Prevention of ischemic complications during aneurysm surgery

Ischemic complications during aneurysm surgery are a frequent cause of postoperative infarctions and new neurological deficits. In this article, we discuss imaging and neurophysiological tools that may help the surgeon to detect intraoperative ischemia. The strength of intraoperative digital subtraction angiography (DSA) is the full view of the arterial and venous vessel. DSA is the gold standard in complex and giant aneurysms, but due to certain disadvantages, it cannot be considered standard of care. Microvascular Doppler sonography is probably the fastest diagnostic tool and can quickly aid diagnosis of large vessel occlusions. Intraoperative indocyanine green videoangiography is the best tool to assess flow in perforating and larger arteries, as well as occlusion of the aneurysm sac. Intraoperative neurophysiological monitoring with somatosensory and motor evoked potentials indirectly measures blood flow by recording neuronal function. It covers all causes of intraoperative ischemia, provided that ischemia occurs in the brain areas under surveillance. However, every method has advantages and disadvantages. No single method is superior to the others in every aspect. Therefore, it is very important for the neurosurgeon to know the strengths and weaknesses of each tool in order to have them available, to know how to use them for each individual situation, and to be ready to apply them within the time window for reversible cerebral ischemia.

The unruptured intracranial aneurysm treatment score: a multidisciplinary consensus.

OBJECTIVE We endeavored to develop an unruptured intracranial aneurysm (UIA) treatment score (UIATS) model that includes and quantifies key factors involved in clinical decision-making in the management of UIAs and to assess agreement for this model among specialists in UIA management and research. METHODS An international multidisciplinary (neurosurgery, neuroradiology, neurology, clinical epidemiology) group of 69 specialists was convened to develop and validate the UIATS model using a Delphi consensus. For internal (39 panel members involved in identification of relevant features) and external validation (30 independent external reviewers), 30 selected UIA cases were used to analyze agreement with UIATS management recommendations based on a 5-point Likert scale (5 indicating strong agreement). Interrater agreement (IRA) was assessed with standardized coefficients of dispersion (vr*) (vr* = 0 indicating excellent agreement and vr* = 1 indicating poor agreement). RESULTS The UIATS accounts for 29 key factors in UIA management. Agreement with UIATS (mean Likert scores) was 4.2 (95% confidence interval [CI] 4.1-4.3) per reviewer for both reviewer cohorts; agreement per case was 4.3 (95% CI 4.1-4.4) for panel members and 4.5 (95% CI 4.3-4.6) for external reviewers (p = 0.017). Mean Likert scores were 4.2 (95% CI 4.1-4.3) for interventional reviewers (n = 56) and 4.1 (95% CI 3.9-4.4) for noninterventional reviewers (n = 12) (p = 0.290). Overall IRA (vr*) for both cohorts was 0.026 (95% CI 0.019-0.033). CONCLUSIONS This novel UIA decision guidance study captures an excellent consensus among highly informed individuals on UIA management, irrespective of their underlying specialty. Clinicians can use the UIATS as a comprehensive mechanism for indicating how a large group of specialists might manage an individual patient with a UIA.

Automatic segmentation of abdominal aortic aneurysm from medical images based on active shape models and texture models

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.

Quantitative evaluation of patient-specific conforming hexahedral meshes of abdominal aortic aneurysms and intraluminal thrombus generated from MRI

A novel method for generating patient-specific high quality conforming hexahedral meshes is presented. The meshes are directly obtained from the segmentation of patient magnetic resonance (MR) images of abdominal aortic aneu-rysms (AAA). The MRI permits distinguishing between struc-tures of interest in soft tissue. Being so, the contours of the lumen, the aortic wall and the intraluminal thrombus (ILT) are available and thus the meshes represent the actual anato-my of the patient?s aneurysm, including the layered morpholo-gies of these structures. Most AAAs are located in the lower part of the aorta and the upper section of the iliac arteries, where the inherent tortuosity of the anatomy and the presence of the ILT makes the generation of high-quality elements at the bifurcation is a challenging task. In this work we propose a novel approach for building quadrilateral meshes for each surface of the sectioned geometry, and generating conforming hexahedral meshes by combining the quadrilateral meshes. Conforming hexahedral meshes are created for the wall and the ILT. The resulting elements are evaluated on four patients? datasets using the Scaled Jacobian metric. Hexahedral meshes of 25,000 elements with 94.8% of elements well-suited for FE analysis are generated.

