient explanations are visualized using waterfall plots, which highlight the contribution degree and direction for each feature. This approach allows the derivation of individual event probability as a function of time as well as patient- and event-specific risk explanations that may help draw attention to modifiable risk factors. Such a method could help present post-scan risk assessments to the patient and foster shared decision-making.
ABSTRACT
PET allows the assessment of cardiovascular pathophysiology across a wide range of cardiovascular conditions. By imaging processes directly involved in disease progression and adverse events, such as inflammation and developing calcifications (microcalcifications), PET can not only enhance our understanding of cardiovascular disease, but also, as shown for 18F-sodium fluoride, has the potential to predict hard endpoints. In this review, the recent advances in disease activity assessment with cardiovascular PET, which provide hope that this promising technology could be leveraged in the clinical setting, shall be discussed.
Subject(s)
Calcinosis , Coronary Artery Disease , Plaque, Atherosclerotic , Humans , Radiopharmaceuticals , Positron-Emission Tomography , Tomography, X-Ray Computed , Multimodal Imaging/methodsABSTRACT
PURPOSE: Patients with known coronary artery disease (CAD) comprise a heterogenous population with varied clinical and imaging characteristics. Unsupervised machine learning can identify new risk phenotypes in an unbiased fashion. We use cluster analysis to risk-stratify patients with known CAD undergoing single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). METHODS: From 37,298 patients in the REFINE SPECT registry, we identified 9221 patients with known coronary artery disease. Unsupervised machine learning was performed using clinical (23), acquisition (17), and image analysis (24) parameters from 4774 patients (internal cohort) and validated with 4447 patients (external cohort). Risk stratification for all-cause mortality was compared to stress total perfusion deficit (< 5%, 5-10%, ≥10%). RESULTS: Three clusters were identified, with patients in Cluster 3 having a higher body mass index, more diabetes mellitus and hypertension, and less likely to be male, have dyslipidemia, or undergo exercise stress imaging (p < 0.001 for all). In the external cohort, during median follow-up of 2.6 [0.14, 3.3] years, all-cause mortality occurred in 312 patients (7%). Cluster analysis provided better risk stratification for all-cause mortality (Cluster 3: hazard ratio (HR) 5.9, 95% confidence interval (CI) 4.0, 8.6, p < 0.001; Cluster 2: HR 3.3, 95% CI 2.5, 4.5, p < 0.001; Cluster 1, reference) compared to stress total perfusion deficit (≥10%: HR 1.9, 95% CI 1.5, 2.5 p < 0.001; < 5%: reference). CONCLUSIONS: Our unsupervised cluster analysis in patients with known CAD undergoing SPECT MPI identified three distinct phenotypic clusters and predicted all-cause mortality better than ischemia alone.