Abstract
This 2022 European Atherosclerosis Society lipoprotein(a) Lp(a) consensus statement updates evidence for the role of Lp(a) in atherosclerotic cardiovascular disease (ASCVD) and aortic valve ...stenosis, provides clinical guidance for testing and treating elevated Lp(a) levels, and considers its inclusion in global risk estimation. Epidemiologic and genetic studies involving hundreds of thousands of individuals strongly support a causal and continuous association between Lp(a) concentration and cardiovascular outcomes in different ethnicities; elevated Lp(a) is a risk factor even at very low levels of low-density lipoprotein cholesterol. High Lp(a) is associated with both microcalcification and macrocalcification of the aortic valve. Current findings do not support Lp(a) as a risk factor for venous thrombotic events and impaired fibrinolysis. Very low Lp(a) levels may associate with increased risk of diabetes mellitus meriting further study. Lp(a) has pro-inflammatory and pro-atherosclerotic properties, which may partly relate to the oxidized phospholipids carried by Lp(a). This panel recommends testing Lp(a) concentration at least once in adults; cascade testing has potential value in familial hypercholesterolaemia, or with family or personal history of (very) high Lp(a) or premature ASCVD. Without specific Lp(a)-lowering therapies, early intensive risk factor management is recommended, targeted according to global cardiovascular risk and Lp(a) level. Lipoprotein apheresis is an option for very high Lp(a) with progressive cardiovascular disease despite optimal management of risk factors. In conclusion, this statement reinforces evidence for Lp(a) as a causal risk factor for cardiovascular outcomes. Trials of specific Lp(a)-lowering treatments are critical to confirm clinical benefit for cardiovascular disease and aortic valve stenosis.
Abstract Objectives Cardiac magnetic resonance (CMR) was used to investigate the extracellular compartment and myocardial fibrosis in patients with aortic stenosis, as well as their association with ...other measures of left ventricular decompensation and mortality. Background Progressive myocardial fibrosis drives the transition from hypertrophy to heart failure in aortic stenosis. Diffuse fibrosis is associated with extracellular volume expansion that is detectable by T1 mapping, whereas late gadolinium enhancement (LGE) detects replacement fibrosis. Methods In a prospective observational cohort study, 203 subjects (166 with aortic stenosis 69 years; 69% male; 37 healthy volunteers 68 years; 65% male) underwent comprehensive phenotypic characterization with clinical imaging and biomarker evaluation. On CMR, we quantified the total extracellular volume of the myocardium indexed to body surface area (iECV). The iECV upper limit of normal from the control group (22.5 ml/m2 ) was used to define extracellular compartment expansion. Areas of replacement mid-wall LGE were also identified. All-cause mortality was determined during 2.9 ± 0.8 years of follow up. Results iECV demonstrated a good correlation with diffuse histological fibrosis on myocardial biopsies (r = 0.87; p < 0.001; n = 11) and was increased in patients with aortic stenosis (23.6 ± 7.2 ml/m2 vs. 16.1 ± 3.2 ml/m2 in control subjects; p < 0.001). iECV was used together with LGE to categorize patients with normal myocardium (iECV <22.5 ml/m2 ; 51% of patients), extracellular expansion (iECV ≥22.5 ml/m2 ; 22%), and replacement fibrosis (presence of mid-wall LGE, 27%). There was evidence of increasing hypertrophy, myocardial injury, diastolic dysfunction, and longitudinal systolic dysfunction consistent with progressive left ventricular decompensation (all p < 0.05) across these groups. Moreover, this categorization was of prognostic value with stepwise increases in unadjusted all-cause mortality (8 deaths/1,000 patient-years vs. 36 deaths/1,000 patient-years vs. 71 deaths/1,000 patient-years, respectively; p = 0.009). Conclusions CMR detects ventricular decompensation in aortic stenosis through the identification of myocardial extracellular expansion and replacement fibrosis. This holds major promise in tracking myocardial health in valve disease and for optimizing the timing of valve replacement. (The Role of Myocardial Fibrosis in Patients With Aortic Stenosis; NCT01755936 )
Vascular calcification is a hallmark of atherosclerosis. The location, density, and confluence of calcification may change portions of the arterial conduit to a noncompliant structure. Calcifications ...may also seed the cap of a thin cap fibroatheroma, altering tensile forces on the cap and rendering the lesion prone to rupture. Many local and systemic factors participate in this process, including hyperlipidemia, ongoing inflammation, large necrotic cores, and diabetes. Vascular cells can undergo chondrogenic or osteogenic differentiation, causing mineralization of membranous bone and formation of endochondral bone. Calcifying vascular cells are derived from local smooth muscle cells and circulating hematopoietic stem cells (especially in intimal calcification). Matrix vesicles in the extracellular space of the necrotic core serve as a nidus for calcification. Although coronary calcification is a marker of coronary atheroma, dense calcification (>400 HU) is usually associated with stable plaques. Conversely, microcalcification (often also referred to as spotty calcification) is more commonly an accompaniment of vulnerable plaques. Recent studies have suggested that microcalcification in the fibrous cap may increase local tissue stress (depending on the proximity of one microcalcific locus to another, and the orientation of the microcalcification in reference to blood flow), resulting in plaque instability. It has been proposed that positron emission tomography imaging with sodium fluoride may identify early calcific deposits and hence high-risk plaques.
