Thoracic aortic microcalcification activity in combined positron emission tomography and magnetic resonance imaging.

INTRODUCTION: Non-invasive detection of pathological changes in thoracic aortic disease remains an unmet clinical need particularly for patients with congenital heart disease. Positron emission tomography combined with magnetic resonance imaging (PET-MRI) could provide a valuable low-radiation method of aortic surveillance in high-risk groups. Quantification of aortic microcalcification activity using sodium [18F]fluoride holds promise in the assessment of thoracic aortopathies. We sought to evaluate aortic sodium [18F]fluoride uptake in PET-MRI using three methods of attenuation correction compared to positron emission tomography computed tomography (PET-CT) in patients with bicuspid aortic valve, METHODS: Thirty asymptomatic patients under surveillance for bicuspid aortic valve disease underwent sodium [18F]fluoride PET-CT and PET-MRI of the ascending thoracic aorta during a single visit. PET-MRI data were reconstructed using three iterations of attenuation correction (Dixon, radial gradient recalled echo with two [RadialVIBE-2] or four [RadialVIBE-4] tissue segmentation). Images were qualitatively and quantitatively analysed for aortic sodium [18F]fluoride uptake on PET-CT and PET-MRI. RESULTS: Aortic sodium [18F]fluoride uptake on PET-MRI was visually comparable with PET-CT using each reconstruction and total aortic standardised uptake values on PET-CT strongly correlated with each PET-MRI attenuation correction method (Dixon R = 0.70; RadialVIBE-2 R = 0.63; RadialVIBE-4 R = 0.64; p < 0.001 for all). Breathing related artefact between soft tissue and lung were detected using Dixon and RadialVIBE-4 but not RadialVIBE-2 reconstructions, with the presence of this artefact adjacent to the atria leading to variations in blood pool activity estimates. Consequently, quantitative agreements between radiotracer activity on PET-CT and PET-MRI were most consistent with RadialVIBE-2. CONCLUSION: Ascending aortic microcalcification analysis in PET-MRI is feasible with comparable findings to PET-CT. RadialVIBE-2 tissue attenuation correction correlates best with the reference standard of PET-CT and is less susceptible to artefact. There remain challenges in segmenting tissue types in PET-MRI reconstructions, and improved attenuation correction methods are required.

Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography.

Chest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ventricular volumes have classically required administration of contrast. Here we show that a fully automated pipeline, incorporating two artificial intelligence models, automatically quantifies coronary calcium, left atrial volume, left ventricular mass, and other cardiac chamber volumes in 29,687 patients from three cohorts. The model processes chamber volumes and coronary artery calcium with an end-to-end time of ~18 s, while failing to segment only 0.1% of cases. Coronary calcium, left atrial volume, and left ventricular mass index are independently associated with all-cause and cardiovascular mortality and significantly improve risk classification compared to identification of abnormalities by a radiologist. This automated approach can be integrated into clinical workflows to improve identification of abnormalities and risk stratification, allowing physicians to improve clinical decision-making.

AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging.

BACKGROUND: Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features. OBJECTIVES: The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility. METHODS: The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization. RESULTS: In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%. CONCLUSIONS: AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.

PAR4 Antagonism in Patients With Coronary Artery Disease Receiving Antiplatelet Therapies.

BACKGROUND: BMS-986141 is a novel potent highly selective antagonist of PAR (protease-activated receptor) type 4. PAR4 antagonism has been demonstrated to reduce thrombus formation in isolation and in combination with factor Xa inhibition in high shear conditions in healthy people. We sought to determine whether PAR4 antagonism had additive antithrombotic effects in patients with coronary artery disease who were receiving antiplatelet therapy. METHODS: Forty-five patients with stable coronary heart disease and 10 healthy volunteers completed a phase 2a open-label 4-arm single-center study. Patients were allocated to 1 of 3 treatment arms for 7 days: (1) ticagrelor (90 mg BID), (2) aspirin (75 mg QD), or (3) the combination of ticagrelor and aspirin. Agonist-induced platelet aggregation, platelet activation, and ex vivo thrombus formation were measured before and 2 and 24 hours after a single oral 4-mg dose of BMS-986141 on the first study visit day in all participants. RESULTS: BMS-986141 demonstrated highly selective inhibition of PAR4-AP (agonist peptide)-induced platelet aggregation, P-selectin expression, and platelet-monocyte aggregate expression (P≤0.001 for all), which were unaffected by concomitant antiplatelet therapies. PAR4 antagonism reduced ex vivo thrombus area in high shear conditions in healthy volunteers (-21%; P=0.001) and in patients receiving ticagrelor alone (-28%; P=0.001), aspirin alone (-23%; P=0.018), or both in combination (-24%; P≤0.001). Plasma concentration of BMS-986141 correlated with PAR4-AP-induced platelet responses (P≤0.001 for all) and total thrombus area under high shear stress conditions (P≤0.01 for all). CONCLUSIONS: PAR4 antagonism has additive antithrombotic effects when used in addition to ticagrelor, aspirin, or their combination, in patients with stable coronary heart disease. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05093790.

