Atherosclerotic plaque characterization using plaque area variation in IVUS images during compression: a computational investigation

INTRODUCTION: The rupture of atherosclerotic plaques causes millions of death yearly. It is known that the kind of predominant tissue is associated with its dangerousness. In addition, the mechanical properties of plaques have been proved to be a good parameter to characterize the type of tissue, important information for therapeutic decisions. METHODS: Therefore, we present an alternative and simple way to discriminate tissues. The procedure relies on computing an index, the ratio of the plaque area variation of a suspecting plaque, using images acquired with vessel and plaques, pre and post-deformation, under different intraluminal pressure. Numerical phantoms of coronary cross-sections with different morphological aspects, and simulated with a range of properties, were used for evaluation. RESULTS: The outcomes provided by this index and a widely used one were compared, so as to measure their correspondence. As a result, correlations up to 99%, a strong agreement with Bland-Altman and very similar histograms between the two indices, have shown a good level of equivalence between the methods. CONCLUSION: The results demonstrated that the proposed index discriminates highly lipidic from fibro-lipidic and calcified tissues in many situations, as good as the widely used index, yet the proposed method is much simpler to be computed.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Universidade Federal de São Paulo (UNIFESP) Instituto de Ciência e Tecnologia Departamento de Ciência e TecnologiaUniversidade de São Paulo Escola Politécnica Departamento de Engenharia de Telecomunicações e ControleUNIFESP, Instituto de Ciência e Tecnologia Depto. de Ciência e TecnologiaSciEL

Estimation of elastic properties for tissue characterization based on ultrasound images.

