Semi-automatic detection and segmentation algorithm of saccular aneurysms in 2D cerebral DSA images

AbstractObjectiveTo detect and segment cerebral saccular aneurysms (CSAs) in 2D Digital Subtraction Angiography (DSA) images.Patients and methodsTen patients underwent Intra-arterial DSA procedures. Patients were injected with Iodine-containing radiopaque material. A scheme for semi-automatic detection and segmentation of intracranial aneurysms is proposed in this study. The algorithm consisted of three major image processing stages: image enhancement, image segmentation and image classification. Applied to the 2D Digital Subtraction Angiography (DSA) images, the algorithm was evaluated in 19 scene files to detect 10 CSAs.ResultsAneurysms were identified by the proposed detection and segmentation algorithm with 89.47% sensitivity and 80.95% positive predictive value (PPV) after executing the algorithm on 19 DSA images of 10 aneurysms. Results have been verified by specialized radiologists. However, 4 false positive aneurysms were detected when aneurysms’ location is at Anterior Communicating Artery (ACA).ConclusionThe suggested algorithm is a promising method for detection and segmentation of saccular aneurysms; it provides a diagnostic tool for CSAs

A framework for intracranial saccular aneurysm detection and quantification using morphological analysis of cerebral angiograms

Reliable early prediction of aneurysm rupture can greatly help neurosurgeons to treat aneurysms at the right time, thus saving lives as well as providing significant cost reduction. Most of the research efforts in this respect involve statistical analysis of collected data or simulation of hemodynamic factors to predict the risk of aneurysmal rupture. Whereas, morphological analysis of cerebral angiogram images for locating and estimating unruptured aneurysms is rarely considered. Since digital subtraction angiography (DSA) is regarded as a standard test by the American Stroke Association and American College of Radiology for identification of aneurysm, this paper aims to perform morphological analysis of DSA to accurately detect saccular aneurysms, precisely determine their sizes, and estimate the probability of their ruptures. The proposed diagnostic framework, intracranial saccular aneurysm detection and quantification, first extracts cerebrovascular structures by denoising angiogram images and delineates regions of interest (ROIs) by using watershed segmentation and distance transformation. Then, it identifies saccular aneurysms among segmented ROIs using multilayer perceptron neural network trained upon robust Haralick texture features, and finally quantifies aneurysm rupture by geometrical analysis of identified aneurysmic ROI. De-identified data set of 59 angiograms is used to evaluate the performance of algorithms for aneurysm detection and risk of rupture quantification. The proposed framework achieves high accuracy of 98% and 86% for aneurysm classification and quantification, respectively

The Role of Biofluid Mechanics in the Assessment of Clinical and Pathological Observations: Sixth International Bio-Fluid Mechanics Symposium and Workshop, March 28–30, 2008 Pasadena, California

Biofluid mechanics is increasingly applied in support of diagnosis and decision-making for treatment of clinical pathologies. Exploring the relationship between blood flow phenomena and pathophysiological observations is enhanced by continuing advances in the imaging modalities, measurement techniques, and capabilities of computational models. When combined with underlying physiological models, a powerful set of tools becomes available to address unmet clinical needs, predominantly in the direction of enhanced diagnosis, as well as assessment and prediction of treatment outcomes. This position paper presents an overview of current approaches and future developments along this theme that were discussed at the 5th International Biofluid Symposium and Workshop held at the California Institute of Technology in 2008. The introduction of novel mechanical biomarkers in device design and optimization, and applications in the characterization of more specific and focal conditions such as aneurysms, are at the center of attention. Further advances in integrative modeling, incorporating multiscale and multiphysics techniques are also discussed

Hemodynamic study in a real intracranial aneurysm: an in vitro and in silico approach

