2023
DOI: 10.3390/cells12162073
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Imaging Carotid Plaque Inflammation Using Positron Emission Tomography: Emerging Role in Clinical Stroke Care, Research Applications, and Future Directions

Abstract: Atherosclerosis is a chronic systemic inflammatory condition of the vasculature and a leading cause of stroke. Luminal stenosis severity is an important factor in determining vascular risk. Conventional imaging modalities, such as angiography or duplex ultrasonography, are used to quantify stenosis severity and inform clinical care but provide limited information on plaque biology. Inflammatory processes are central to atherosclerotic plaque progression and destabilization. 18F-fluorodeoxyglucose (FDG) positro… Show more

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Cited by 2 publications
(3 citation statements)
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“…These approaches aim to enhance the accuracy of risk stratification by considering a broader range of factors and exploiting large datasets to identify hidden patterns and associations. Machine learning models, such as random forests and deep neural networks, have shown promise in predicting post-MI outcomes based on clinical, genetic, and imaging data [21]. Early diagnosis and risk stratification are critical components of managing myocardial infarction effectively.…”
Section: Risk Prediction Modelsmentioning
confidence: 99%
See 2 more Smart Citations
“…These approaches aim to enhance the accuracy of risk stratification by considering a broader range of factors and exploiting large datasets to identify hidden patterns and associations. Machine learning models, such as random forests and deep neural networks, have shown promise in predicting post-MI outcomes based on clinical, genetic, and imaging data [21]. Early diagnosis and risk stratification are critical components of managing myocardial infarction effectively.…”
Section: Risk Prediction Modelsmentioning
confidence: 99%
“…Advanced imaging modalities like cardiac MRI and CCTA provide comprehensive insights into cardiac structure and function, facilitating risk stratification and treatment decisions. Risk prediction models like GRACE and TIMI scores help clinicians estimate the likelihood of adverse outcomes following MI, guiding personalized care [21,22]. As research continues to advance, we can expect further refinements in these diagnostic and risk stratification tools.…”
Section: Risk Prediction Modelsmentioning
confidence: 99%
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