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Coronary artery calcium: A technical argument for a new scoring method.
Willemink, MJ, van der Werf, NR, Nieman, K, Greuter, MJW, Koweek, LM, Fleischmann, D
Journal of cardiovascular computed tomography. 2019;(6):347-352
Abstract
Coronary artery calcium (CAC) is a strong predictor for future cardiovascular events. Traditionally CAC has been quantified using the Agatston score, which was developed in the late 1980s for electron beam tomography (EBT). While EBT has been completely replaced by modern multiple-detector row CT technology, the traditional CAC scoring method by Agatston remains in use, although the literature indicates suboptimal reproducibility and subjects being incorrectly classified. The traditional Agatston scoring method counteracts the technical advances of CT technology, and prevents the use of thinner sections, obtained at lower tube voltage and overall decreased radiation exposure that has become available to other CT applications. Moreover, recent studies have shown that not only the total amount of CAC, but also its density and distribution in the coronary arterial tree may be of prognostic value. Acquisition and reconstruction techniques thus need to be adapted for modern CT technology and optimized for CAC quantification. In this review we describe the technical limitations of the Agatston score followed by our suggestions for developing a new and more robust CAC quantification method.
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Intracoronary Lithotripsy for the Treatment of Calcified Plaque.
Yeoh, J, Hill, J
Interventional cardiology clinics. 2019;(4):411-424
Abstract
Intravascular lithotripsy facilitates percutaneous coronary intervention of lesions with severe calcification by using high-pressure ultrasonic energy. It is the newest adjunctive tool for calcium modification and is showing promise as its users gather more experience and it becomes readily available worldwide. This article reviews intravascular lithotripsy technology, the evidence in the literature, and the advantages and disadvantages compared with other forms of calcium modification, and discusses its role in specific subsets of coronary lesions. It concludes with a discussion about the future direction of research involving this new technology as its role within percutaneous cardiac procedures becomes more defined.
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Cardiovascular Risk Heterogeneity in Adults with Diabetes: Selective Use of Coronary Artery Calcium in Statin Use Decision-making.
Sarkar, S, Orimoloye, OA, Nass, CM, Blumenthal, RS, Martin, SS
Journal of general internal medicine. 2019;(11):2643-2647
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Abstract
Current American College of Cardiology/American Heart Association and American Diabetes Association guidelines recommend statin therapy for all patients with diabetes between the ages of 40 and 75, including those without cardiovascular disease (CVD). While diabetes is a major CVD risk factor, not all patients with diabetes have an equal risk of CVD. Thus, a more risk-based approach warrants consideration when recommending statin therapy for the primary prevention of CVD. Coronary artery calcium (CAC) is a noninvasive imaging modality that can help risk stratify patients with diabetes for future CVD events. CAC has been extensively studied in large cohorts such as the Multi-Ethnic Study of Atherosclerosis and found to outperform other novel risk stratification tools including carotid intima-media thickness. Moreover, a CAC score of 0 has been shown to be useful in downgrading the estimated risk of a CVD event in patients with diabetes and an intermediate Pooled Cohort Equation score. As clinicians weigh the recommendation for a lifelong therapy and the problem of statin nonadherence and patients weigh concerns about adverse effects of statins, the decision to initiate statin therapy in patients with diabetes is ideally a shared one between patients and providers, and CAC could facilitate this discussion.
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Coronary risk assessment using traditional risk factors with CT coronary artery calcium scoring in clinical practice.
Kerut, EK, Hall, ME, Turner, MC, McMullan, MR
Echocardiography (Mount Kisco, N.Y.). 2018;(8):1216-1222
Abstract
As coronary artery calcium (CAC) is atherosclerosis and not just a marker of cardiovascular (CV) disease, measurement of a patient's coronary artery calcium score (CACS) is a strong predictor of risk. Clinically performed in asymptomatic patients, the CACS, along with several CV risk factors, namely age, sex, ethnicity, diabetes, tobacco use, family history, cholesterol level, blood pressure, and use of cholesterol or hypertensive medications, provide a predictive model of 10 year risk for CV events. A smartphone "App" makes this quick to obtain and use. This helps the clinician in making recommendations for both lifestyle changes and statin therapy. Those patients in which the most benefit occur from measurement of a CACS are those at an intermediate CV risk. Measurement of the CACS has become an integral part of the clinician's assessment of a patient's CV risk and for guiding preventative therapies.
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Primary prevention of coronary artery disease: let's start with calcium score.
Gatto, L, Prati, F
Journal of cardiovascular medicine (Hagerstown, Md.). 2018;:e103-e106
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Coronary Calcium Score and Cardiovascular Risk.
Greenland, P, Blaha, MJ, Budoff, MJ, Erbel, R, Watson, KE
Journal of the American College of Cardiology. 2018;(4):434-447
Abstract
Coronary artery calcium (CAC) is a highly specific feature of coronary atherosclerosis. On the basis of single-center and multicenter clinical and population-based studies with short-term and long-term outcomes data (up to 15-year follow-up), CAC scoring has emerged as a widely available, consistent, and reproducible means of assessing risk for major cardiovascular outcomes, especially useful in asymptomatic people for planning primary prevention interventions such as statins and aspirin. CAC testing in asymptomatic populations is cost effective across a broad range of baseline risk. This review summarizes evidence concerning CAC, including its pathobiology, modalities for detection, predictive role, use in prediction scoring algorithms, CAC progression, evidence that CAC changes the clinical approach to the patient and patient behavior, novel applications of CAC, future directions in scoring CAC scans, and new CAC guidelines.
