962 resultados para Abdominal aortic aneurysm, Epidemiology, temperature


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PURPOSE: To retrospectively evaluate the safety and effectiveness of the use of bivalirudin, a direct thrombin antagonist, compared with unfractionated heparin in endovascular aneurysm repair (EVAR). MATERIALS AND METHODS: Between March 1994 and September 2007, 740 consecutive patients (mean age, 75.7 y +/- 7.7; 69 women) underwent elective EVAR for infrarenal abdominal aortic aneurysm. Bivalirudin was used in 98 of these 740 (13.2%) and unfractioned heparin was used in the other 642 (86.8%). Complications were classified according to the Society of Vascular Surgery/International Society for Cardiovascular Surgery criteria. Major bleeding was defined as clinically overt blood loss resulting in a decrease of hemoglobin of more than 3 g/dL, any decrease in hemoglobin of more than 4 g/dL, transfusion of 2 U or more of red blood cells, or intracranial or retroperitoneal hemorrhage. RESULTS: Grade 1 major complications were observed in 161 of 642 patients (25.2%) in the heparin group and 12 of 98 patients (12.2%) in the bivalirudin group (P = .0046), whereas the incidences of grade 3 major complications were not significantly different between groups (P = .57). The rate of total complications was higher in the heparin group than in the bivalirudin group (247 of 642 [38.5%] vs 21 of 98 [21.4%]; P = .001). Major bleeding occurred in 10 of 98 patients (10.2%) receiving bivalirudin and in 91 of 642 patients (14.2%) receiving heparin (P = .34). One of 21 major complications (4.76%) in the bivalirudin group and 12 of 247 major complications (4.86%) in the heparin group were attributable to thrombosis (P = 1.0). CONCLUSIONS: Bivalirudin is a safe and feasible alternative to unfractionated heparin in patients undergoing EVAR.

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To analyze the detection of endoleaks with low-tube-voltage computed tomographic (CT) angiography.

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We present a case of a ruptured abdominal aortic aneurysm (AAA) with ambiguous accessory findings on post-mortem computed-tomography (PMCT), post-mortem magnetic resonance (PMMR) imaging, and PMCT-angiography (PMCTA) suggestive of thoracic aortic dissection. The diagnosis of ruptured AAA was confirmed by autopsy; however, there was no aortic dissection. The imaging findings that mimicked the presence of aortic dissection might have been an atypical presentation of post-mortem clotting or sedimentation. This case is an ideal example to illustrate benefits, limitations, and challenges of post-mortem cross-sectional imaging. It serves as a reminder that both, training as well as correlation of imaging findings with autopsy are fundamental to improve our understanding of radiologic findings on post-mortem cross-sectional imaging.

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AIMS In this work, we provide novel insight into the morphology of dissecting abdominal aortic aneurysms in angiotensin II-infused mice. We demonstrate why they exhibit a large variation in shape and, unlike their human counterparts, are located suprarenally rather than infrarenally. METHODS AND RESULTS We combined synchrotron-based, ultra-high resolution ex vivo imaging (phase contrast X-Ray tomographic microscopy) with in vivo imaging (high-frequency ultrasound and contrast-enhanced micro-CT) and image-guided histology. In all mice, we observed a tear in the tunica media of the abdominal aorta near the ostium of the celiac artery. Independently we found that, unlike the gradual luminal expansion typical for human aneurysms, the outer diameter increase of angiotensin II-induced dissecting aneurysms in mice was related to one or several intramural haematomas. These were caused by ruptures of the tunica media near the ostium of small suprarenal side branches, which had never been detected by the established small animal imaging techniques. The tear near the celiac artery led to apparent luminal dilatation, while the intramural haematoma led to a dissection of the tunica adventitia on the left suprarenal side of the aorta. The number of ruptured branches was higher in those aneurysms that extended into the thoracic aorta, which explained the observed variability in aneurysm shape. CONCLUSION Our results are the first to describe apparent luminal dilatation, suprarenal branch ruptures, and intramural haematoma formation in dissecting abdominal aortic aneurysms in mice. Moreover, we validate and demonstrate the vast potential of phase contrast X-ray tomographic microscopy in cardiovascular small animal applications.

