Carotid Atheroinflammation Is Associated With Cerebral Small Vessel Disease Severity.

Background: Atherosclerosis is a systemic inflammatory disease, with common inflammatory processes implicated in both atheroma vulnerability and blood-brain barrier disruption. This prospective multimodal imaging study aimed to measure directly the association between systemic atheroma inflammation ("atheroinflammation") and downstream chronic cerebral small vessel disease severity. Methods: Twenty-six individuals with ischemic stroke with ipsilateral carotid artery stenosis of >50% underwent 18fluoride-fluorodeoxyglucose-positron emission tomography within 2 weeks of stroke. Small vessel disease severity and white matter hyperintensity volume were assessed using 3-tesla magnetic resonance imaging also within 2 weeks of stroke. Results: Fluorodeoxyglucose uptake was independently associated with more severe small vessel disease (odds ratio 6.18, 95% confidence interval 2.1-18.2, P < 0.01 for the non-culprit carotid artery) and larger white matter hyperintensity volumes (coefficient = 14.33 mL, P < 0.01 for the non-culprit carotid artery). Conclusion: These proof-of-concept results have important implications for our understanding of the neurovascular interface and potential therapeutic exploitation in the management of systemic atherosclerosis, particularly non-stenotic disease previously considered asymptomatic, in order to reduce the burden of chronic cerebrovascular disease

Imaging Atherosclerosis.

Advances in atherosclerosis imaging technology and research have provided a range of diagnostic tools to characterize high-risk plaque in vivo; however, these important vascular imaging methods additionally promise great scientific and translational applications beyond this quest. When combined with conventional anatomic- and hemodynamic-based assessments of disease severity, cross-sectional multimodal imaging incorporating molecular probes and other novel noninvasive techniques can add detailed interrogation of plaque composition, activity, and overall disease burden. In the catheterization laboratory, intravascular imaging provides unparalleled access to the world beneath the plaque surface, allowing tissue characterization and measurement of cap thickness with micrometer spatial resolution. Atherosclerosis imaging captures key data that reveal snapshots into underlying biology, which can test our understanding of fundamental research questions and shape our approach toward patient management. Imaging can also be used to quantify response to therapeutic interventions and ultimately help predict cardiovascular risk. Although there are undeniable barriers to clinical translation, many of these hold-ups might soon be surpassed by rapidly evolving innovations to improve image acquisition, coregistration, motion correction, and reduce radiation exposure. This article provides a comprehensive review of current and experimental atherosclerosis imaging methods and their uses in research and potential for translation to the clinic.J.M.T. is supported by a Wellcome Trust research training fellowship (104492/Z/14/Z). M.D is supported by the British Heart Foundation (FS/14/78/31020). N.R.E. is supported by a research training fellowship from the Dunhill Medical Trust (RTF44/0114). A.J.B. is supported by the British Heart Foundation. J.H.F.R. is part-supported by the HEFCE, the NIHR Cambridge Biomedical Research Centre, the British Heart Foundation, and the Wellcome Trust.This is the final version of the article. It first appeared from the American Heart Association via http://dx.doi.org/10.1161/CIRCRESAHA.115.30624

