Pericoronary and periaortic adipose tissue density are associated with inflammatory disease activity in Takayasu arteritis and atherosclerosis.

AIMS: To examine pericoronary adipose tissue (PCAT) and periaortic adipose tissue (PAAT) density on coronary computed tomography angiography for assessing arterial inflammation in Takayasu arteritis (TAK) and atherosclerosis. METHODS AND RESULTS: PCAT and PAAT density was measured in coronary (n = 1016) and aortic (n = 108) segments from 108 subjects [TAK + coronary artery disease (CAD), n = 36; TAK, n = 18; atherosclerotic CAD, n = 32; matched controls, n = 22]. Median PCAT and PAAT densities varied between groups (mPCAT: P < 0.0001; PAAT: P = 0.0002). PCAT density was 7.01 ± standard error of the mean (SEM) 1.78 Hounsfield Unit (HU) higher in coronary segments from TAK + CAD patients than stable CAD patients (P = 0.0002), and 8.20 ± SEM 2.04 HU higher in TAK patients without CAD than controls (P = 0.0001). mPCAT density was correlated with Indian Takayasu Clinical Activity Score (r = 0.43, P = 0.001) and C-reactive protein (r = 0.41, P < 0.0001) and was higher in active vs. inactive TAK (P = 0.002). mPCAT density above -74 HU had 100% sensitivity and 95% specificity for differentiating active TAK from controls [area under the curve = 0.99 (95% confidence interval 0.97-1)]. The association of PCAT density and coronary arterial inflammation measured by 68Ga-DOTATATE positron emission tomography (PET) equated to an increase of 2.44 ± SEM 0.77 HU in PCAT density for each unit increase in 68Ga-DOTATATE maximum tissue-to-blood ratio (P = 0.002). These findings remained in multivariable sensitivity analyses adjusted for potential confounders. CONCLUSIONS: PCAT and PAAT density are higher in TAK than atherosclerotic CAD or controls and are associated with clinical, biochemical, and PET markers of inflammation. Owing to excellent diagnostic accuracy, PCAT density could be useful as a clinical adjunct for assessing disease activity in TAK.

Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events.

Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk.

Atherosclerosis imaging using PET: Insights and applications.

PET imaging is able to harness biological processes to characterise high-risk features of atherosclerotic plaque prone to rupture. Current radiotracers are able to track inflammation, microcalcification, hypoxia, and neoangiogenesis within vulnerable plaque. 18 F-fluorodeoxyglucose (18 F-FDG) is the most commonly used radiotracer in vascular studies and is employed as a surrogate marker of plaque inflammation. Increasingly, 18 F-FDG and other PET tracers are also being used to provide imaging endpoints in cardiovascular interventional trials. The evolution of novel PET radiotracers, imaging protocols, and hybrid scanners are likely to enable more efficient and accurate characterisation of high-risk plaque. This review explores the role of PET imaging in atherosclerosis with a focus on PET tracers utilised in clinical research and the applications of PET imaging to cardiovascular drug development.

Dual-Tracer Positron-Emission Tomography for Identification of Culprit Carotid Plaques and Pathophysiology In Vivo.

BACKGROUND: Inflammation and microcalcification are interrelated processes contributing to atherosclerotic plaque vulnerability. Positron-emission tomography can quantify these processes in vivo. This study investigates (1) 18F-fluorodeoxyglucose (FDG) and 18F-sodium fluoride (NaF) uptake in culprit versus nonculprit carotid atheroma, (2) spatial distributions of uptake, and (3) how macrocalcification affects this relationship. METHODS: Individuals with acute ischemic stroke with ipsilateral carotid stenosis of ≥50% underwent FDG-positron-emission tomography and NaF-positron-emission tomography. Tracer uptake was quantified using maximum tissue-to-background ratios (TBRmax) and macrocalcification quantified using Agatston scoring. RESULTS: In 26 individuals, median most diseased segment TBRmax (interquartile range) was higher in culprit than in nonculprit atheroma for both FDG (2.08 [0.52] versus 1.89 [0.40]; P<0.001) and NaF (2.68 [0.63] versus 2.39 [1.02]; P<0.001). However, whole vessel TBRmax was higher in culprit arteries for FDG (1.92 [0.41] versus 1.71 [0.31]; P<0.001) but not NaF (1.85 [0.28] versus 1.79 [0.60]; P=0.10). NaF uptake was concentrated at carotid bifurcations, while FDG was distributed evenly throughout arteries. Correlations between FDG and NaF TBRmax differed between bifurcations with low macrocalcification (rs=0.38; P<0.001) versus high macrocalcification (rs=0.59; P<0.001). CONCLUSIONS: This is the first study to demonstrate increased uptake of both FDG and NaF in culprit carotid plaques, with discrete distributions of pathophysiology influencing vulnerability in vivo. These findings have implications for our understanding of the natural history of the disease and for the clinical assessment and management of carotid atherosclerosis.

Vascular Positron Emission Tomography and Restenosis in Symptomatic Peripheral Arterial Disease: A Prospective Clinical Study.

OBJECTIVES: This study determined whether in vivo positron emission tomography (PET) of arterial inflammation (18F-fluorodeoxyglucose [18F-FDG]) or microcalcification (18F-sodium fluoride [18F-NaF]) could predict restenosis following PTA. BACKGROUND: Restenosis following lower limb percutaneous transluminal angioplasty (PTA) is common, unpredictable, and challenging to treat. Currently, it is impossible to predict which patient will suffer from restenosis following angioplasty. METHODS: In this prospective observational cohort study, 50 patients with symptomatic peripheral arterial disease underwent 18F-FDG and 18F-NaF PET/computed tomography (CT) imaging of the superficial femoral artery before and 6 weeks after angioplasty. The primary outcome was arterial restenosis at 12 months. RESULTS: Forty subjects completed the study protocol with 14 patients (35%) reaching the primary outcome of restenosis. The baseline activities of femoral arterial inflammation (18F-FDG tissue-to-background ratio [TBR] 2.43 [interquartile range (IQR): 2.29 to 2.61] vs. 1.63 [IQR: 1.52 to 1.78]; p < 0.001) and microcalcification (18F-NaF TBR 2.61 [IQR: 2.50 to 2.77] vs. 1.69 [IQR: 1.54 to 1.77]; p < 0.001) were higher in patients who developed restenosis. The predictive value of both 18F-FDG (cut-off TBRmax value of 1.98) and 18F-NaF (cut-off TBRmax value of 2.11) uptake demonstrated excellent discrimination in predicting 1-year restenosis (Kaplan Meier estimator, log-rank p < 0.001). CONCLUSIONS: Baseline and persistent femoral arterial inflammation and micro-calcification are associated with restenosis following lower limb PTA. For the first time, we describe a method of identifying complex metabolically active plaques and patients at risk of restenosis that has the potential to select patients for intervention and to serve as a biomarker to test novel interventions to prevent restenosis.