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Coronary computed tomographic imaging in women: An expert consensus statement from the Society of Cardiovascular Computed Tomography.
Truong, QA, Rinehart, S, Abbara, S, Achenbach, S, Berman, DS, Bullock-Palmer, R, Carrascosa, P, Chinnaiyan, KM, Dey, D, Ferencik, M, et al
Journal of cardiovascular computed tomography. 2018;(6):451-466
Abstract
This expert consensus statement from the Society of Cardiovascular Computed Tomography (SCCT) provides an evidence synthesis on the use of computed tomography (CT) imaging for diagnosis and risk stratification of coronary artery disease in women. From large patient and population cohorts of asymptomatic women, detection of any coronary artery calcium that identifies females with a 10-year atherosclerotic cardiovascular disease risk of >7.5% may more effectively triage women who may benefit from pharmacologic therapy. In addition to accurate detection of obstructive coronary artery disease (CAD), CT angiography (CTA) identifies nonobstructive atherosclerotic plaque extent and composition which is otherwise not detected by alternative stress testing modalities. Moreover, CTA has superior risk stratification when compared to stress testing in symptomatic women with stable chest pain (or equivalent) symptoms. For the evaluation of symptomatic women both in the emergency department and the outpatient setting, there is abundant evidence from large observational registries and multi-center randomized trials, that CT imaging is an effective procedure. Although radiation doses are far less for CT when compared to nuclear imaging, radiation dose reduction strategies should be applied in all women undergoing CT imaging. Effective and appropriate use of CT imaging can provide the means for improved detection of at-risk women and thereby focus preventive management resulting in long-term risk reduction and improved clinical outcomes.
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The evolving view of coronary artery calcium and cardiovascular disease risk.
Thomas, IC, Forbang, NI, Criqui, MH
Clinical cardiology. 2018;(1):144-150
Abstract
Calcification of the coronary artery is a complex pathophysiologic process that is intimately associated with atherosclerosis. Extensive investigation has demonstrated the value of identifying and quantifying coronary artery calcium (CAC) in atherosclerotic cardiovascular disease (CVD) prognostication. However, over the last several years, an increasing body of evidence has suggested that CAC has underappreciated aspects that modulate, and at times attenuate, future CVD risk. The most commonly used measure of CAC, the Agatston unit, effectively models both higher density and higher area of CAC as risk factors for future CVD events. Recent findings from the Multi-Ethnic Study of Atherosclerosis (MESA) have challenged this assumption, demonstrating that higher density of CAC is protective for coronary heart disease and CVD events. Statins may be associated with an increase in CAC, an unexpected finding given their clear benefits in the prevention and treatment of CVD. Studies utilizing intracoronary ultrasound and coronary computed tomography angiography have demonstrated that calcified atherosclerotic plaque-as compared with noncalcified or sparsely calcified plaque-is associated with fewer CVD events. These studies lend support to the often-asserted (but as yet unvalidated) view that calcification may play a role in plaque stabilization. Furthermore, vascular calcification, though a surrogate for atherosclerotic plaque burden, may also possess identifiable aspects that can refine CVD risk assessment.
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Coronary Artery Calcium Scoring in Young Adults: Evidence and Challenges.
Saad, M, Pothineni, NV, Thomas, J, Parikh, R, Kovelamudi, S, Elsayed, D, Nairooz, R, Feit, F
Current cardiology reports. 2018;(2):10
Abstract
PURPOSE OF REVIEW This review aims to summarize the evidence and challenges of coronary artery calcium (CAC) scoring as a screening tool for coronary artery disease (CAD) in young adults. RECENT FINDINGS Several cohort studies have highlighted the value of CAC scoring in CAD risk assessment in young adults. The largest study to date is the Coronary Artery Risk Development in Young Adults (CARDIA) study. The study examined patients at 18-30 years of age and demonstrated that the presence of any degree of CAC was associated with a higher risk of coronary events compared to zero CAC, with an incremental increase in the risk of events with higher scores. However, it is important to note that 70% of patients screened had CAC = 0 at the age of 56. Despite the evidence that higher CAC score cutoff used in guidelines for predicting cardiovascular risk may be "falsely reassuring," however, mass screening of young adults using CAC score may be challenging. The development of prediction tools and scoring systems to identify patients at higher risk of developing CAC based on known CAD risk factors may help reduce the number needed to screen to detect patients with positive CAC.
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10.
Machine learning in cardiac CT: Basic concepts and contemporary data.
Singh, G, Al'Aref, SJ, Van Assen, M, Kim, TS, van Rosendael, A, Kolli, KK, Dwivedi, A, Maliakal, G, Pandey, M, Wang, J, et al
Journal of cardiovascular computed tomography. 2018;(3):192-201
Abstract
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular medicine. Owing to the growing body of literature validating both the diagnostic performance as well as the prognostic implications of anatomic and physiologic findings, coronary computed tomography angiography (CCTA) is now a well-established non-invasive modality for the assessment of cardiovascular disease. ML has been increasingly utilized to optimize performance as well as extract data from CCTA as well as non-contrast enhanced cardiac CT scans. The purpose of this review is to describe the contemporary state of ML based algorithms applied to cardiac CT, as well as to provide clinicians with an understanding of its benefits and associated limitations.