First-in-human controlled inhalation of thin graphene oxide nanosheets to study acute cardiorespiratory responses.

Graphene oxide nanomaterials are being developed for wide-ranging applications but are associated with potential safety concerns for human health. We conducted a double-blind randomized controlled study to determine how the inhalation of graphene oxide nanosheets affects acute pulmonary and cardiovascular function. Small and ultrasmall graphene oxide nanosheets at a concentration of 200 µg m-3 or filtered air were inhaled for 2 h by 14 young healthy volunteers in repeated visits. Overall, graphene oxide nanosheet exposure was well tolerated with no adverse effects. Heart rate, blood pressure, lung function and inflammatory markers were unaffected irrespective of graphene oxide particle size. Highly enriched blood proteomics analysis revealed very few differential plasma proteins and thrombus formation was mildly increased in an ex vivo model of arterial injury. Overall, acute inhalation of highly purified and thin nanometre-sized graphene oxide nanosheets was not associated with overt detrimental effects in healthy humans. These findings demonstrate the feasibility of carefully controlled human exposures at a clinical setting for risk assessment of graphene oxide, and lay the foundations for investigating the effects of other two-dimensional nanomaterials in humans. Clinicaltrials.gov ref: NCT03659864.

CT Attenuation of Periaortic Adipose Tissue in Abdominal Aortic Aneurysms.

Purpose To assess periaortic adipose tissue attenuation at CT angiography in different abdominal aortic aneurysm disease states. Materials and Methods In a retrospective observational study from January 2018 to December 2022, periaortic adipose tissue attenuation was assessed at CT angiography in patients with asymptomatic or symptomatic (including rupture) abdominal aortic aneurysms and controls without aneurysms. Adipose tissue attenuation was measured using semiautomated software in periaortic aneurysmal and nonaneurysmal segments of the abdominal aorta and in subcutaneous and visceral adipose tissue. Periaortic adipose tissue attenuation values between the three groups were assessed using Student t tests and Wilcoxon rank sum tests followed by a multiregression model. Results Eighty-eight individuals (median age, 70 years [IQR, 65-78]; 78 male and 10 female patients) were included: 70 patients with abdominal aortic aneurysms (40 asymptomatic and 30 symptomatic, including 24 with rupture) and 18 controls. There was no evidence of differences in the periaortic adipose tissue attenuation in the aneurysmal segment in asymptomatic patients versus controls (-81.44 HU ± 7 [SD] vs -83.27 HU ± 9; P = .43) and attenuation in nonaneurysmal segments between asymptomatic patients versus controls (-75.43 HU ± 8 vs -78.81 HU ± 6; P = .08). However, symptomatic patients demonstrated higher periaortic adipose tissue attenuation in both aneurysmal (-57.85 HU ± 7; P < .0001) and nonaneurysmal segments (-58.16 HU ± 8; P < .0001) when compared with the other two groups. Conclusion Periaortic adipose tissue CT attenuation was not increased in stable abdominal aortic aneurysm disease. There was a generalized increase in attenuation in patients with symptomatic disease, likely reflecting the systemic consequences of acute rupture. Keywords: Abdominal Aortic Aneurysm, Periaortic Adipose Tissue Attenuation, CT Angiography ClinicalTrials.gov registration no. NCT02229006 © RSNA, 2024.

Accelerated elastin degradation by age-disease interaction: a common feature in age-related diseases.

