119 research outputs found

    Non-invasive imaging of high-risk coronary plaque: the role of computed tomography and positron emission tomography

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    Despite recent advances, cardiovascular disease remains the leading cause of death globally. As such, there is a need to optimise our current diagnostic and risk stratification pathways in order to better deliver individualised preventative therapies. Non-invasive imaging of coronary artery plaque can interrogate multiple aspects of coronary atherosclerotic disease, including plaque morphology, anatomy and flow. More recently, disease activity is being assessed to provide mechanistic insights into in vivo atherosclerosis biology. Molecular imaging using positron emission tomography is unique in this field, with the potential to identify specific biological processes using either bespoke or re-purposed radiotracers. This review provides an overview of non-invasive vulnerable plaque detection and molecular imaging of coronary atherosclerosis

    Complementary role of cardiac CT in the assessment of aortic valve replacement dysfunction

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    Aortic valve replacement is the second most common cardiothoracic procedure in the UK. With an ageing population, there are an increasing number of patients with prosthetic valves that require follow-up. Imaging of prosthetic valves is challenging with conventional echocardiographic techniques making early detection of valve dysfunction or complications difficult. CT has recently emerged as a complementary approach offering excellent spatial resolution and the ability to identify a range of aortic valve replacement complications including structural valve dysfunction, thrombus development, pannus formation and prosthetic valve infective endocarditis. This review discusses each and how CT might be incorporated into a multimodal cardiovascular imaging pathway for the assessment of aortic valve replacements and in guiding clinical management

    Positron emission tomography imaging of coronary atherosclerosis

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    Inflammation has a central role in the progression of coronary atherosclerosis. Recent developments in cardiovascular imaging with the advent of hybrid positron emission tomography have provided a window into the molecular pathophysiology underlying coronary plaque inflammation. Using novel radiotracers targeted at specific cellular pathways, the potential exists to observe inflammation, apoptosis, cellular hypoxia, microcalcification and angiogenesis in vivo. Several clinical studies are now underway assessing the ability of this hybrid imaging modality to inform about atherosclerotic disease activity and the prediction of future cardiovascular risk. A better understanding of the molecular mechanisms governing coronary atherosclerosis may be the first step toward offering patients a more stratified, personalized approach to treatment

    Machine-learning with 18F-sodium fluoride PET and quantitative plaque analysis on CT angiography for the future risk of myocardial infarction

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    Coronary (18)F-sodium fluoride ((18)F-NaF) PET and CT angiography–based quantitative plaque analysis have shown promise in refining risk stratification in patients with coronary artery disease. We combined both of these novel imaging approaches to develop an optimal machine-learning model for the future risk of myocardial infarction in patients with stable coronary disease. Methods: Patients with known coronary artery disease underwent coronary (18)F-NaF PET and CT angiography on a hybrid PET/CT scanner. Machine-learning by extreme gradient boosting was trained using clinical data, CT quantitative plaque analysis, measures and (18)F-NaF PET, and it was tested using repeated 10-fold hold-out testing. Results: Among 293 study participants (65 ± 9 y; 84% male), 22 subjects experienced a myocardial infarction over the 53 (40–59) months of follow-up. On univariable receiver-operator-curve analysis, only (18)F-NaF coronary uptake emerged as a predictor of myocardial infarction (c-statistic 0.76, 95% CI 0.68–0.83). When incorporated into machine-learning models, clinical characteristics showed limited predictive performance (c-statistic 0.64, 95% CI 0.53–0.76) and were outperformed by a quantitative plaque analysis-based machine-learning model (c-statistic 0.72, 95% CI 0.60–0.84). After inclusion of all available data (clinical, quantitative plaque and (18)F-NaF PET), we achieved a substantial improvement (P = 0.008 versus (18)F-NaF PET alone) in the model performance (c-statistic 0.85, 95% CI 0.79–0.91). Conclusion: Both (18)F-NaF uptake and quantitative plaque analysis measures are additive and strong predictors of outcome in patients with established coronary artery disease. Optimal risk stratification can be achieved by combining clinical data with these approaches in a machine-learning model

