Images Of Common Carotid Artery Research Articles

Preprocessing techniques with medical ultrasound common carotid artery images

Preprocessing techniques with medical ultrasound common carotid artery images

Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm.

Stroke and cardiovascular diseases (CVD) significantly affect the world population. The early detection of such events may prevent the burden of death and costly surgery. Conventional methods are neither automated nor clinically accurate. Artificial Intelligence-based methods of automatically detecting and predicting the severity of CVD and stroke in their early stages are of prime importance. This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy determination. The results of the Attention-UNet model are benchmarked against UNet, UNet++, and UNet3P models. Visual plaque segmentation showed improvement in the Attention-UNet results compared to the other three models. The correlation coefficient (CC) value for Attention-UNet is 0.96, compared to 0.93, 0.96, and 0.92 for UNet, UNet++, and UNet3P models. Similarly, the AUC value for Attention-UNet is 0.97, compared to 0.964, 0.966, and 0.965 for other models. Conclusively, the Attention-UNet model is beneficial in segmenting very bright and fuzzy plaque images that are hard to diagnose using other methods. Further, we present a multi-ethnic, multi-center, racial bias-free study of stroke risk assessment.

Encoder-Decoder Architecture for Ultrasound IMC Segmentation and cIMT Measurement.

Cardiovascular diseases (CVDs) have shown a huge impact on the number of deaths in the world. Thus, common carotid artery (CCA) segmentation and intima-media thickness (IMT) measurements have been significantly implemented to perform early diagnosis of CVDs by analyzing IMT features. Using computer vision algorithms on CCA images is not widely used for this type of diagnosis, due to the complexity and the lack of dataset to do it. The advancement of deep learning techniques has made accurate early diagnosis from images possible. In this paper, a deep-learning-based approach is proposed to apply semantic segmentation for intima-media complex (IMC) and to calculate the cIMT measurement. In order to overcome the lack of large-scale datasets, an encoder-decoder-based model is proposed using multi-image inputs that can help achieve good learning for the model using different features. The obtained results were evaluated using different image segmentation metrics which demonstrate the effectiveness of the proposed architecture. In addition, IMT thickness is computed, and the experiment showed that the proposed model is robust and fully automated compared to the state-of-the-art work.

Effect of despeckling filters on the segmentation of ultrasound common carotid artery images

BackgroundCarotid intima-media thickness (IMT) measured in B-mode ultrasound image is an important indicator of Atherosclerosis disease. Speckle noise inherently present in ultrasounds’ thereby degrades the visual evaluation and limits the automated segmentation performance. The objective of this study is to investigate the effects of three despeckle filters on the segmentation of carotid IMT in ultrasound image. MethodsAutomated segmentation of IMT is achieved by utilizing fast fuzzy c-mean clustering and distance-regularized level set without re-initialization techniques. Manual segmentation has been done by an experienced radiologist. The performances of median, hybrid median and improved adaptive complex diffusion (IACDF) filters are examined and a quantitative and qualitative comparison among these filters has been reported on 151 DICOM images. Bland–Altman plots were used to compare IMT results of these filters.Furthermore, performances of above three filters are evaluated under different noise levels by individually adding speckle and salt and pepper noise in ten randomly selected images from 151 DICOM dataset. Plots between noise and quality evaluation metric parameters are used to compare de-noising performance of these filters. ResultsThe average processing time per image of proposed IMT measurement technique without-filter and with filter is approx 15.39 s max. ConclusionIt is shown that the median filter (window 5 × 5) measures better than hybrid median and IACDF filters. Finally, concluded that de-noising of ultrasound image before segmentation procedure certainly improves segmentation accuracy. Furthermore, it is observed that these filters do not impose serious computational burden and entail moderate processing time.

Association of carotid wall layers with atherosclerotic plaques and cardiac hypertrophy in hypertensive subjects.