Aging is a major driving force for many diseases but the relationship between chronological age, the aging process and age-related diseases is not fully understood. Fragmentation and loss of ultra-long-lived elastin are key features in aging and several age-related diseases leading to increased mortality. By comparing the relationship between age and elastin turnover with healthy volunteers, we show that accelerated elastin turnover by age-disease interaction is a common feature of age-related diseases.

Calcium Scoring Improves Clinical Management in Patients With Low Clinical Likelihood of Coronary Artery Disease.

BACKGROUND: Coronary artery calcium scoring (CACS) improves management of chest pain patients. However, it is unknown whether the benefit of CACS is dependent on the clinical likelihood (CL). OBJECTIVES: This study aims to investigate for which patients CACS has the greatest benefit when added to a CL model. METHODS: Based on data from a clinical database, the CL of obstructive coronary artery disease (CAD) was calculated for 39,837 patients referred for cardiac imaging due to symptoms suggestive of obstructive CAD. Patients were categorized according to the risk factor-weighted (RF-CL) model (very low, ≤5%; low, >5 to ≤15%; moderate >15 to ≤50%; high, >50%). CL was then recalculated incorporating the CACS result (CACS-CL). Reclassification rates and the number needed to test with CACS to reclassify patients were calculated and validated in 3 independent cohorts (n = 9,635). RESULTS: In total, 15,358 (39%) patients were down- or upclassified after including CACS. Reclassification rates were 8%, 75%, 53%, and 30% in the very low, low, moderate, and high RF-CL categories, respectively. Reclassification to very low CACS-CL occurred in 48% of reclassified patients. The number needed to test to reclassify 1 patient from low RF-CL to very low CACS-CL was 2.1 with consistency across age, sex, and cohorts. CACS-CL correlated better to obstructive CAD prevalence than RF-CL. CONCLUSIONS: Added to an RF-CL model for obstructive CAD, CACS identifies more patients unlikely to benefit from further testing. The number needed to test with CACS to reclassify patients depends on the pretest RF-CL and is lowest in patients with low (>5% to ≤15%) likelihood of CAD.

Assessment of the alpha 7 nicotinic acetylcholine receptor as an imaging marker of cardiac repair-associated processes using NS14490.

BACKGROUND: Cardiac repair and remodeling following myocardial infarction (MI) is a multifactorial process involving pro-reparative inflammation, angiogenesis and fibrosis. Noninvasive imaging using a radiotracer targeting these processes could be used to elucidate cardiac wound healing mechanisms. The alpha7 nicotinic acetylcholine receptor (ɑ7nAChR) stimulates pro-reparative macrophage activity and angiogenesis, making it a potential imaging biomarker in this context. We investigated this by assessing in vitro cellular expression of ɑ7nAChR, and by using a tritiated version of the PET radiotracer [18F]NS14490 in tissue autoradiography studies. RESULTS: ɑ7nAChR expression in human monocyte-derived macrophages and vascular cells showed the highest relative expression was within macrophages, but only endothelial cells exhibited a proliferation and hypoxia-driven increase in expression. Using a mouse model of inflammatory angiogenesis following sponge implantation, specific binding of [3H]NS14490 increased from 3.6 ± 0.2 µCi/g at day 3 post-implantation to 4.9 ± 0.2 µCi/g at day 7 (n = 4, P < 0.01), followed by a reduction at days 14 and 21. This peak matched the onset of vessel formation, macrophage infiltration and sponge fibrovascular encapsulation. In a rat MI model, specific binding of [3H]NS14490 was low in sham and remote MI myocardium. Specific binding within the infarct increased from day 14 post-MI (33.8 ± 14.1 µCi/g, P ≤ 0.01 versus sham), peaking at day 28 (48.9 ± 5.1 µCi/g, P ≤ 0.0001 versus sham). Histological and proteomic profiling of ɑ7nAChR positive tissue revealed strong associations between ɑ7nAChR and extracellular matrix deposition, and rat cardiac fibroblasts expressed ɑ7nAChR protein under normoxic and hypoxic conditions. CONCLUSION: ɑ7nAChR is highly expressed in human macrophages and showed proliferation and hypoxia-driven expression in human endothelial cells. While NS14490 imaging displays a pattern that coincides with vessel formation, macrophage infiltration and fibrovascular encapsulation in the sponge model, this is not the case in the MI model where the ɑ7nAChR imaging signal was strongly associated with extracellular matrix deposition which could be explained by ɑ7nAChR expression in fibroblasts. Overall, these findings support the involvement of ɑ7nAChR across several processes central to cardiac repair, with fibrosis most closely associated with ɑ7nAChR following MI.