Mestrado de dupla diplomação com o Centro Federal de Educação Tecnológica Celso Suckow da Fonseca - Cefet/RJIntracranial aneurysm (IA) is a cerebrovascular disease with high rates of mortality and morbidity when it ruptures. It is known that changes in the intra-aneurysmal hemodynamic load play a significant factor in the development and rupture of IA. However, these factors are not fully understood. In this sense, the main objective of this work is to study the hemodynamic behavior during the blood analogues flow inside an AI and to determine its influence on the evolution of this pathology. To this end, experimental and numerical studies were carried out, using a real AI model obtained using computerized angiography. In the experimental approach, it was necessary, in the initial phase, to develop and manufacture biomodels from medical images of real aneurysms. Two techniques were used to manufacture the biomodels: rapid prototyping and gravity casting. The materials used to obtain the biomodels were of low cost. After manufacture, the biomodels were compared to each other for their transparency and final structure and proved to be suitable for testing flow visualizations. Numerical studies were performed with the aid of the Ansys Fluent software, using computational fluid dynamics (CFD), using the finite volume method. Subsequently, flow tests were performed experimentally and numerically using flow rates calculated from the velocity curve of a patient's doppler test. The experimental and numerical tests, in steady-state, made it possible to visualize the three-dimensional behavior of the flow inside the aneurysm, identifying the vortex zones created throughout the cardiac cycle. Correlating the results obtained in the two analyzes, it was possible to identify that the areas of vortexes are characterized by low speed and with increasing the fluid flow, the vortexes are positioned closer to the wall. These characteristics are associated with the rupture of an intracranial aneurysm. There was also a good qualitative correlation between numerical and experimental results.O aneurisma intracraniano (AI) é uma patologia cerebrovascular com altas taxas de mortalidade e morbidade quando se rompe. Sabe-se que alterações na carga hemodinâmica intra-aneurismática exerce um fator significativo no desenvolvimento e ruptura de AI, porém, esses fatores não estão totalmente compreendidos. Nesse sentido, o objetivo principal deste trabalho é o de estudar o comportamento hemodinâmico durante o escoamento de fluidos análogos do sangue no interior de um AI e determinar a sua influência na evolução da patologia. Para tal, foram realizados estudos experimentais e numéricos, utilizando um modelo de AI real obtido por meio de uma angiografia computadorizada. Na abordagem experimental foi necessário, na fase inicial, desenvolver e fabricar biomodelos a partir de imagens médicas de um aneurisma real. No fabrico dos biomodelos foram utilizadas duas técnicas: a prototipagem rápida e o vazamento por gravidade. Os materiais utilizados para a obtenção dos biomodelos foram de baixo custo. Após a fabricação, os biomodelos foram comparados entre si quanto à sua transparência e estrutura final e verificou-se serem adequados para testes de visualizações do fluxo. Os estudos numéricos foram realizados com recurso ao software Ansys Fluent, utilizando a dinâmica dos fluidos computacional (CFD), através do método dos volumes finitos. Posteriormente, foram realizados testes de escoamento experimentais e numéricos, utilizando caudais determinados a partir da curva de velocidades do ensaio doppler de um paciente. Os testes experimentais e numéricos, em regime permanente, possibilitaram a visualização do comportamento tridimensional do fluxo no interior do aneurisma, identificando as zonas de vórtices criadas ao longo do ciclo cardíaco. Correlacionando os resultados obtidos nas duas análises, foi possível identificar que as áreas de vórtices são caracterizadas por uma baixa velocidade e com o aumento do caudal os vórtices posicionam-se mais próximos da parede. Essas características apresentadas estão associadas com a ruptura de aneurisma intracraniano. Verificou-se, também, uma boa correlação qualitativa entre os resultados numéricos e experimentais

The role of shape for aneurysm risk assessment

Although the shape of intracranial aneurysms and the geometry of the surrounding vasculature are commonly taken into account by clinicians when assessing and treating aneurysms, it remains dif- ficult to quantify shape and develop clinical guidelines or tools that accommodate aneurysm shape. Here, we present new evidence that aneurysm shape is a meaningful proxy for disease status, the re- sults of a benchmark analysis comparing novel and established measurement methods for their ability to discriminate between ruptured and unruptured aneurysms, and how these findings can be trans- lated into clinics. We conclude with a plea for multi-centric data collections and present our own contributions to it

The Use of Artificial Intelligence in the Management of Intracranial Aneurysms

The use of artificial intelligence (AI) has potential benefits in the management of intracranial aneurysms. Early detection of intracranial aneurysms is critical due to their high risk of complications such as rupture, vasospasm, and ischemia with highly impact on morbidity and mortality. The main findings suggest that AI can improve the accuracy of aneurysm detection, rupture risk prediction, and assist neurointervention in planning and performing procedures. This chapter discusses the potential for AI to improve patient care by enabling earlier diagnosis and timely treatment, reducing medical errors, costs, morbidity, and mortality. However, further validation of AI-based applications is necessary in a real-world clinical setting

Nonlinear vibrations of an idealized saccular aneurysm

Intracranial saccular aneurysms are a small portion of a vessel that bulges outward forming a balloonlike sac. Approximately 3% of the worldwide population suffer from this pathology and its rupture entails subarachnoid haemorrhage, causing in most of the cases brain damage or even death. Many physical and clinical factors such as its location, geometry and growth, the surrounding fluids, other underlying condition, the sex or the age of the subject highly affect the evolution of aneurysms. However, although it is known that many parameters affect their development, the main criteria for deciding their treatment is their size. The main contribution of this work is the development of a 3D mathematical model to describe the behaviour of an idealized intracranial saccular aneurysm. An study of its mechanical behaviour is performed to understand under which conditions the aneurysm will break. The problem is divided into three main sections: the first one considers an aneurysm surrounded by a non-viscous Newtonian fluid and a constant internal pressure, the second one introduces the viscosity in the surrounding fluid and the last one introduces an internal pulsatile pressure. Additionally, this work analyzes how the variations of the internal pressure value, the thickness of the aneurysm and the density of both the surrounding fluid and aneurysm’s wall, affect the behaviour of the aneurysm.Ingeniería Biomédic

Hyperelasticity of Soft Tissues and Related Inverse Problems

International audienceIn this chapter, we are interested in the constitutive equations used to model macroscopically the mechanical function of soft tissues. After reviewing some basics about nonlinear finite–strain constitutive relations, we present recent developments of experimental biomechanics and inverse methods aimed at quantifying consti-tutive parameters of soft tissues. A focus is given to in vitro characterization of hyperelastic parameters based on full-field data that can be collected with digital image correlation systems during the experimental tests. The specific use of these data for membrane-like tissues is first illustrated through the example of bulge inflation tests carried out onto pieces of aortic aneurysms. Then an inverse method, based on the principle of virtual power, is introduced to estimate regional variations of material parameters for more general applications