Carotid intima-media thickness (cIMT) is considered a marker of subclinical atherosclerosis and is related to target-organ damage in hypertensive patients. However, increased cIMT may be due to increases in the thickness of intima (cIT) and media (cMT) layers. This study evaluated whether cIMT layers (cIT and cMT) had a greater association with carotid atherosclerotic plaques and left ventricular hypertrophy (LVH) than cIMT in hypertensive subjects. We cross-sectionally evaluated clinical, carotid, and echocardiography characteristics of 186 hypertensive patients followed at an outpatient clinic. High-resolution images of common carotid arteries were obtained by ultrasonography equipped with 10-MHz transducers, and cIT, cMT, and cIMT were manually measured using an image-processing software. Among all participants (n = 186; age = 60.8 ± 10.9 years, 43% males), there were 58% with carotid plaques and 58% with LVH. Mean cIT, cMT, and cIMT values were 0.267 ± 0.060, 0.475 ± 0.107, and 0.742 ± 0.142 mm, respectively. In logistic regression analysis adjusted for relevant covariates, carotid plaques showed stronger association with cIT than with cMT and cIMT. Furthermore, cIT showed greater area under the ROC curve (0.92; 95% CI 0.87-0.96) than cIMT (0.79; 95% CI 0.72-0.85) and cMT (0.64; 95% CI 0.56-0.72) to identify plaques. Conversely, cIT, cMT, and cIMT had modest association and accuracy to identify LVH (area under the ROC curve = 0.61, 0.57, and 0.60, respectively). In conclusion, cIT is a more accurate marker of atherosclerosis than cMT or cIMT, while cIT and cMT provide no incremental value in identifying LVH when compared with cIMT among hypertensive subjects.

Geometric Total Plaque Area Is an Equally Powerful Phenotype Compared With Carotid Intima-Media Thickness for Stroke Risk Assessment: A Deep Learning Approach

Currently, carotid intima-media thickness (cIMT) and geometric total plaque area (gTPA) are computed manually and thus are tedious and prone to interobserver and intraobserver variabilities. This study presents an intelligence-based automated deep learning (DL)–based technique for carotid wall interface detection, cIMT, and lumen diameter (LD) measurements, followed by a 3D cylindrical approach for TPA measurement. The observers were used for manual tracings of which were then used for the design of two DL-based systems. The DL boundaries for inner lumen wall and outer interadventitial borders were used for computing the cIMT and LD. Using cylindrical approach, we computed the gTPA. Furthermore, we compute the 10-year image-based cIMT and gTPA, using the progression rates. A total of 396 B-mode ultrasound right and left common carotid artery images were taken from 203 patients. The mean cIMT and gTPA using DL1 and DL2 is 0.91 mm, 20.52 mm2 and 0.88 mm, 19.44 mm2, respectively. The coefficient of correlation between gTPA and cIMT using DL1 and DL2 is 0.92 ( P < .001) and 0.94 ( P < .001), respectively. The area under the curve (AUC) for gTPA showed an improvement over cIMT by 14.36% and 12.57% for DL1 and DL2, respectively. The corresponding 10-year risk improvements were 9.09% and 6.26%. Our statistical significance tests successfully passed t test, Mann-Whitney, Wilcoxon, Kolmogorov-Smirnov, and Friedman. The study shows gTPA as an equally powerful carotid risk biomarker like cIMT. Given the cIMT and LD, cylindrical fitting is a fast method for gTPA measurements.

Efficient initialisation of distance-regularised level set without re-initialisation scheme and quantitative evaluation of IMT in B mode ultrasound common carotid artery images

Segmentation of the Common Carotid Artery (CCA) wall is imperative for the estimation of the Intima Media Thickness (IMT) in B-mode longitudinal ultrasound images. IMT is considered as the prominent indicator of atherosclerosis and is defined as the distance between Lumen-Intima (LI) and Media-Adventitia (MA) interfaces of CCA vessel. This paper proposes an efficient initialisation scheme for Distance-Regularised Level Set without re-initialisation Evolution (DRLSE) method by utilising Fast Fuzzy C-Mean clustering (FFCM) technique to detect Li and MA interfaces accurately. Distance between the detected interfaces is determined by Polyline Distance Metric (PDM). Also, a quantitative and qualitative comparison among proposed method, manual method and snake method is presented. Experimental results show that the proposed method is robust in terms of region of interest selection (ROI), noise (speckle as well as salt and pepper) and images acquired from different machines. Inter-method, inter-operator and intra-operator variability have been studied by computing average, standard deviation, Coefficient of Variation (CV%) and via Wilcoxon’s signed-rank test (at p < 0.05). Reported results demonstrate close agreement between manual and proposed methods. The proposed method is semiautomatic and bears an advantage that a tight ROI is not required which encourages its use in clinical practice.