Artificial intelligence-based automated left ventricular mass quantification from non-contrast cardiac CT scans: correlation with contrast CT and cardiac MRI.

Background: Non-contrast CT scans are not used for evaluating left ventricle myocardial mass (LV mass), which is typically evaluated with contrast CT or cardiovascular magnetic resonance imaging (MRI). We assessed the feasibility of LV mass estimation from standard, ECG-gated, non-contrast CT using an artificial intelligence (AI) approach and compare it with coronary CT angiography (CTA) and cardiac MRI. Methods: We enrolled consecutive patients who underwent coronary CTA, which included non-contrast CT calcium scanning and contrast CTA, and cardiac MRI. The median interval between coronary CTA and MRI was 22 days (IQR: 3-76). We utilized an nn-Unet AI model that automatically segmented non-contrast CT structures. AI measurement of LV mass was compared to contrast CTA and MRI. Results: A total of 316 patients (Age: 57.1±16.7, 56% male) were included. The AI segmentation took on average 22 seconds per case. An excellent correlation was observed between AI and contrast CTA LV mass measures (r=0.84, p<0.001), with no significant differences (136.5±55.3 vs. 139.6±56.9 g, p=0.133). Bland-Altman analysis showed minimal bias of 2.9. When compared to MRI, measured LV mass was higher with AI (136.5±55.3 vs. 127.1±53.1 g, p<0.001). There was an excellent correlation between AI and MRI (r=0.85, p<0.001), with a small bias (-9.4). There were no statistical differences between the correlations of LV mass between contrast CTA and MRI, or AI and MRI. Conclusions: The AI-based automated estimation of LV mass from non-contrast CT demonstrated excellent correlations and minimal biases when compared to contrast CTA and MRI.

Exercise electrocardiography for pre-test assessment of the likelihood of coronary artery disease.

OBJECTIVES: To develop a tool including exercise electrocardiography (ExECG) for patient-specific clinical likelihood estimation of patients with suspected obstructive coronary artery disease (CAD). METHODS: An ExECG-weighted clinical likelihood (ExECG-CL) model was developed in a training cohort of patients with suspected obstructive CAD undergoing ExECG. Next, the ExECG-CL model was applied in a CAD validation cohort undergoing ExECG and clinically driven invasive coronary angiography and a prognosis validation cohort and compared with the risk factor-weighted clinical likelihood (RF-CL) model for obstructive CAD discrimination and prognostication, respectively.In the CAD validation cohort, obstructive CAD was defined as >50% diameter stenosis on invasive coronary angiography. For prognosis, the endpoint was non-fatal myocardial infarction and death. RESULTS: The training cohort consisted of 1214 patients (mean age 57 years, 57% males). In the CAD (N=408; mean age 55 years, 53% males) and prognosis validation (N=3283; mean age 57 years, 57% males) cohorts, 11.8% patients had obstructive CAD and 4.4% met the endpoint. In the CAD validation cohort, discrimination of obstructive CAD was similar between the ExECG-CL and RF-CL models: area under the receiver-operating characteristic curves 83.1% (95% CIs 77.5% to 88.7%) versus 80.7% (95% CI 74.6% to 86.8%), p=0.14. In the ExECG-CL model, more patients had very low (≤5%) clinical likelihood of obstructive CAD compared with the RF-CL (42.2% vs 36.0%, p<0.01) where obstructive CAD prevalence and event risk remained low. CONCLUSIONS: ExECG incorporated into a clinical likelihood model improves reclassification of patients to a very low clinical likelihood group with very low prevalence of obstructive CAD and favourable prognosis.

Roadmap on the use of artificial intelligence for imaging of vulnerable atherosclerotic plaque in coronary arteries.

