Anouk C. van Dijk

Newly-Diagnosed Disturbed Glucose Metabolism is Associated withAtherosclerosis in Patients with Transient Ischemic Attack or IschemicStroke

Objective: Newly-diagnosed disturbed glucose metabolism is highly prevalent in non-diabetic patients with transient ischemic attack (TIA) or ischemic stroke, and increases the risk of recurrent stroke. Diabetes mellitus is associated with atherosclerosis. We aimed to assess whether newly-diagnosed disturbed glucose metabolism is associated with atherosclerosis as well. Research design and methods: Patients with a recent TIA or ischemic stroke were classified in three groups based on glucose levels and use of antidiabetic drugs. Pre-existent diabetes mellitus was defined as the use of antidiabetic drugs prior to the event. Newly-diagnosed disturbed glucose metabolism was defined as two or more disturbed glucose tests: fasting plasma glucose level ≥ 5.6 mmol/L, 2-hour post-load glucose level ≥ 7.8 mmol/L, and/or glycosylated hemoglobin level ≥ 39 mmol/mol. We used CT-angiography to assess stenosis in the carotid artery bifurcations and calcification volume in the aortic arch, carotid bifurcations and intracranial carotid arteries. The relation between glucose groups and measures of atherosclerosis was expressed as odds ratios and beta coefficients with corresponding 95% CI, adjusted for potential confounders. Results: Of the 1217 patients, 384 (32%) had newly-diagnosed disturbed glucose metabolism, and 210 (17%) had pre-existent diabetes mellitus. Newly-diagnosed disturbed glucose metabolism was independently associated with stenosis ≥ 50% (aOR (95%CI) 1.15 (1.04-2.20)). Pre-existent diabetes mellitus was associated with stenosis ≥ 50% and with calcification volume in all regions, especially in patients without the use of cholesterol-lowering drugs prior to the event. Conclusions: Our study shows that newly-diagnosed disturbed glucose metabolism in patients with a recent TIA or ischemic stroke is associated with more severe extra- and intracranial atherosclerosis, similar to pre-existent diabetes mellitus.

Multi-Center MRI Carotid Plaque Component Segmentation Using Feature Normalization and Transfer Learning

Automated segmentation of plaque components in carotid artery magnetic resonance imaging (MRI) is important to enable large studies on plaque vulnerability, and for incorporating plaque composition as an imaging biomarker in clinical practice. Especially supervised classification techniques, which learn from labeled examples, have shown good performance. However, a disadvantage of supervised methods is their reduced performance on data different from the training data, for example on images acquired with different scanners. Reducing the amount of manual annotations required for each new dataset will facilitate widespread implementation of supervised methods. In this paper we segment carotid plaque components of clinical interest (fibrous tissue, lipid tissue, calcification and intraplaque hemorrhage) in a multi-center MRI study. We perform voxelwise tissue classification by traditional same-center training, and compare results with two approaches that use little or no annotated same-center data. These approaches additionally use an annotated set of different-center data. We evaluate 1) a nonlinear feature normalization approach, and 2) two transfer-learning algorithms that use same and different-center data with different weights. Results showed that the best results were obtained for a combination of feature normalization and transfer learning. While for the other approaches significant differences in voxelwise or mean volume errors were found compared with the reference same-center training, the proposed approach did not yield significant differences from that reference. We conclude that both extensive feature normalization and transfer learning can be valuable for the development of supervised methods that perform well on different types of datasets.

Use of Antiplatelet Agents Is Associated With Intraplaque Hemorrhage on Carotid Magnetic Resonance Imaging The Plaque at Risk Study

Background and Purpose— Intraplaque hemorrhage (IPH), visualized by magnetic resonance imaging, has shown to be associated with the risk of stroke in patients with carotid artery stenosis. The mechanisms of IPH development are poorly understood. In this study, we investigated the association between clinical patient characteristics and carotid IPH on high-resolution magnetic resonance imaging. Methods— Patients participate in the Plaque at Risk (PARISK) study. This prospective, multicenter cohort study included patients with recent amaurosis fugax, hemispheric transient ischemic attack, or nondisabling stroke in the internal carotid artery territory and an ipsilateral carotid stenosis of <70%, who were not scheduled for carotid revascularization procedure. One hundred patients, recruited between 2010 and 2012, underwent a 3-T high-resolution carotid magnetic resonance imaging. We documented clinical patient characteristics and performed multivariable logistic regression analysis to investigate their association with IPH. Results— IPH was observed in 45 patients (45%) in 1 or both carotid arteries. Male sex and the use of antiplatelet agents before the index event were associated with IPH in univariable analysis. In a multivariable analysis, only previous use of antiplatelet agents was significantly associated with IPH (odds ratio, 2.71; 95% confidence interval, 1.12–6.61). Risk factors of atherosclerotic arterial disease, including a history of symptomatic arterial diseases, were not associated with IPH. Conclusions— In this cohort of 100 patients with recently symptomatic carotid stenosis, the previous use of antiplatelet agents is associated with carotid IPH on magnetic resonance imaging. Antiplatelet therapy may increase the risk of IPH, but our findings need to be confirmed in larger patient cohorts. The implications for risk stratification remain to be determined.