Common carotid artery intima-media thickness increases throughout the pregnancy cycle: a prospective cohort study

BackgroundHigh parity is associated with greater cardiovascular disease (CVD) among mid-life and older women. Prospective studies of arterial change throughout pregnancy are needed to provide insight into potential mechanisms. This study assessed vascular adaptation across pregnancy in healthy first-time pregnant women.MethodsThe Maternal Vascular Adaptation to Healthy Pregnancy Study (Pittsburgh, PA, 2010–2015) assessed 37 primigravid women each trimester, 6–8 weeks after delivery and 1–5 years postpartum, with B-mode ultrasound imaging of common carotid artery (CCA) intima-media thickness (IMT) and inter-adventitial diameter (IAD) to assess associations with physical and cardiometabolic measures.ResultsThirty-seven women (age 28.2 ± 4.5 years, pre-pregnant BMI 24.4 ± 3.2 kg/m2) experienced uncomplicated pregnancies. After adjustment for age and pre-pregnancy BMI, mean (SE) IAD (mm) increased each trimester, from 6.38 (0.08) in the 1st trimester to 6.92 (0.09) in the 3rd trimester, and then returned to 1st trimester levels postpartum (6.35 [0.07], P <  0.001). In contrast, mean (SE) CCA IMT (mm) increased from the 2nd trimester (i.e., 0.546 [0.01]) onward, and remained higher at an average of 2.7 years postpartum (0.581 [0.02], P = 0.03). Weight partially explained changes in IAD.ConclusionsIn uncomplicated first pregnancies, IAD increased and returned to 1st trimester levels postpartum. In contrast, CCA IMT remained increased 2 years postpartum. Maternal weight explained vascular changes better than did metabolic changes. Increased postpartum CCA IMT may persist and contribute to long-term CVD risk.

Carotid plaque thickness and carotid plaque burden predict future cardiovascular events in asymptomatic adult Americans.

Prediction of cardiovascular events improves using imaging, i.e. coronary calcium score and ultrasound assessment of carotid plaque. This study analysed the predictive value of two ultrasound measures of carotid plaque size: carotid plaque thickness and carotid and intima-media thickness (IMT). A total of 6102 asymptomatic persons underwent assessment of conventional risk factors and imaging by carotid ultrasound. Carotid plaque burden (cPB) and maximum carotid plaque thickness (cPTmax) were measured from 'cross-sectional sweep' video acquisition of the carotid artery. IMT was measured from distal common carotid artery images. All participants were followed up for ∼3 years, and major cardiovascular events (MACE) were collected and adjudicated. All data were available for 5808 participants, in whom 216 first MACE events were observed. Increasing both cPB and cPTmax were associated with increasing the risk of future MACE when compared with participants without carotid atherosclerosis. Fully adjusted for risk factors, hazard ratios for cPTmax were 1.96 [95% confidence interval (CI) 0.91-4.25, P = 0.015] for primary MACE and 3.13 (95% CI 1.80-5.51, P < 0.001) for secondary MACE, similar to that of cPB. IMT did not improve risk prediction significantly. Non-categorical net reclassification index (NRI) for cPTmax was 0.178 (95% CI 0.027-0.299, P = 0.032) for primary MACE and 0.173 (95% CI 0.109-0.243, P < 0.001) for secondary MACE, which is almost similar to cPB. IMT assessment did not result in significant NRI. The simpler cPTmax predicted cardiovascular events similarly to the more comprehensive cPB, whereas IMT did not. Awaiting true 3D ultrasound technology cPTmax may be a simple useful measure for prediction of future ASCVD.

