Background: In this study a multiscore analysis of various biomarkers including matrix metalloproteinases (MMPs), inflammatory factors and other clinical parameters was performed to establish a set of reliable biomarkers for improved detection of plaque instability in patients with advanced carotid stenosis. Methods: Study patients (n = 101) were classified as histologically stable (n = 37) or unstable (n = 64). Serum levels of MMP-1, -2, -3, -7, -8, -9, MMP inhibitors TIMP-1, -2, and inflammatory factors such as tumor necrosis factor (TNF-α), interleukin (IL)-1β, -6, -8, -10, and -12 were measured by ELISA assays. Multiscore analysis was performed using multiple receiver operating characteristics analysis and determination of appropriate cutoff values. Results: Circulating levels of MMP-1, -7, TIMP-1, TNF-α, and IL-8 were significantly enhanced in patients with unstable plaques compared to individuals with stable lesions, mean differences being 1.2 (p = 0.032), 2.5 (p = 0.004), 30.0 (p = 0.014), 1.3 (p = 0.047), and 2.2 (p = 0.033), respectively. The combination of MMP-1, -7, TIMP-1 and IL-8 demonstrated the highest positive predictive value of 89.4% and negative predictive value of 60.1% for patients correctly classified as individuals with unstable and stable carotid lesions by means of blood sample analysis. Conclusions: Multiple relevant biomarkers that play a decisive role in plaque instability can improve the correct determination of vulnerable carotid plaques in patients with advanced carotid artery stenosis.

PurposeThe aim of this study was to investigate prospectively whether MRI plaque imaging can identify patients with asymptomatic carotid artery stenosis who have an increased risk for future cerebral events. MRI plaque imaging allows categorization of carotid stenosis into different lesion types (I–VIII). Within these lesion types, lesion types IV–V and VI are regarded as rupture-prone plaques, whereas the other lesion types represent stable ones.MethodsEighty-three consecutive patients (45 male (54.2%); age 54–88 years (mean 73.2 years)) presenting with an asymptomatic carotid stenosis of 50–99% according to ECST-criteria were recruited. Patients were imaged with a 1.5-T scanner. T1-, T2-, time-of-flight-, and proton-density weighted studies were performed. The carotid plaques were classified as lesion type I–VIII. Clinical endpoints were ischemic stroke, TIA or amaurosis fugax. Survival analysis and log rank test were used to ascertain statistical significance.ResultsSix out of 83 patients (7.2%) were excluded: 4 patients had insufficient MR image quality; 1 patient was lost-to-follow-up; 1 patient died shortly after the baseline MRI plaque imaging. The following results were obtained by analyzing the remaining 77 patients. The mean time of follow-up was 41.1 months.During follow-up, n = 9 (11.7%) ipsilateral ischemic cerebrovascular events occurred. Only patients presenting with the high-risk lesion types IV–V and VI developed an ipsilateral cerebrovascular event versus none of the patients presenting with the stable lesion types III, VII, and VIII (n = 9 (11.7%) vs. n = 0 (0%) during follow-up). Event-free survival was higher among patients with the MRI-defined stable lesion types (III, VII, and VIII) than in patients with the high-risk lesion types (IV–V and VI) (log rank test P<0.0001).ConclusionsMRI plaque imaging has the potential to identify patients with asymptomatic carotid stenosis who are particularly at risk of developing future cerebral ischemia. MRI could improve selection criteria for invasive therapy in the future.

The peri-infarct cortex (PIC) is the site of long-term physiologic changes after ischemic stroke. Traditional methods for delineating the peri-infarct gray matter (GM) have used a volumetric Euclidean distance metric to define its extent around the infarct. This metric has limitations in the case of cortical stroke, i.e., those where ischemia leads to infarction in the cortical GM, because the vascularization of the cerebral cortex follows the complex, folded topology of the cortical surface. Instead, we used a geodesic distance metric along the cortical surface to subdivide the PIC into equidistant rings emanating from the infarct border and compared this new approach to a Euclidean distance metric definition. This was done in 11 patients with [F-18]-Flumazenil ([18-F]-FMZ) positron emission tomography (PET) scans at 2 weeks post-stroke and at 6 month follow-up. FMZ is a PET radiotracer with specific binding to the alpha subunits of the type A γ-aminobutyric acid (GABAA) receptor. Additionally, we used partial-volume correction (PVC) of the PET images to compensate for potential cortical thinning and long-term neuronal loss in follow-up images. The difference in non-displaceable binding potential (BP ) between the stroke unaffected and affected hemispheres was 35% larger in the geodesic versus the Euclidean peri-infarct models in initial PET images and 48% larger in follow-up PET images. The inter-hemispheric BP difference was approximately 17-20% larger after PVC when compared to uncorrected PET images. PET studies of peri-infarct GM in cortical strokes should use a geodesic model and include PVC as a preprocessing step. Hum Brain Mapp 38:326-338, 2017. © 2016 Wiley Periodicals, Inc.

Early recognition of vulnerable patients is an important issue for stroke prevention. In our study, a multiscore analysis of various biomarkers was performed to evaluate its superiority over the analysis of single factors. Study subjects (n = 110) were divided into four groups: asymptomatic patients with stable (n = 25) and unstable (n = 36) plaques and symptomatic patients with stable (n = 13) and unstable (n = 36) plaques. Serum levels of MMP-1, -2, -3, -7, -8, -9, TIMP-1, -2, TNF-α, IL-1b, and IL-6, -8, -10, -12 were measured. Multi-score analysis was performed using multiple receiver operating characteristics (ROC) and determination of appropriate cutoff values. Significant differences between the groups were observed for MMP-1, -7, -9 and TIMP-1 in serum of the study subjects (P < 0.05). Multiple biomarker analysis led to a significant increase in the AUC (area under curve). In case of plaque instability, positive predictive value (PPV) for up to 86.4% could be correctly associated with vulnerable plaques. Thus, multiscore analysis might be preferable than the use of single biomarkers.

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