Generación de modelos físicos personalizados y segmentación de la pared arterial y el trombo intraluminal en imágenes de aneurismas aórticos abdominales

Esta tesis doctoral está encuadrada dentro del marco general de la ingeniería biomédica aplicada al tratamiento de las enfermedades cardiovasculares, enfermedades que provocan alrededor de 1.9 millones (40%) de muertes al año en la Unión Europea. En este contexto surge el proyecto europeo SCATh-Smart Catheterization, cuyo objetivo principal es mejorar los procedimientos de cateterismo aórtico introduciendo nuevas tecnologías de planificación y navegación quirúrgica y minimizando el uso de fluoroscopía. En particular, esta tesis aborda el modelado y diagnóstico de aneurismas aórticos abdominales (AAA) y del trombo intraluminal (TIL), allí donde esté presente, así como la segmentación de estas estructuras en imágenes preoperatorias de RM. Los modelos físicos específicos del paciente, construidos a partir de imágenes médicas preoperatorias, tienen múltiples usos, que van desde la evaluación preoperatoria de estructuras anatómicas a la planificación quirúrgica para el guiado de catéteres. En el diagnóstico y tratamiento de AAA, los modelos físicos son útiles a la hora de evaluar diversas variables biomecánicas y fisiológicas de las estructuras vasculares. Existen múltiples técnicas que requieren de la generación de modelos físicos que representen la anatomía vascular. Una de las principales aplicaciones de los modelos físicos es el análisis de elementos finitos (FE). Las simulaciones de FE para AAA pueden ser específicas para el paciente y permiten modelar estados de estrés complejos, incluyendo los efectos provocados por el TIL. La aplicación de métodos numéricos de análisis tiene como requisito previo la generación de una malla computacional que representa la geometría de interés mediante un conjunto de elementos poliédricos, siendo los hexaédricos los que presentan mejores resultados. En las estructuras vasculares, generar mallas hexaédricas es un proceso especialmente exigente debido a la compleja anatomía 3D ramificada. La mayoría de los AAA se encuentran situados en la bifurcación de la arteria aorta en las arterias iliacas y es necesario modelar de manera fiel dicha bifurcación. En el caso de que la sangre se estanque en el aneurisma provocando un TIL, éste forma una estructura adyacente a la pared aórtica. De este modo, el contorno externo del TIL es el mismo que el contorno interno de la pared, por lo que las mallas resultantes deben reflejar esta particularidad, lo que se denomina como "mallas conformadas". El fin último de este trabajo es modelar las estructuras vasculares de modo que proporcionen nuevas herramientas para un mejor diagnóstico clínico, facilitando medidas de riesgo de rotura de la arteria, presión sistólica o diastólica, etc. Por tanto, el primer objetivo de esta tesis es diseñar un método novedoso y robusto para generar mallas hexaédricas tanto de la pared aórtica como del trombo. Para la identificación de estas estructuras se utilizan imágenes de resonancia magnética (RM). Deben mantenerse sus propiedades de adyacencia utilizando elementos de alta calidad, prestando especial atención al modelado de la bifurcación y a que sean adecuadas para el análisis de FE. El método tiene en cuenta la evolución de la línea central del vaso en el espacio tridimensional y genera la malla directamente a partir de las imágenes segmentadas, sin necesidad de reconstruir superficies triangulares. Con el fin de reducir la intervención del usuario en el proceso de generación de las mallas, es también objetivo de esta tesis desarrollar un método de segmentación semiautomática de las distintas estructuras de interés. Las principales contribuciones de esta tesis doctoral son: 1. El diseño, implementación y evaluación de un algoritmo de generación de mallas hexaédricas conformadas de la pared y el TIL a partir de los contornos segmentados en imágenes de RM. Se ha llevado a cabo una evaluación de calidad que determine su aplicabilidad a métodos de FE. Los resultados demuestran que el algoritmo desarrollado genera mallas conformadas de alta calidad incluso en la región de la bifurcación, que son adecuadas para su uso en métodos de análisis de FE. 2. El diseño, implementación y evaluación de un método de segmentación automático de las estructuras de interés. La luz arterial se segmenta de manera semiautomática utilizando un software disponible a partir de imágenes de RM con contraste. Los resultados de este proceso sirven de inicialización para la segmentación automática de las caras interna y externa de la pared aórtica utilizando métodos basado en modelos de textura y forma a partir de imágenes de RM sin contraste. Los resultados demuestran que el algoritmo desarrollado proporciona segmentaciones fieles de las distintas estructuras de interés. En conclusión, el