Artificial intelligence (AI) is likely to revolutionize the way medical images are analysed and has the potential to improve the identification and analysis of vulnerable or high-risk atherosclerotic plaques in coronary arteries, leading to advances in the treatment of coronary artery disease. However, coronary plaque analysis is challenging owing to cardiac and respiratory motion, as well as the small size of cardiovascular structures. Moreover, the analysis of coronary imaging data is time-consuming, can be performed only by clinicians with dedicated cardiovascular imaging training, and is subject to considerable interreader and intrareader variability. AI has the potential to improve the assessment of images of vulnerable plaque in coronary arteries, but requires robust development, testing and validation. Combining human expertise with AI might facilitate the reliable and valid interpretation of images obtained using CT, MRI, PET, intravascular ultrasonography and optical coherence tomography. In this Roadmap, we review existing evidence on the application of AI to the imaging of vulnerable plaque in coronary arteries and provide consensus recommendations developed by an interdisciplinary group of experts on AI and non-invasive and invasive coronary imaging. We also outline future requirements of AI technology to address bias, uncertainty, explainability and generalizability, which are all essential for the acceptance of AI and its clinical utility in handling the anticipated growing volume of coronary imaging procedures.

External validation of novel clinical likelihood models to predict obstructive coronary artery disease and prognosis.

OBJECTIVES: The risk factor-weighted and coronary artery calcium score-weighted clinical likelihood (RF-CL and CACS-CL, respectively) models improve discrimination of patients with suspected obstructive coronary artery disease (CAD). However, external validation is warranted.Compared to the 2019 European Society of Cardiology pretest probability (ESC-PTP) model, the aims were (1) to validate the RF-CL and CACS-CL models for identification of obstructive CAD and revascularisation, and (2) to investigate prognosis by CL thresholds. METHODS: Stable de novo chest pain patients (n=1585) undergoing coronary CT angiography (CTA) were investigated. Obstructive CAD was defined as >70% diameter stenosis in a major epicardial vessel on CTA. Decision of revascularisation within 120 days was based on onsite judgement. The endpoint was non-fatal myocardial infarction or cardiovascular death. The ESC-PTP was calculated based on age, sex and symptom typicality, the RF-CL additionally included number of risk factors, and the CACS-CL incorporated CACS to the RF-CL. RESULTS: Obstructive CAD was present in 386/1585 (24.4%) patients, and 91/1585 (5.7%) patients underwent revascularisation. Both the RF-CL and CACS-CL classified more patients to very-low CL (<5%) of obstructive CAD compared with the ESC-PTP model (41.4% and 52.2% vs 19.2%, p<0.001). In very-low CL patients, obstructive CAD and revascularisation prevalences (≤6% and <1%) remained similar combined with low event risk during 5.0 years follow-up. CONCLUSION: In an external validation cohort, the novel RF-CL and CACS-CL models improve categorisation to a very-low CL group with preserved prevalences of obstructive CAD, revascularisation and favourable prognosis.

Noninvasive Coronary Atherosclerotic Plaque Imaging.

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.

Targeting the apelin system for the treatment of cardiovascular diseases.

Cardiovascular disease is the leading cause of death worldwide. Its prevalence is rising due to ageing populations and the increasing incidence of diseases such as chronic kidney disease, obesity, and diabetes that are associated with elevated cardiovascular risk. Despite currently available treatments, there remains a huge burden of cardiovascular disease-associated morbidity for patients and healthcare systems, and newer treatments are needed. The apelin system, comprising the apelin receptor and its two endogenous ligands apelin and elabela, is a broad regulator of physiology that opposes the actions of the renin-angiotensin and vasopressin systems. Activation of the apelin receptor promotes endothelium-dependent vasodilatation and inotropy, lowers blood pressure, and promotes angiogenesis. The apelin system appears to protect against arrhythmias, inhibits thrombosis, and has broad anti-inflammatory and anti-fibrotic actions. It also promotes aqueous diuresis through direct and indirect (central) effects in the kidney. Thus, the apelin system offers therapeutic promise for a range of cardiovascular, kidney, and metabolic diseases. This review will discuss current cardiovascular disease targets of the apelin system and future clinical utility of apelin receptor agonism.

Implementation of a high sensitivity cardiac troponin I assay and risk of myocardial infarction or death at five years: observational analysis of a stepped wedge, cluster randomised controlled trial.