Developing a bio-inspired multi-gene genetic programming based intelligent estimator to reduce speckle noise from ultrasound images

The speckle noise commonly occurs in ultrasound imaging based applications. Due to the multiplicative nature, speckle noise deteriorates the visual quality of ultrasound images. This affects the performance of radiologists and practitioners for disease diagnosis and/or patient treatment. The current study proposes a bio-inspired multi-gene genetic programming (MGGP) based intelligent estimator to reduce the speckle noise from ultrasound images. The proposed MGGP approach is based on the parallel framework of multiple genes and has effectively utilized the evolutionary learning capabilities to develop an intelligent estimator, by exploiting the useful statistical features extracted from local neighboring pixels. The performance of the proposed novel approach is evaluated on ultrasound images of common carotid artery corrupted with different noise levels. Further, the robust performance was validated on several diverse types of ultrasound images of Breast Cyst, Kidney Cancer, Liver, Liver Cyst, and Fetal Head. The proposed bio-inspired approach showed superior denoising performance over existing approaches. The proposed intelligent estimator is capable of removing speckle noise effectively while preserving the fine lines and edges. During evolution, the MGGP framework automatically selects the useful statistical features and primitive functions from a wider solution space to develop the intelligent estimator. Further, the proposed approach does not require image-dependent optimal threshold values, as conventional speckle denoising approaches required.

Arterial-ventricular coupling and parameters of vascular stiffness in hypertensive patients: Role of gender.

ObjectiveNon-invasive estimation of arterial–ventricular coupling has been extensively used for the evaluation of cardiovascular performance, however, a relative small amount of data is available regarding arterial–ventricular coupling and its components in hypertension. The present study was designed to investigate the relationship between left ventricular elastance, arterial elastance, parameters of vascular stiffness and the influence of gender in a population of hypertensive individuals.MethodsIn 102 patients, trans-thoracic cardiac ultrasound, parameters of aortic stiffness (carotid-femoral pulse wave velocity) and wave reflection (augmentation index) were recorded. Ultrasound images of common carotid arteries were acquired for the assessment of intima-media thickness as well as carotid compliance and distensibility coefficient.ResultsMean age was 61 years, 32% diabetes, 56% dyslipidemia, 9% previous cardiovascular events; women (n = 32) and men were superimposable for cardiovascular risk factors prevalence. In the population, ventricular elastance was significantly correlated with arterial elastance (r = 0.887), age (r = 0.334), gender (r = −0.494), BMI (r = −0.313), augmentation index (r = 0.479) (all p < 0.001); and with carotid compliance and distensibility coefficient (r = 0.229 and r = − 0.250, respectively, both p < 0.05); however, only arterial elastance and gender were independently associated with ventricular elastance in multiple regression models adjusted for confounding factors. Gender-specific analysis revealed that arterial elastance and augmentation index remained statistically significant associated with ventricular elastance in men (r = 0.275, p = 0.04); instead augmentation index was no longer significant (r = 0.052, p = 0.77) in the female sex.ConclusionsIn hypertensive patients, main determinants of ventricular elastance are arterial elastance, as an integrated index of arterial vascular load, and gender; however, pressure augmentation might play an additional role in men.

Ultrasound-Based Automated Carotid Lumen Diameter/Stenosis Measurement and its Validation System

Objective Degree of carotid stenosis is an important predictor to assess risk of stroke. Systolic velocity-based methods for lumen diameter and stenosis measurement are subjective. Image-based methods face a challenge because of low gradients in media and intima walls. Methods This article presents AtheroEdge™ 2.0, a two-stage process for automated carotid lumen diameter measurement that combats the above challenges. Stage one uses spectral analysis based on the hypothesis that far-wall adventitia is brightest. Stage two uses lumen pixel region identification based on the assumption that blood flow has constant density. Using global and local processing, lumen boundaries are detected. This clinical system outputs lumen diameter along with stenosis severity index (SSI). Results Our database consists of institutional review board–approved 202 patients (males/females: 155/47) left and right common carotid artery images (404 images, Toshiba scanner). Two trained neuro radiologists performed manual lumen border tracings using ImgTracer™ software. The coefficient of correlation between automated and two manual readings was 0.91 and 0.92. Dice similarity and Jaccard index were 95.82%, 95.72% and 92.10%, 91.92%, respectively. The mean diameter error between automated and two manual readings was 0.27 ± 0.26 and 0.26 ± 0.28 mm, respectively. Precision of merit was 98.05% and 99.03% with respect to two readings. SSI showed 97% accuracy. Conclusions The image-based automated carotid lumen diameter and stenosis measurement system is fast, accurate, and reliable.