Carotid artery lumen segmentation in 3D free-hand ultrasound images using surface graph cuts.

We present a new approach for automated segmentation of the carotid lumen bifurcation from 3D free-hand ultrasound using a 3D surface graph cut method. The method requires only the manual selection of single seed points in the internal, external, and common carotid arteries. Subsequently, the centerline between these points is automatically traced, and the optimal lumen surface is found around the centerline using graph cuts. To refine the result, the latter process was iterated. The method was tested on twelve carotid arteries from six subjects including three patients with a moderate carotid artery stenosis. Our method successfully segmented the lumen in all cases. We obtained an average dice overlap with respect to a manual segmentation of 84% for healthy volunteers. For the patient data, we obtained a dice overlap of 66.7%.

Visualization of Local Changes in Vessel Wall Morphology and Plaque Progression in Serial Carotid Artery Magnetic Resonance Imaging

Carotid atherosclerosis is an important cause of ischemic stroke. Assessment of plaque composition in addition to degree of luminal stenosis can be used to identify patients with increased risk of stroke and assess disease progression. Magnetic resonance imaging (MRI) is an excellent noninvasive imaging technique to assess vessel wall morphology and plaque composition, with good accuracy and reproducibility.1 Serial MRI of the carotid artery is used in several studies which focus on measuring the natural history of carotid artery plaques in symptomatic1 and asymptomatic2 patients and effects of lipid-lowering therapy using statins.3,4 The current standard to analyze serial MRI scans is to compare volume measurements based on manual segmentations of the vessel wall and plaque components. Before comparing the scans, the scans have to be aligned to each other on a slice level. Different approaches exist to align scans from different time points. One study aligns the scans by centering the image stack at each time point over the plaque,1 and another study uses the baseline scan as a reference at the follow-up session to ensure targeting the same arterial segment.4 Alternatively, postprocessing can be used to match the axial images from different time points according to their distance to the carotid bifurcation.2,3 Furthermore, comparison between time points is hindered by inconsistent repositioning of the artery from scan to scan in conjunction with thick image slices. Balu et al5 studied the influence of subject repositioning on measurement precision in serial MRI and identified orientation variability as the most important factor that affected reproducibility. Besides repositioning variability, the current comparison of time points is primarily based on volume measurements, which is a limited representation of the available image data, and no attention is given to local changes or visual …

Heritability and Genome-Wide Association Analyses of Intracranial Carotid Artery Calcification The Rotterdam Study

Background and Purpose— Intracranial carotid artery calcification (ICAC) is one of the most important risk factors for stroke. Although several environmental risk factors for ICAC have been identified, its genetic background remains unclear. Methods— Between 2003 and 2006, 2034 participants from the prospective population-based Rotterdam study (mean age: 69.6±6.8 years; 51.7% female) underwent computed tomography to quantify vascular calcification in the intracranial internal carotid artery. Blood samples were drawn for genotyping. Genotypes of the participants were imputed to the 1000 Genomes reference panel to generate genetic relationship matrices for the estimation of the heritability of ICAC volume. Adjustments were made for age and sex. Subsequently, genome-wide association analyses were performed to identify specific variants. Results— The age- and sex-adjusted heritability (h2) of ICAC was 47% [standard error (SE): 19%; P=0.009]. Genome-wide association analyses identified a variant on chromosome 9p21.3 (rs1537372; N=2034; P=4.75×10−9) and 1 variant on chromosome 11p11.2 (rs11038042, N=2034; P=3.27×10−8) that were significantly associated with ICAC volume. Rs1537372 replicated in an independent sample of 716 stroke patients (Pcombined=1.38×10−10). Conclusions— ICAC volume is a heritable trait, which is partly explained by common genetic variation. We identified specific genetic variants associated with ICAC, which given the importance of ICAC in stroke risk, needs replication in larger-scale studies to further elucidate its genetic basis.