OBJECTIVE: To evaluate the impact of implementing a high sensitivity assay for cardiac troponin I on long term outcomes in patients with suspected acute coronary syndrome. DESIGN: Secondary observational analysis of a stepped wedge, cluster randomised controlled trial. SETTING: 10 secondary and tertiary care centres in Scotland, UK. PARTICIPANTS: 48 282 consecutive patients with suspected acute coronary syndrome. Myocardial injury was defined as any high sensitivity assay result for cardiac troponin I >99th centile of 16 ng/L in women and 34 ng/L in men. INTERVENTION: Hospital sites were randomly allocated to either early (n=5 hospitals) or late (n=5 hospitals) implementation of a high sensitivity cardiac troponin I assay with sex specific diagnostic thresholds. MAIN OUTCOME MEASURE: The main outcome was myocardial infarction or death at five years. RESULTS: 10 360 patients had cardiac troponin concentrations greater than the 99th centile, of whom 1771 (17.1%) were reclassified by the high sensitivity assay. The five year incidence of subsequent myocardial infarction or death before and after implementation of the high sensitivity assay was 29.4% (5588/18 978) v 25.9% (7591/29 304), respectively, in all patients (adjusted hazard ratio 0.97, 95% confidence interval 0.93 to 1.01), and 63.0% (456/720) v 53.9% (567/1051), respectively, in those reclassified by the high sensitivity assay (0.82, 0.72 to 0.94). After implementation of the high sensitivity assay, a reduction in subsequent myocardial infarction or death was observed in patients with non-ischaemic myocardial injury (0.83, 0.75 to 0.91) but not in those with type 1 or type 2 myocardial infarction (0.92, 0.83 to 1.01 and 0.98, 0.84 to 1.14). CONCLUSIONS: Implementation of a high sensitivity cardiac troponin I assay in the assessment of patients with suspected acute coronary syndrome was associated with a reduced risk of subsequent myocardial infarction or death at five years in those reclassified by the high sensitivity assay. Improvements in outcome were greatest in patients with non-ischaemic myocardial injury, suggesting a broader benefit beyond the identification of myocardial infarction. TRIAL REGISTRATION: ClinicalTrials.gov NCT01852123.

Aortic valve perivascular adipose tissue computed tomography attenuation in patients with aortic stenosis.

OBJECTIVE: Aortic stenosis (AS) shares pathophysiological similarities with atherosclerosis including active inflammation. CT attenuation of perivascular adipose tissue provides a measure of vascular inflammation that is linked to prognosis and has the potential to be applied to the aortic valve. We investigated perivascular adipose tissue attenuation around the aortic valve in patients with AS. METHODS: CT attenuation was measured in the perivascular adipose tissue extending 3 mm radially and 10 mm longitudinally around the aortic valve in patients with and without AS. Associations between perivascular adipose tissue attenuation and AS disease severity, activity and progression were investigated. RESULTS: Perivascular adipose tissue attenuation around the aortic valve demonstrated good intraobserver and interobserver repeatability (interobserver: intraclass correlation coefficient 0.977 (95% CI: 0.94, 0.99)) but was similar between patients with AS (n=120) and control subjects (n=80) (-62.4 (-68.7, -56.5) Hounsfield units (HU) vs -61.2 (-65.3, -55.6) HU, p=0.099). There were no differences between perivascular adipose tissue attenuation in patients with mild (-60.2 (-66.9, -55.1) HU), moderate (-62.8 (-69.6, -56.80) HU) or severe (-62.3 (-69.3, -55.4) HU) AS (all p>0.05), and perivascular adipose tissue attenuation did not demonstrate an association with AS severity as assessed by echocardiography or CT calcium scoring, nor with disease activity assessed by 18F-sodium fluoride positron emission tomography. Moreover, there was no association between baseline aortic valve perivascular adipose tissue attenuation and subsequent AS progression (annualised change in peak velocity: r=0.072, p=0.458). Similar results were found using five other image analysis methods. CONCLUSIONS: CT-derived aortic valve perivascular adipose tissue attenuation is not associated with AS disease severity, activity or progression suggesting that it has no value in the investigation and management of patients with AS.