Assessment of noise reduction in ultrasound images of common carotid and brachial arteries

The present study assessed the use of filters for noise reduction in ultrasound images of the common carotid artery (CCA) and brachial artery using intima–media thickness, which is a safe and non-invasive technique for determining subclinical atherosclerosis and cardiovascular risk. A new combined speckle reducing anisotropic diffusion (SRAD) filter for noise reduction is then proposed. Ultrasonic examination of both arteries was performed on 30 men (aged 40 ± 5 years). The programme was designed using MATLAB software to extract consecutive images in bit map format from the audio video interleaves. An additional programme was designed in MATLAB to apply the region of interest (ROI) to the thickness of the intima–media of the posterior walls of the arteries. Block-matching techniques were used to estimate arterial motion from ultrasound images of the B-mode CCA and brachial artery. Different noise reduction filters and Canny edge detection were carried out separately in the ROI. The programme measured mean square error (MSE) and peak signal-to-noise ratio (PSNR). The results demonstrated that the new combined SRAD filter with Canny edge detection identified the lowest value for MSE and the highest value for PSNR in 90 consecutive frames (∼3 cardiac cycles). The results indicate that MSE and PSNR were better detected by the proposed combined SRAD filter with Canny edge detection than did several commonly used filters with Canny detection for speckle suppression and preservation detail in carotid and brachial arteries ultrasound images.

Abstract 509: Accurate Measurement of Carotid Lumen Diameter and Narrowing Utilizing Ultrasound

Introduction: Ultrasound is often used for monitoring of carotid disease. In current clinical practice, degree of stenosis is an important predictor to assess stroke risk. Lumen narrowing from plaque is currently measured via techniques such as computed tomographic scan, magnetic resonance angiogram or conventional angiogram. Duplex ultrasound measures degree of stenosis based on peak systolic velocities and other parameters and only provides a wide range of level of stenosis. Pursuing lumen size measurement in ultrasound via manual quantification of lumen diameter is tedious. Furthermore, non-uniformity in plaque growth makes it more challenging and time-consuming. There has been an increasing interest in the automatic and robust delineation of the lumen boundaries of the carotids and to measure the lumen diameter via ultrasound given its non-invasive and safe approach. Methods: Deidentified carotid ultrasound images were obtained on patients retrospectively who underwent carotid ultrasound at Toho University Ohashi Medical Center, Tokyo, Japan. A higher order derivative Gaussian filter is applied on these images to highlight the edges. Using pixel classification, lumen region is detected and lumen boundaries are estimated. Results: Of the 202 patients with common carotid artery images, 155 were males and 47 were females.Mean age 69 ± 15.9 years. Mean HbA1c, LDL, HDL and Cholesterol of patients were 6.28±1.1 mg/dl, 101.27±31.6 mg/dl, 50.26±14.8 mg/dl and 175.04±38 mg/dl, respectively. Specialist trained in carotid ultrasound manually traced lumen diameter. Automated tracing and lumen measurements were obtained. The coefficient of correlation between automated diameter and manual diameter was: 0.88, 0.91 and 0.93. The mean diameter error between automated and manual tracing were: 0.50±0.37 mm, 0.36±0.34 mm and 0.30±0.28 mm. Precision of merit between automated diameter and manual diameter was: 93.28%, 95.33% and 96.32% corresponding to manual tracers. Conclusions: The automated lumen diameter measurement is near real time, quick, accurate, fully automated and reliable to assess carotid lumen diameter and narrowing.

Fully automatic segmentation of ultrasound common carotid artery images based on machine learning

Atherosclerosis is responsible for a large proportion of cardiovascular diseases (CVD), which are the leading cause of death in the world. The atherosclerotic process is a complex degenerative condition mainly affecting the medium- and large-size arteries, which begins in childhood and may remain unnoticed during decades. It causes thickening and the reduction of elasticity in the blood vessels. An early diagnosis of this condition is crucial to prevent patients from suffering more serious pathologies (heart attacks and strokes). The evaluation of the Intima-Media Thickness (IMT) of the Common Carotid Artery (CCA) in B-mode ultrasound images is considered the most useful tool for the investigation of preclinical atherosclerosis. Usually, it is manually measured by the radiologists. This paper proposes a fully automatic segmentation technique based on Machine Learning and Statistical Pattern Recognition to measure IMT from ultrasound CCA images. The pixels are classified by means of artificial neural networks to identify the IMT boundaries. Moreover, the concepts of Auto-Encoders (AE) and Deep Learning have been included in the classification strategy. The suggested approach is tested on a set of 55 longitudinal ultrasound images of the CCA by comparing the automatic segmentation with four manual tracings.