trabajo realizado en esta tesis doctoral corrobora las hipótesis de investigación postuladas, y pretende servir como aportación para futuros avances en la generación de modelos físicos de geometrías biológicas. ABSTRACT The frame of this PhD Thesis is the biomedical engineering applied to the treatment of cardiovascular diseases, which cause around 1.9 million deaths per year in the European Union and suppose about 40% of deaths per year. In this context appears the European project SCATh-Smart Catheterization. The main objective of this project is creating a platform which improves the navigation of catheters in aortic catheterization minimizing the use of fluoroscopy. In the framework of this project, the specific field of this PhD Thesis is the diagnosis and modeling of abdominal aortic aneurysm (AAAs) and the intraluminal thrombus (ILT) whenever it is present. Patient-specific physical models built from preoperative imaging are becoming increasingly important in the area of minimally invasive surgery. These models can be employed for different purposes, such as the preoperatory evaluation of anatomic structures or the surgical planning for catheter guidance. In the specific case of AAA diagnosis and treatment, physical models are especially useful for evaluating pressures over vascular structures. There are multiple techniques that require the generation of physical models which represent the target anatomy. Finite element (FE) analysis is one the principal applications for physical models. FE simulations for AAA may be patient-specific and allow modeling biomechanical and physiological variables including those produced by ILT, and also the segmentation of those anatomical structures in preoperative MR images. Applying numeric methods requires the generation of a proper computational mesh. These meshes represent the patient anatomy using a set of polyhedral elements, with hexahedral elements providing better results. In the specific case of vascular structures, generating hexahedral meshes is a challenging task due to the complex 3D branching anatomy. Each patient’s aneurysm is unique, characterized by its location and shape, and must be accurately represented for subsequent analyses to be meaningful. Most AAAs are located in the region where the aorta bifurcates into the iliac arteries and it is necessary to model this bifurcation precisely and reliably. If blood stagnates in the aneurysm and forms an ILT, it exists as a conforming structure with the aortic wall, i.e. the ILT’s outer contour is the same as the wall’s inner contour. Therefore, resulting meshes must also be conforming. The main objective of this PhD Thesis is designing a novel and robust method for generating conforming hexahedral meshes for the aortic wall and the thrombus. These meshes are built using largely high-quality elements, especially at the bifurcation, that are suitable for FE analysis of tissue stresses. The method accounts for the evolution of the vessel’s centerline which may develop outside a single plane, and generates the mesh directly from segmented images without the requirement to reconstruct triangular surfaces. In order to reduce the user intervention in the mesh generation process is also a goal of this PhD. Thesis to develop a semiautomatic segmentation method for the structures of interest. The segmentation is performed from magnetic resonance image (MRI) sequences that have tuned to provide high contrast for the arterial tissue against the surrounding soft tissue, so that we determine the required information reliably. The main contributions of this PhD Thesis are: 1. The design, implementation and evaluation of an algorithm for generating hexahedral conforming meshes of the arterial wall and the ILT from the segmented contours. A quality inspection has been applied to the meshes in order to determine their suitability for FE methods. Results show that the developed algorithm generates high quality conforming hexahedral meshes even at the bifurcation region. Thus, these meshes are suitable for FE analysis. 2. The design, implementation and evaluation of a semiautomatic segmentation method for the structures of interest. The lumen is segmented in a semiautomatic way from contrast filled MRI using an available software. The results obtained from this process are used to initialize the automatic segmentation of the internal and external faces of the aortic wall. These segmentations are performed by methods based on texture and shape models from MRI with no contrast. The results show that the algorithm provides faithful segmentations of the structures of interest requiring minimal user intervention. In conclusion, the work undertaken in this PhD. Thesis verifies the investigation hypotheses. It intends to serve as basis for future physical model generation of proper biological anatomies used by numerical methods.