    Coronary 18F-Fluoride Uptake and Progression of Coronary Artery Calcification

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    Background Positron emission tomography (PET) using 18F-sodium fluoride (18F-fluoride) to detect microcalcification may provide insight into disease activity in coronary atherosclerosis. This study aimed to investigate the relationship between 18F-fluoride uptake and progression of coronary calcification in patients with clinically stable coronary artery disease. Methods Patients with established multivessel coronary atherosclerosis underwent 18F-fluoride PET-computed tomography angiography and computed tomography calcium scoring, with repeat computed tomography angiography and calcium scoring at one year. Coronary PET uptake was analyzed qualitatively and semiquantitatively in diseased vessels by measuring maximum tissue-to-background ratio. Coronary calcification was quantified by measuring calcium score, mass, and volume. Results In a total of 183 participants (median age 66 years, 80% male), 116 (63%) patients had increased 18F-fluoride uptake in at least one vessel. Individuals with increased 18F-fluoride uptake demonstrated more rapid progression of calcification compared with those without uptake (change in calcium score, 97 [39-166] versus 35 [7-93] AU; P<0.0001). Indeed, the calcium score only increased in coronary segments with 18F-fluoride uptake (from 95 [30-209] to 148 [61-289] AU; P<0.001) and remained unchanged in segments without 18F-fluoride uptake (from 46 [16-113] to 49 [20-115] AU; P=0.329). Baseline coronary 18F-fluoride maximum tissue-to-background ratio correlated with 1-year change in calcium score, calcium volume, and calcium mass (Spearman ρ=0.37, 0.38, and 0.46, respectively; P<0.0001 for all). At the segmental level, baseline 18F-fluoride activity was an independent predictor of calcium score at 12 months (P<0.001). However, at the patient level, this was not independent of age, sex, and baseline calcium score (P=0.50). Conclusions Coronary 18F-fluoride uptake identifies both patients and individual coronary segments with more rapid progression of coronary calcification, providing important insights into disease activity within the coronary circulation. At the individual patient level, total calcium score remains an important marker of disease burden and progression. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02110303

    Association of Lipoprotein(a) With Atherosclerotic Plaque Progression

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    BACKGROUND: Lipoprotein(a) [Lp(a)] is associated with increased risk of myocardial infarction, although the mechanism for this observation remains uncertain. OBJECTIVES: This study aims to investigate whether Lp(a) is associated with adverse plaque progression. METHODS: Lp(a) was measured in patients with advanced stable coronary artery disease undergoing coronary computed tomography angiography at baseline and 12 months to assess progression of total, calcific, noncalcific, and low-attenuation plaque (necrotic core) in particular. High Lp(a) was defined as Lp(a) ≄ 70 mg/dL. The relationship of Lp(a) with plaque progression was assessed using linear regression analysis, adjusting for body mass index, segment involvement score, and ASSIGN score (a Scottish cardiovascular risk score comprised of age, sex, smoking, blood pressure, total and high-density lipoprotein [HDL]–cholesterol, diabetes, rheumatoid arthritis, and deprivation index). RESULTS: A total of 191 patients (65.9 ± 8.3 years of age; 152 [80%] male) were included in the analysis, with median Lp(a) values of 100 (range: 82 to 115) mg/dL and 10 (range: 5 to 24) mg/dL in the high and low Lp(a) groups, respectively. At baseline, there was no difference in coronary artery disease severity or plaque burden. Patients with high Lp(a) showed accelerated progression of low-attenuation plaque compared with low Lp(a) patients (26.2 ± 88.4 mm(3) vs −0.7 ± 50.1 mm(3); P = 0.020). Multivariable linear regression analysis confirmed the relation between Lp(a) and low-attenuation plaque volume progression (ÎČ = 10.5% increase for each 50 mg/dL Lp(a), 95% CI: 0.7%-20.3%). There was no difference in total, calcific, and noncalcific plaque volume progression. CONCLUSIONS: Among patients with advanced stable coronary artery disease, Lp(a) is associated with accelerated progression of coronary low-attenuation plaque (necrotic core). This may explain the association between Lp(a) and the high residual risk of myocardial infarction, providing support for Lp(a) as a treatment target in atherosclerosis
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