Identifying patients at risk of developing premature coronary artery disease (PCAD) which occurs at age below 45 years old and constitutes approximately 7-10% of coronary artery disease (CAD) worldwide remains a problem. Oxidative stress has been proposed as a crucial step in the early development of PCAD. This study was conducted to determine the oxidative status of PCAD in comparison to CAD patients. PCAD (<45 years old) and CAD (>60 years old) patients were recruited with age-matched controls (n = 30, each group). DNA damage score, plasma malondialdehyde (MDA) and protein carbonyl content were measured for oxidative damage markers. Antioxidants such as erythrocyte glutathione (GSH), oxidised glutathione (GSSG), and glutathione peroxidase activity (GPx), superoxide dismutase (SOD) and catalase (CAT) were also determined. DNA damage score and protein carbonyl content were significantly higher in both PCAD and CAD when compared to age-matched controls while MDA level was increased only in PCAD (p<.05). In contrast, GSH, GSH/GSSG ratio, α-tocotrienol isomer, and GPx activity were significantly decreased, but only in PCAD when compared to age-matched controls. The decrease in GSH was associated with PCAD (OR = 0.569 95%CI [0.375 - 0.864], p = .008) and cut-off values of 6.69 μM with areas under the ROC curves (AUROC) 95%CI: 0.88 [0.80-0.96] (sensitivity of 83.3%; specificity of 80%). However, there were no significant differences in SOD and CAT activities in all groups. A higher level of oxidative stress indicated by elevated MDA levels and low levels of GSH, α-tocotrienol and GPx activity in patients below 45 years old may play a role in the development of PCAD and has potential as biomarkers for PCAD.
Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.
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