A review of ultrasound common carotid artery image and video segmentation techniques.

The determination of the wall thickness [intima-media thickness (IMT)], the delineation of the atherosclerotic carotid plaque, the measurement of the diameter in the common carotid artery (CCA), as well as the grading of its stenosis are important for the evaluation of the atherosclerosis disease. All these measurements are also considered to be significant markers for the clinical evaluation of the risk of stroke. A number of CCA segmentation techniques have been proposed in the last few years either for the segmentation of the intima-media complex (IMC), the lumen of the CCA, or for the atherosclerotic carotid plaque from ultrasound images or videos of the CCA. The present review study proposes and discusses the methods and systems introduced so far in the literature for performing automated or semi-automated segmentation in ultrasound images or videos of the CCA. These are based on edge detection, active contours, level sets, dynamic programming, local statistics, Hough transform, statistical modeling, neural networks, and an integration of the above methods. Furthermore, the performance of these systems is evaluated and discussed based on various evaluation metrics. We finally propose the best performing method that can be used for the segmentation of the IMC and the atherosclerotic carotid plaque in ultrasound images and videos. We end the present review study with a discussion of the different image and video CCA segmentation techniques, future perspectives, and further extension of these techniques to ultrasound video segmentation and wall tracking of the CCA. Future work on the segmentation of the CCA will be focused on the development of integrated segmentation systems for the complete segmentation of the CCA as well as the segmentation and motion analysis of the plaque and or the IMC from ultrasound video sequences of the CCA. These systems will improve the evaluation, follow up, and treatment of patients affected by advanced atherosclerosis disease conditions.

Anisotropic diffusion filter based edge enhancement for the segmentation of carotid intima-media layer in ultrasound images using variational level set method without re-initialisation.

In this work an attempt has been made to enhance the edges and segment the boundary of intima-media layer of Common Carotid Artery (CCA) using anisotropic diffusion filter and level set method. Ultrasound B mode longitudinal images of normal and abnormal images of common carotid arteries are used in this study. The images are subjected to anisotropic diffusion filter to generate edge map. This edge map is used as a stopping boundary in variational level set method without re-initialisation to segment the intima-media layer. Geometric features are extracted from this layer and analyzed statistically. Results show that anisotropic diffusion filtering is able to extract the edges in both normal and abnormal images. The obtained edge maps are found to have high contrast and sharp edges. The edge based variational level set method is able to segment the intima-media layer precisely from common carotid artery. The extracted geometrical features such as major axis and extent are found to be statistically significant in differentiating normal and abnormal images. Thus this study seems to be clinically useful in diagnosis of cardiovascular disease.

Implementation of three different segmentation techniques for quantitative evaluation of IMT in B-mode ultrasound common carotid artery images

This paper reports three techniques for automated intima–media thickness measurement in the B-mode common carotid artery ultrasound images. These are the gradient based (GB), localising region-based active contour (LAC) and level-set evolution without re-initialisation (LER). Authors have reported results with quantitative and qualitative comparisons. From results, it is observed that the performance of LER is superior in terms of accuracy and robustness in the presence of weak boundaries and strong noise. The correlation coefficients between automated measurements and manually obtained reference values were 0.63, 0.76 and 0.98 for GB, LAC and LER techniques, respectively (N = 66). The figure-of-merit of LER was 99.59%, better than GB (88.86%) and LAC (98.52%).