The first-line evaluation of aortic stenosis severity is Doppler echocardiography. However, in up to 40% of patients, resting echocardiographic assessment of aortic stenosis severity is discordant, ...leading to clinical uncertainty. Interest has therefore grown in aortic valve calcium scoring by multidetector computed tomography (CT-AVC) as an alternative load independent assessment of aortic stenosis severity. This paper will briefly review the pathophysiology of aortic stenosis and the crucial role that calcification plays in driving progressive obstruction of the valve. Subsequently, it will describe published reports that have investigated CT-AVC, validating this parameter against histology, and establishing its diagnostic accuracy versus echocardiography as well as its powerful independent prognostic capability. Finally, this review seeks to provide a practical guide about how best to acquire and interpret CT-AVC with a close focus on potential pitfalls and how these might be best avoided as this technique becomes more widely adopted in to clinical practice.
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•Measurement of aortic valve calcification is useful in assessing aortic stenosis severity in patients for whom echocardiography is not conclusive.•Aortic valve calcification should be measured on noncontrast electrocardiogram-gated computer tomography scans (120 kV to 140 kV; 60% to 80% RR interval) with the use of the Agatston method.•Calcification of left ventricular outflow tract, aorta, mitral annulus, and coronary arteries should carefully be excluded from the measurement of aortic valve calcification.•An aortic valve calcification score higher than 1,300 AU in women or 2,000 AU in men should be considered severe.
Abstract Objectives The purpose of this study was to explore the diagnostic usefulness of hybrid cardiac magnetic resonance (CMR) and positron emission tomography (PET) using 18F-fluorodeoxyglucose ...(FDG) for active cardiac sarcoidosis. Background Active cardiac sarcoidosis (aCS) is underdiagnosed and has a high mortality. Methods Patients with clinical suspicion of aCS underwent hybrid CMR/PET with late gadolinium enhancement (LGE) and FDG to assess the pattern of injury and disease activity, respectively. Patients were categorized visually as magnetic resonance (MR)+PET+ (characteristic LGE aligning exactly with increased FDG uptake), MR+PET− (characteristic LGE but no increased FDG), MR−PET− (neither characteristic LGE nor increased FDG), and MR−PET+ (increased FDG uptake in absence of characteristic LGE) and further characterized as aCS+ (MR+PET+) or aCS− (MR+PET−, MR−PET−, MR−PET+). FDG uptake was quantified using maximum target-to-normal-myocardium ratio and the net uptake rate ( K i ) from dynamic Patlak analysis. Receiver operating characteristic methods were used to identify imaging biomarkers for aCS. FDG PET was assessed using computed tomography/PET in 19 control subjects with healthy myocardium. Results A total of 25 patients (12 males; 54.9 ± 9.8 years of age) were recruited prospectively; 8 were MR+PET+, suggestive of aCS; 1 was MR+PET−, consistent with inactive cardiac sarcoidosis; and 8 were MR−PET−, with no imaging evidence of cardiac sarcoidosis. Eight patients were MR−PET+ (6 with global myocardial FDG uptake, 2 with focal-on-diffuse uptake); they demonstrated distinct K i values and hyperintense maximum standardized uptake value compared with MR+PET+ patients. Similar hyperintense patterns of global (n = 9) and focal-on-diffuse (n = 2) FDG uptake were also observed in control patients, suggesting physiological myocardial uptake. Maximum target-to-normal-myocardium ratio values were higher in the aCS+ group (p < 0.001), demonstrating an area under the curve of 0.98 on receiver operating characteristic analysis for the detection of aCS, with an optimal maximum target-to-normal myocardium ratio threshold of 1.2 (Youden index: 0.94). Conclusions CMR/PET imaging holds major promise for the diagnosis of aCS, providing incremental information about both the pattern of injury and disease activity in a single scan. (In Vivo Molecular Imaging MRI of Atherothrombotic Lesions; NCT01418313 )
Abstract
Background
Coronary inflammation induces dynamic changes in the balance between water and lipid content in perivascular adipose tissue (PVAT), as captured by perivascular Fat Attenuation ...Index (FAI) in standard coronary CT angiography (CCTA). However, inflammation is not the only process involved in atherogenesis and we hypothesized that additional radiomic signatures of adverse fibrotic and microvascular PVAT remodelling, may further improve cardiac risk prediction.
