94 research outputs found

    Morphometric and meristic study of Garra rufa populations in Tigris and Persian Gulf Basins

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    This study was conducted to determine morphometric and meristic characteristics of Garra rufa in 13 stations of Tigris and Persian Gulf basins. We caught 310 specimens during the year 2007-2008 using electro-shocker and sachok. Univariate analysis of variance (ANOVA) and principal component analysis were conducted and the ANOVA revealed significant differences in 28 morphometric and 9 meristic factors (P<0.05). Factor analysis showed that G. rufa of thirteen stations had 48.855% changes in 3 factors of the first morphometric characters (pectoral fin length, ventral fin length, depth of anal fin) and 71/611% changes in 3 factors of the first meristic characters (lateral line scales , circum peduncle scales, predorsal scales). Plotting the first and second principal component morphometric and meristic characters showed that the Mond River population was separated from the others but the other populations were overlapping with each other in the characteristics studied

    Bolus characteristics based on Magnetic Resonance Angiography

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    BACKGROUND: A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation. METHODS: MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design. RESULTS: The maximum speed of the bolus in the aorta ranged from 5–13 cm/s and the dwell time ranged from 7–13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location. CONCLUSION: The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design

    Secondary Endoleak Management Following TEVAR and EVAR.

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    Endovascular abdominal and thoracic aortic aneurysm repair and are widely used to treat increasingly complex aneurysms. Secondary endoleaks, defined as those detected more than 30 days after the procedure and after previous negative imaging, remain a challenge for aortic specialists, conferring a need for long-term surveillance and reintervention. Endoleaks are classified on the basis of their anatomic site and aetiology. Type 1 and type 2 endoleaks (EL1 and EL2) are the most common endoleaks necessitating intervention. The management of these requires an understanding of their mechanics, and the risk of sac enlargement and rupture due to increased sac pressure. Endovascular techniques are the main treatment approach to manage secondary endoleaks. However, surgery should be considered where endovascular treatments fail to arrest aneurysm growth. This chapter reviews the aetiology, significance, management strategy and techniques for different endoleak types
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