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

open20siAcknowledgements: EPVL is undertaking a PhD funded by the Cambridge School of Clinical Medicine, Frank Edward Elmore Fund and the Medical Research Council’s Doctoral Training Partnership [award reference: 1966157]. JMT is supported by a Wellcome Trust Clinical Research Career Development Fellowship [211100/Z/18/Z], the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre and the British Heart Foundation Cambridge Centre of Research Excellence. NRE was supported by a Research Training Fellowship from The Dunhill Medical Trust [RTF44/0114]. MMC was supported by fellowships from the Royal College of Surgeons of England, and the British Heart Foundation [BHF; FS/16/29/31957]. HP is undertaking a PhD with a BHF CRE studentship. FJG is an NIHR Senior Investigator. LR and ES were supported by The Mark Foundation for Cancer Research and Cancer Research UK (CRUK) Cambridge Centre [C9685/A25177]. MR is supported by AstraZeneca Oncology R&amp;D. ES receives additional support provided by the NIHR Cambridge Biomedical Research Centre. FAG receives funding from CRUK. EAW receives support from the NIHR CRN. CBS acknowledges support from the Leverhulme Trust project on ‘Breaking the non-convexity barrier’, the Philip Leverhulme Prize, the EPSRC grants EP/S026045/1 and EP/T003553/1, the EPSRC Centre Nr. EP/N014588/1, the Wellcome Innovator Award RG98755, European Union Horizon 2020 research and innovation programmes under the Marie Skodowska-Curie grant agreement No. 777826 NoMADS and No. 691070 CHiPS, the Cantab Capital Institute for the Mathematics of Information and the Alan Turing Institute. JHFR is part-supported by the NIHR Cambridge Biomedical Research Centre, the British Heart Foundation, HEFCE, the Wellcome Trust and the EPSRC grant [EP/N014588/1] for the University of Cambridge Centre for Mathematical Imaging in Healthcare. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.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.noneLe E.P.V.; Rundo L.; Tarkin J.M.; Evans N.R.; Chowdhury M.M.; Coughlin P.A.; Pavey H.; Wall C.; Zaccagna F.; Gallagher F.A.; Huang Y.; Sriranjan R.; Le A.; Weir-McCall J.R.; Roberts M.; Gilbert F.J.; Warburton E.A.; Schonlieb C.-B.; Sala E.; Rudd J.H.F.Le E.P.V.; Rundo L.; Tarkin J.M.; Evans N.R.; Chowdhury M.M.; Coughlin P.A.; Pavey H.; Wall C.; Zaccagna F.; Gallagher F.A.; Huang Y.; Sriranjan R.; Le A.; Weir-McCall J.R.; Roberts M.; Gilbert F.J.; Warburton E.A.; Schonlieb C.-B.; Sala E.; Rudd J.H.F

Triple-gated motion and blood pool clearance corrections improve reproducibility of coronary 18F-NaF PET

PurposeTo improve the test-retest reproducibility of coronary plaque 18F-sodium fluoride (18F-NaF) positron emission tomography (PET) uptake measurements.MethodsWe recruited 20 patients with coronary artery disease who underwent repeated hybrid PET/CT angiography (CTA) imaging within 3&nbsp;weeks. All patients had 30-min PET acquisition and CTA during a single imaging session. Five PET image-sets with progressive motion correction were reconstructed: (i) a static dataset (no-MC), (ii) end-diastolic PET (standard), (iii) cardiac motion corrected (MC), (iv) combined cardiac and gross patient motion corrected (2 × MC) and, (v) cardiorespiratory and gross patient motion corrected (3 × MC). In addition to motion correction, all datasets were corrected for variations in the background activities which are introduced by variations in the injection-to-scan delays (background blood pool clearance correction, BC). Test-retest reproducibility of PET target-to-background ratio (TBR) was assessed by Bland-Altman analysis and coefficient of reproducibility.ResultsA total of 47 unique coronary lesions were identified on CTA. Motion correction in combination with BC improved the PET TBR test-retest reproducibility for all lesions (coefficient of reproducibility: standard = 0.437, no-MC = 0.345 (27% improvement), standard&nbsp;+&nbsp;BC = 0.365 (20% improvement), no-MC + BC = 0.341 (27% improvement), MC + BC = 0.288 (52% improvement), 2 × MC + BC = 0.278 (57% improvement) and 3 × C + BC = 0.254 (72% improvement), all p &lt; 0.001). Importantly, in a sub-analysis of 18F-NaF-avid lesions with gross patient motion &gt;&nbsp;10&nbsp;mm following corrections, reproducibility was improved by 133% (coefficient of reproducibility: standard = 0.745, 3 × MC = 0.320).ConclusionJoint corrections for cardiac, respiratory, and gross patient motion in combination with background blood pool corrections markedly improve test-retest reproducibility of coronary 18F-NaF PET

Greater aortic inflammation and calcification in abdominal aortic aneurysmal disease than atherosclerosis: a prospective matched cohort study