No Association between Thrombin Generation and Intra-Plaque Haemorrhage in Symptomatic Carotid Atherosclerotic Plaques: The Plaque at RISK (PARISK) Study

BACKGROUND  Carotid atherosclerosis is an important cause of stroke. Intra-plaque haemorrhage (IPH) on magnetic resonance imaging (MRI) increases stroke risk. Development of IPH is only partly understood. Thrombin is an essential enzyme in haemostasis. Experimental animal studies have shown conflicting results on the relation between thrombin and plaque vulnerability. We hypothesize that decreased thrombin generation (TG) is associated with IPH and plaque vulnerability. OBJECTIVE  This article investigates whether TG is associated with IPH and other features of plaque vulnerability in stroke patients. METHODS  Recently symptomatic stroke patients underwent carotid MRI and blood sampling. MRI plaque features include plaque burden, presence of IPH, amount of lipid-rich necrotic core (LRNC), calcified tissue and fibrous tissue (% of total wall volume). TG was assessed in platelet-poor plasma and expressed as: peak height (PH) and endogenous thrombin potential (ETP). MR images could be analysed in 224 patients. Blood samples were available in 161 of 224 patients. Binary multivariate logistic and linear regression were used to investigate the association between TG and MRI plaque features. RESULTS  IPH and LRNC were present in 65 (40%) and 102 (63%) of plaques. There were no significant associations between TG and IPH; PH odds ratio (OR) = 1, 95% confidence interval (CI): 0.76 to 1.45 and ETP OR = 1, 95% CI: 0.73 to 1.37. After correction for age, sex and hypercholesterolaemia, the association was weak but non-significant; PH: OR = 0.76, 95% CI: 0.52 to 1.10 and ETP: OR = 0.73, 95% CI: 0.53 to 1.37. CONCLUSION  Features of carotid plaque on MRI show no significant association with TG in stroke patients. Systemic TG does not seem to be an important factor in IPH development.

VESS09. Computed Tomography Angiography Structural Analysis of Carotid Plaque Burden, Juxtaluminal Dark Matter, and Calcification in Symptomatic and Contralateral Asymptomatic Stenosis (30%-70%): What Can Be Learned?

there was an overall increase in true lumen diameter and concomitant decrease in false lumen diameter in both acute and nonacute patients at the level of the largest diameter in both the thoracic and abdominal aorta. At 5 years, 66% of acute and 81% of nonacute patients exhibited either a stable or shrinking transaortic diameter in the thoracic aorta; 52% of acute and 24% of nonacute patients experienced growth in transaortic diameter in the abdominal aorta. Five-year freedom from secondary intervention was 66% 6 8% for acute and 71% 6 9% for nonacute patients (log-rank test, P 1⁄4 .71). Conclusions: Endovascular repair of complicated type B aortic dissection with a composite device design demonstrated low all-cause mortality at 30 days as well as low dissection-related mortality during follow-up. Overall, the acute and nonacute cohorts from the feasibility study appeared to respond similarly to treatment involving use of the stent graft and bare metal stent, demonstrating similar clinical outcomes and favorable aortic remodeling in the thoracic and abdominal aorta.

Evaluating Classifiers for Atherosclerotic Plaque Component Segmentation in MRI

Segmentation of tissue components of atherosclerotic plaques in MRI is promising for improving future treatment strategies of cardiovascular diseases. Several methods have been proposed before with varying results. This study aimed to perform a structured comparison of various classifiers, training set sizes, and MR image sequences to determine the most promising strategy for methodology development. Five different classifiers (linear discriminant classifier (LDC), quadratic discriminant classifier (QDC), random forest (RF), and support vector classifiers with both a linear (SVM\(_{lin}\)) and radial basis function kernel (SVM\(_{rbf}\))) were evaluated. We used carotid MRI data from 124 symptomatic patients, scanned in 4 centres with 2 different MRI protocols (45 and 79 patients). Firstly, learning curves of accuracy as a function of increasing training data size showed stabilisation of performance after using \(\sim \)10–15 patients for training. Best results were found for LDC, QDC and RF. Intraplaque haemorrhage was most accurately classified in both protocols, and lowest accuracy was found for the lipid-rich necrotic core. Secondly, for LDC and RF it was shown that leaving out different MRI sequences usually negatively affects results for one or more classes. However, leaving out T2-weighted scans did not have a big impact. In conclusion, several classifiers obtain generally good results for classification of plaque components in MRI. Identification of intraplaque haemorrhage is the most promising, and lipid-rich necrotic core remains the most difficult.