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INTRODUCTION Since the initial publication in 2000, Angiotensin II-infused mice have become one of the most popular models to study abdominal aortic aneurysm in a pre-clinical setting. We recently used phase contrast X-ray based computed tomography to demonstrate that these animals develop an apparent luminal dilatation and an intramural hematoma, both related to mural ruptures in the tunica media in the vicinity of suprarenal side branches. AIMS The aim of this narrative review was to provide an extensive overview of small animal applicable techniques that have provided relevant insight into the pathogenesis and morphology of dissecting AAA in mice, and to relate findings from these techniques to each other and to our recent PCXTM-based results. Combining insights from recent and consolidated publications we aimed to enhance our understanding of dissecting AAA morphology and anatomy. RESULTS AND CONCLUSION We analyzed in vivo and ex vivo images of aortas obtained from macroscopic anatomy, histology, high-frequency ultrasound, contrast-enhanced micro-CT, micro-MRI and PCXTM. We demonstrate how in almost all publications the aorta has been subdivided into a part in which an intact lumen lies adjacent to a remodeled wall/hematoma, and a part in which elastic lamellae are ruptured and the lumen appears to be dilated. We show how the novel paradigm fits within the existing one, and how 3D images can explain and connect previously published 2D structures. We conclude that PCXTM-based findings are in line with previous results, and all evidence points towards the fact that dissecting AAAs in Angiotensin II-infused mice are actually caused by ruptures of the tunica media in the immediate vicinity of small side branches.

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A semi-automatic segmentation algorithm for abdominal aortic aneurysms (AAA), and based on Active Shape Models (ASM) and texture models, is presented in this work. The texture information is provided by a set of four 3D magnetic resonance (MR) images, composed of axial slices of the abdomen, where lumen, wall and intraluminal thrombus (ILT) are visible. Due to the reduced number of images in the MRI training set, an ASM and a custom texture model based on border intensity statistics are constructed. For the same reason the shape is characterized from 35-computed tomography angiography (CTA) images set so the shape variations are better represented. For the evaluation, leave-one-out experiments have been held over the four MRI set.

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Acknowledgements This study received no specific funding. The study involved the analysis of data collected routinely as part of the national AAA screening programme in Scotland.

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Objective: To determine the long term relative survival of all patients who had surgery for abdominal aortic aneurysm in Western Australia during 1985-94.

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Abdominal Aortic Aneurism is a disease related to a weakening in the aortic wall that can cause a break in the aorta and the death. The detection of an unusual dilatation of a section of the aorta is an indicative of this disease. However, it is difficult to diagnose because it is necessary image diagnosis using computed tomography or magnetic resonance. An automatic diagnosis system would allow to analyze abdominal magnetic resonance images and to warn doctors if any anomaly is detected. We focus our research in magnetic resonance images because of the absence of ionizing radiation. Although there are proposals to identify this disease in magnetic resonance images, they need an intervention from clinicians to be precise and some of them are computationally hard. In this paper we develop a novel approach to analyze magnetic resonance abdominal images and detect the lumen and the aortic wall. The method combines different algorithms in two stages to improve the detection and the segmentation so it can be applied to similar problems with other type of images or structures. In a first stage, we use a spatial fuzzy C-means algorithm with morphological image analysis to detect and segment the lumen; and subsequently, in a second stage, we apply a graph cut algorithm to segment the aortic wall. The obtained results in the analyzed images are pretty successful obtaining an average of 79% of overlapping between the automatic segmentation provided by our method and the aortic wall identified by a medical specialist. The main impact of the proposed method is that it works in a completely automatic way with a low computational cost, which is of great significance for any expert and intelligent system.

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