High-quality conforming hexahedral meshes of patient-specific abdominal aortic aneurysms including their intraluminal thrombi

In order to perform finite element (FE) analyses of patient-specific abdominal aortic aneurysms, geometries derived from medical images must be meshed with suitable elements. We propose a semi-automatic method for generating conforming hexahedral meshes directly from contours segmented from medical images. Magnetic resonance images are generated using a protocol developed to give the abdominal aorta high contrast against the surrounding soft tissue. These data allow us to distinguish between the different structures of interest. We build novel quadrilateral meshes for each surface of the sectioned geometry and generate conforming hexahedral meshes by combining the quadrilateral meshes. The three-layered morphology of both the arterial wall and thrombus is incorporated using parameters determined from experiments. We demonstrate the quality of our patient-specific meshes using the element Scaled Jacobian. The method efficiently generates high-quality elements suitable for FE analysis, even in the bifurcation region of the aorta into the iliac arteries. For example, hexahedral meshes of up to 125,000 elements are generated in less than 130 s, with 94.8 % of elements well suited for FE analysis. We provide novel input for simulations by independently meshing both the arterial wall and intraluminal thrombus of the aneurysm, and their respective layered morphologies.

Pathogenetic sequence for aneurysm revealed in mice underexpressing fibrillin-1

Dissecting aortic aneurysm is the hallmark of Marfan syndrome (MFS) and the result of mutations in fibrillin-1, the major constituent of elastin-associated extracellular microfibrils. It is yet to be established whether dysfunction of fibrillin-1 perturbs the ability of the elastic vessel wall to sustain hemodynamic stress by disrupting microfibrillar assembly, by impairing the homeostasis of established elastic fibers, or by a combination of both mechanisms. The pathogenic sequence responsible for the mechanical collapse of the elastic lamellae in the aortic wall is also unknown. Targeted mutation of the mouse fibrillin-1 gene has recently suggested that deficiency of fibrillin-1 reduces tissue homeostasis rather than elastic fiber formation. Here we describe another gene-targeting mutation, mgR, which shows that underexpression of fibrillin-1 similarly leads to MFS-like manifestations. Histopathological analysis of mgR/mgR specimens implicates medial calcification, the inflammatory–fibroproliferative response, and inflammation-mediated elastolysis in the natural history of dissecting aneurysm. More generally, the phenotypic severity associated with various combinations of normal and mutant fibrillin-1 alleles suggests a threshold phenomenon for the functional collapse of the vessel wall that is based on the level and the integrity of microfibrils.

Influence of rurality, deprivation and distance from clinic on uptake in men invited for abdominal aortic aneurysm screening

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.

Long term relative survival after surgery for abdominal aortic aneurysm in Western Australia: population based study

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

Automatic Abdominal Aortic Aneurysm segmentation in MR images

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.

Heart disease and thoracic aneurysm /

Mode of access: Internet.

Tracheal Compression Caused by Aortic Aneurysm

Carbon dust drawing on stipple board; Dr. Cameron Haight, University of Michigan Department of Thoracic Surgery

Combined arteriovenous fistula and venous aneurysm following knee arthrodesis

We study a case of a 65-year-old woman who developed popliteal arteriovenous fistula (AVF) and venous aneurysm following left knee arthrodesis. Presenting features included left popliteal and calf pain, a tender pulsatile mass posterior to her left knee, popliteal bruit and a thrill at the popliteal fossa and ankle. Left femoral angiography showed an AVF arising from the right tibioperoneal trunk and an aneurysm at the level of the AVF. Findings at open investigation included AVF between the tibioperoneal trunk and the popliteal vein, and a venous aneurysm arising from the popliteal vein opposite the neck of the arteriovenous communication. The aneurysm and fistula were repaired using prolene suture.