Funder: British Heart Foundation; FundRef: http://dx.doi.org/10.13039/501100000274Objective: Using combined positron emission tomography and CT (PET-CT), we measured aortic inflammation and calcification in patients with abdominal aortic aneurysms (AAA), and compared them with matched controls with atherosclerosis. Methods: We prospectively recruited 63 patients (mean age 76.1±6.8 years) with asymptomatic aneurysm disease (mean size 4.33±0.73 cm) and 19 age-and-sex-matched patients with confirmed atherosclerosis but no aneurysm. Inflammation and calcification were assessed using combined 18F-FDG PET-CT and quantified using tissue-to-background ratios (TBRs) and Agatston scores. Results: In patients with AAA, 18F-FDG uptake was higher within the aneurysm than in other regions of the aorta (mean TBRmax2.23±0.46 vs 2.12±0.46, p=0.02). Compared with atherosclerotic control subjects, both aneurysmal and non-aneurysmal aortae showed higher 18F-FDG accumulation (total aorta mean TBRmax2.16±0.51 vs 1.70±0.22, p=0.001; AAA mean TBRmax2.23±0.45 vs 1.68±0.21, p<0.0001). Aneurysms containing intraluminal thrombus demonstrated lower 18F-FDG uptake within their walls than those without (mean TBRmax2.14±0.43 vs 2.43±0.45, p=0.018), with thrombus itself showing low tracer uptake (mean TBRmax thrombus 1.30±0.48 vs aneurysm wall 2.23±0.46, p<0.0001). Calcification in the aneurysmal segment was higher than both non-aneurysmal segments in patients with aneurysm (Agatston 4918 (2901–8008) vs 1017 (139–2226), p<0.0001) and equivalent regions in control patients (442 (304-920) vs 166 (80-374) Agatston units per cm, p=0.0042). Conclusions: The entire aorta is more inflamed in patients with aneurysm than in those with atherosclerosis, perhaps suggesting a generalised inflammatory aortopathy in patients with aneurysm. Calcification was prominent within the aneurysmal sac, with the remainder of the aorta being relatively spared. The presence of intraluminal thrombus, itself metabolically relatively inert, was associated with lower levels of inflammation in the adjacent aneurysmal wall

PET Molecular Targets and Near-Infrared Fluorescence Imaging of Atherosclerosis

PURPOSE OF REVIEW: With this review, we aim to summarize the role of positron emission tomography (PET) and near-infrared fluorescence imaging (NIRF) in the detection of atherosclerosis. RECENT FINDINGS: (18)F-FDG is an established measure of increased macrophage activity. However, due to its low specificity, new radiotracers have emerged for more specific detection of vascular inflammation and other high-risk plaque features such as microcalcification and neovascularization. Novel NIRF probes are engineered to sense endothelial damage as an early sign of plaque erosion as well as oxidized low-density lipoprotein (oxLDL) as a prime target for atherosclerosis. Integrated NIRF/OCT (optical coherence tomography) catheters enable to detect stent-associated microthrombi. Novel radiotracers can improve specificity of PET for imaging atherosclerosis. Advanced NIRF probes show promise for future application in human. Intravascular NIRF might play a prominent role in the detection of stent-induced vascular injury

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

AimsTo 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 resultsPCAT 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 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 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.ConclusionsPCAT 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

Funder: School of Clinical Medicine, University of Cambridge; doi: http://dx.doi.org/10.13039/501100007552Funder: Frank Edward Elmore FundFunder: National Institute for Health Research (NIHR) Imperial Biomedical Research CentreFunder: British Heart Foundation Cambridge Centre of Research ExcellenceFunder: Royal College of Surgeons of England; doi: http://dx.doi.org/10.13039/501100000297Funder: Cancer Research UK; doi: http://dx.doi.org/10.13039/501100000289Funder: AstraZeneca Oncology RFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272Funder: Leverhulme Trust; doi: http://dx.doi.org/10.13039/501100000275Funder: Cantab Capital Institute for the Mathematics of InformationFunder: Alan Turing Institute; doi: http://dx.doi.org/10.13039/100012338Funder: NIHR Cambridge Biomedical Research CentreFunder: Higher Education Funding Council for England; doi: http://dx.doi.org/10.13039/501100000384Abstract: 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

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

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