Abstract 271: Thrombospondin-1 Plays a Direct Role in Leptin-Induced Atherosclerosis

Hyperleptinemia, characteristic of diabetes and a hallmark feature of obesity, contributes to the increased risk of atherosclerotic complications. We recently reported that leptin has a direct regulatory effect on the expression of a potent proatherogenic and antiangiogenic matricellular protein thrombospondin-1 (TSP-1) in vitro and in vivo . While leptin and TSP-1 are independently linked to atherosclerosis, a potential cross-talk in vivo remains unknown. The present study is the first evidence that TSP-1 plays a direct role in leptin-induced atherosclerosis. Briefly ApoE -/- and TSP-1 -/- /ApoE -/- double knockout (dKO) mice at 17 wks of age, on regular chow diet, were injected i.p. with murine recombinant leptin (5μg/g body weight) or PBS (vehicle control) once daily for 3 wks and mice were sacrificed at 20 wks of age. Using en face atherosclerotic lesion assay shown by Oil red O staining, we demonstrated that while leptin in vivo significantly increased (2.5-fold) lesion area in the aortic walls of ApoE -/- mice, TSP-1 -/- /ApoE -/- dKO mice developed relatively fewer lesions in response to exogenous leptin. Using high-frequency ultrasound imaging we found that in ApoE -/- mice leptin significantly decreased diameter of transaortic arch, ascending and descending aorta (p &lt; 0.01), while TSP-1 -/- /ApoE -/- dKO mice were completely protected against this leptin-induced reduction in aortic vessel diameter. Ultrasound imaging of common carotid artery further revealed that leptin-treated TSP-1 -/- /ApoE -/- dKO mice were protected against development of vascular lesions while leptin-treated ApoE -/- mice showed more pronounced lesions and a significant reduction in carotid artery internal diameter (p ≤ 0.02). Finally, while leptin in vivo significantly increased plasma cholesterol (~40%) and triglyceride (2.5 fold) levels in ApoE -/- mice, this leptin-induced increase in plasma lipid levels was attenuated in TSP-1 -/- /ApoE -/- dKO mice. Together, our results suggest that knockout of TSP-1 protects ApoE -/- mice against leptin-induced atherosclerosis in vivo , underscoring a novel role of TSP-1 in hyperleptinemia-induced macrovascular complications.

Abstract 645: Atheroprotective Mechanism of Chromium Picolinate in Streptozotocin-Induced Diabetic ApoE-/- Mice

Vascular disease accounts for increased morbidity and mortality in diabetes. Given the burden of health care expenditure in diabetics, relatively cost-effective strategies represent an attractive therapeutic approach. Trivalent chromium (Cr) is a mineral nutrient reported to have a beneficial role in glycemic and cardiovascular health. While previous studies suggest that Cr reduces vascular inflammation in diabetes, the precise mechanisms of Cr action in the large blood vessels in diabetes remain unknown. We showed earlier that Cr picolinate (CrP, a bioavailable form of Cr) in vitro downregulates a potent proatherogenic matricellular protein thrombospondin-1 (TSP-1) in glucose-stimulated vascular smooth muscle cells. The present study provides the first evidence of an atheroprotective mechanism of Cr in vivo in a mouse model of diabetic atherosclerosis. Briefly, hyperglycemia was induced in male ApoE -/- mice (6wks age) with 50mg/Kg/day streptozotocin (STZ), i.p. for 5 consecutive days. Hyperglycemic mice (blood glucose&gt;250mg/dl) on regular chow diet were treated with or without CrP (8μg/Kg) in drinking water starting at 8 wks of age and all mice were sacrificed at 18 wks of age. Using en face atherosclerotic lesion assay shown by Oil red O staining, we demonstrated that CrP in vivo significantly prevents development of lesion in aortic vessel walls of hyperglycemic STZ-ApoE -/- mice compared to untreated STZ-ApoE -/- mice. Consistently, high-frequency ultrasound imaging of common carotid artery revealed that CrP prevents development of vascular lesions in STZ-ApoE -/- mice while untreated mice showed more pronounced lesions with a significant reduction (20%) in carotid artery diameter. Importantly, atheroprotective effects of CrP were accompanied by a significant decrease (&gt;35%) in TSP-1 and PCNA (proliferation marker) expression in aortic vessels of STZ-ApoE -/- mice, shown by immunoblotting. Also, en face studies showed that knockout of TSP-1 protects STZ-induced hyperglycemic ApoE -/- mice against atherosclerosis. Together, our results suggest that CrP in vivo prevents diabetic atherosclerosis via downregulation of TSP-1 in the large blood vessel wall, underscoring TSP-1 as a novel therapeutic target in diabetic atherosclerosis.