Methods and results
We present a new artificial intelligence-powered method to predict cardiac risk by analysing the radiomic profile of coronary PVAT, developed and validated in patient cohorts acquired in three different studies. In Study 1, adipose tissue biopsies were obtained from 167 patients undergoing cardiac surgery, and the expression of genes representing inflammation, fibrosis and vascularity was linked with the radiomic features extracted from tissue CT images. Adipose tissue wavelet-transformed mean attenuation (captured by FAI) was the most sensitive radiomic feature in describing tissue inflammation (TNFA expression), while features of radiomic texture were related to adipose tissue fibrosis (COL1A1 expression) and vascularity (CD31 expression). In Study 2, we analysed 1391 coronary PVAT radiomic features in 101 patients who experienced major adverse cardiac events (MACE) within 5 years of having a CCTA and 101 matched controls, training and validating a machine learning (random forest) algorithm (fat radiomic profile, FRP) to discriminate cases from controls (C-statistic 0.77 95%CI: 0.62–0.93 in the external validation set). The coronary FRP signature was then tested in 1575 consecutive eligible participants in the SCOT-HEART trial, where it significantly improved MACE prediction beyond traditional risk stratification that included risk factors, coronary calcium score, coronary stenosis, and high-risk plaque features on CCTA (ΔC-statistic = 0.126, P < 0.001). In Study 3, FRP was significantly higher in 44 patients presenting with acute myocardial infarction compared with 44 matched controls, but unlike FAI, remained unchanged 6 months after the index event, confirming that FRP detects persistent PVAT changes not captured by FAI.
Conclusion
The CCTA-based radiomic profiling of coronary artery PVAT detects perivascular structural remodelling associated with coronary artery disease, beyond inflammation. A new artificial intelligence (AI)-powered imaging biomarker (FRP) leads to a striking improvement of cardiac risk prediction over and above the current state-of-the-art.
Although aortic stenosis is a common condition associated with major morbidity, mortality, and health economic costs, there are currently no medical interventions capable of delaying or halting its ...progression. Re-evaluation of the underlying pathophysiology is therefore required so that novel therapeutic strategies can be developed. Aortic stenosis is characterized by progressive aortic valve narrowing and secondary left ventricular hypertrophy. Both processes are important because in combination they drive the development of symptoms and adverse events that characterize the latter stages of the disease. In this review, the authors examine the pathophysiology of aortic stenosis with respect to both the valve and the myocardium. In particular, the authors focus on the role of inflammation, fibrosis, and calcification in progressive valve narrowing and then examine the development of left ventricular hypertrophy, its subsequent decompensation, and the transition to heart failure. Finally the authors discuss potential therapeutic strategies on the basis of similarities aortic stenosis shares with other pathological conditions.
Aortic stenosis is a common, potentially fatal condition that is set to become an increasing public health burden. Once symptoms develop, there is an inexorable deterioration with a poor prognosis. ...Despite this, there are no medical therapies capable of modifying disease progression, and the only available treatment is aortic valve replacement, to which not all patients are suited. Conventional teaching suggests that aortic stenosis is a degenerative condition whereby "wear and tear" leads to calcium deposition within the valve. Although mechanical stress and injury are important factors, it is becoming increasingly appreciated that aortic stenosis is instead governed by a highly complex, regulated pathological process with similarities to skeletal bone formation. This review discusses the pathophysiology of aortic stenosis with an emphasis on the emerging importance of calcification, how this can be visualized and monitored using noninvasive imaging, and how our improved knowledge may ultimately translate into novel disease-modifying treatments.
Aortic stenosis is characterized both by progressive valve narrowing and the left ventricular remodeling response that ensues. The only effective treatment is aortic valve replacement, which is ...usually recommended in patients with severe stenosis and evidence of left ventricular decompensation. At present, left ventricular decompensation is most frequently identified by the development of typical symptoms or a marked reduction in left ventricular ejection fraction <50%. However, there is growing interest in using the assessment of myocardial fibrosis as an earlier and more objective marker of left ventricular decompensation, particularly in asymptomatic patients, where guidelines currently rely on nonrandomized data and expert consensus. Myocardial fibrosis has major functional consequences, is the key pathological process driving left ventricular decompensation, and can be divided into 2 categories. Replacement fibrosis is irreversible and identified using late gadolinium enhancement on cardiac magnetic resonance, while diffuse fibrosis occurs earlier, is potentially reversible, and can be quantified with cardiac magnetic resonance T1 mapping techniques. There is a substantial body of observational data in this field, but there is now a need for randomized clinical trials of myocardial imaging in aortic stenosis to optimize patient management. This review will discuss the role that myocardial fibrosis plays in aortic stenosis, how it can be imaged, and how these approaches might be used to track myocardial health and improve the timing of aortic valve replacement.
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