Ultrassonografia (US) é usada por médicos para ajudar em diagnósticos e intervenções. Ela fornece uma visada tomográfica de órgãos internos como, por exemplo, pâncreas aorta, fígado, bexiga, rins e baço. O médico pode utilizar a US para realizar apenas uma avaliação visual ou pode também comprimir o tecido para analisar a dinâmica, uma vez que a elasticidade da lesão pode estar relacionada à patologias. Consequentemente, diversos procedimentos computacionais vem sendo desenvolvidos com o intuito de fornecer ao médico informações acerca das propriedades elásticas do tecido. Entretanto, uma avaliação completa e objetiva dos procedimentos computacionais sobre US pode ser dificultada pelo difícil acesso a imagens com as propriedades desejadas ou pela falta de padrão-ouro para ser utilizado como referência. Portanto, nós desenvolvemos uma ferramenta capaz de criar phantoms numérico que imitam a compressão induzida por um médico através de um transdutor. A deformação do tecido é baseada em método doe elementos finitos e o deslocamento dos espalhadores é calculado usando isomorfismo linear. Depois do deslocamento dos espalhadores, Field II foi utilizado para simular o ruído Speckle. Assim, foi possível a criação de uma sequência de imagens de US com deformação realística. Este método foi implementado em Matlab e está disponível para download sem custos. A deformação do phantom foi validada através da medição de contraste de compressão em phantoms de duas camadas. Uma atenção especial foi dada a doenças cardiovasculares devido ao impacto que essas patologias causam no cenário médico do Brasil e do mundo. Nas últimas décadas, a prevalência de patologias cardiovasculares têm crescido progressivamente e se tornou uma séria questão de saúde pública. Elas estão entre as maiores causas de mortes, internações e gastos com saúde. Na prática intervencionista, o ultrassom intravascular (IVUS) é utilizado para obter informações do vaso sanguíneo e de eventuais patologias. Portanto, foi desenvolvida também uma simulação numérica de phantoms de IVUS. A simulação do vaso sanguíneo também se baseou em método dos elementos finitos e isomorfismo linear. Contudo, uma simulação confiável de IVUS deve considerar o caminho do cateter no interior do vaso sanguíneo, porque isto determina a posição do transdutor. Portanto, nós desenvolvemos um novo método, baseado em equilíbrio de forças, para determinar a posição de menor energia do cateter. O método foi validado através da comparação da posição estimada com a posição de um fio-guia de aço real e apresentou erro quadrático médio e média Hausdorff menor que 1 mm para ambos. Foram utilizados dois métodos diferentes para rastrear e estimar a deformação de determinadas estruturas no tecido: Optical Flow e 2D Block Matching. Foi aplicado uma implementação inovadora de 2D Block Matching com interpolação sub-pixel linear e propagação de deslocamento. Posteriormente, a validação será feita comparando-se a o movimento estimado com o padrão-ouro numérico utilizado para construir a simulação. O 2D block matching forneceu resultados melhores que o optical flow. Após a análise em phantoms numéricos, equipamento real de ultrassom foi utilizado para aquisição de imagens modo-B de phantoms físicos. Então, nós realizamos a estimativa do movimento das estruturas para analisar as propriedades morfológicas e dinâmicas do tecidos. Os resultados obtidos foram comparados com a elastografia fornecida pelo equipamento. Em acordo com os resultados obtidos na simulação numérica, o 2D block matching novamente apresentou resultados melhores que o optical flow. Finalmente, os dois métodos de rastreamento foi aplicada em imagens simuladas de IVUS, que foram divididas em 2 conjuntos de quadros. O primeiro conjunto, S1, continha todos os quadros da sequência de IVUS e o segundo conjunto, S2, continha apenas os quadros correspondentes a uma fase específica do ciclo cardíaco. Sendo assim, foi analisado o balanço entre o impacto do movimento cardíaco e a taxa de quadros. Para os pontos localizados nas bordas dos objetos, Optical flow teve um bom desempenho para ambos S1 e S2. Em regiões homogêneas, entretanto, o optical flow foi capaz de rastrear os pontos em S2, sugerindo que é melhor o trabalho com movimento cardíaco reduzido em detrimento da taxa de quadros, tal qual a aquisição de IVUS engatilhado por ECG. Já o 2D block matching apresentou um mau rastreamento para todos os pontos selecionados. Além da simulação da aquisição de ultrassonografia com deformação e do rastreamento de estruturas, também desenvolvemos uma nova técnica de filtragem capaz de remover a textura speckle sem borrar as bordas. A técnica proposta apresentou os melhores resultados quando comparados com outros nove filtros da literatura. Foi desenvolvida também uma nova métrica que utiliza o ruído speckle da própria imagem para fornecer um parâmetro que pode ajudar o usuário a decidir o tamanho da janelo de um filtro.Ultrasonography (US) is used by physicians to help on diagnosis and interventions. It provides tomographic views of inner organs such as pancreas, aorta, inferior vena cava, liver, gall bladder, bile ducts, kidneys and spleen. The physician may utilize US to perform only a visual assessment or may also compress the tissue to analyze its dynamics, since lesion elasticity may be related to dangerousness. Consequently, several computational procedures have been developed in order to provide information about the elastic properties of the tissue. However, a thorough and objective evaluation of US computational procedures may be hindered by the difficult access to US images with the desired features and the lack of gold-standard parameters. Therefore, we developed a tool that is able to create numeric phantom that mimics the compression induced by physician with the transducer. The tissue deformation was based on finite elements method and the displacement of the scatterers were calculated using linear isomorphism. After the scatterer displacement, Field II was used to simulate the speckle noise. Thus, it is possible to create a sequence of US images with realistic deformation. This technique was implemented in Matlab and is available for free download. The phantom deformation was validated by measuring the strain contrast from double-layered phantoms. Special attention was given to cardiovascular diseases due to their impact on Brazilian and world populations. During the last decades, the prevalence of cardiovascular pathologies has increased progressively, and has become a serious public health problem. They are among the major causes of death, hospitalizations and health expenses. In interventionist practice, intravascular ultrasound (IVUS) is used to obtain information about blood vessels and eventual pathologies. Therefore, we also created numeric IVUS phantoms. The simulation of the blood vessel was also based in finite elements method with linear isomorphism. However, a reliable IVUS simulation must consider the catheter path inside the blood vessel, because it determines the position of the transducer. Hence, we developed a new method, based on equilibrium of forces, to determine the minimum energy position of the catheter. The method was validated by comparing its position with the position of a real stainless steel IVUS guidewire and presented root mean squared error and Hausdorff mean smaller than 1 mm for both. We used two different techniques to track and estimate deformation of different structures in the simulated US images, namely, Optical Flow and 2D Block Matching. We applied an innovative implementation of 2D block matching with sub-pixel linear interpolation and displacement propagation. Then, the estimated deformation from both methods were compared with the numeric gold-standard, and 2D block matching presented better results than optical flow. After the work with numeric phantoms, real US equipment was utilized to acquire B-mode images from a physical phantom. Then, we performed the movement estimation of the imaged tissue to analyze its morphological and dynamic properties. The results were compared to the elastography images provided by the US equipment. In accordance with the results from the numeric simulation, 2D block matching presented better results than Optical flow. Finally, we performed the two speckle tracking on a set of numerically simulated IVUS images, where the images were divided into two sets of frames. The first set, S1, contained all the frames from the IVUS sequence and the second set, S2, contained only the frames corresponding to a specific phase of the cardiac cycle. Thus, we analyzed the trade-off between the impact of the cardiac motion and low frame rate. For the points located at the edges of the object, optical flow had a good performance for both S1 and S2. In homogenous regions, however, optical flow was able to track the points only in S2, suggesting that it is better to work with low frame rate and reduced cardiac motion, as in EKG-triggered IVUS acquisition. 2D block matching presented poor results in all points of both S1 and S2. Besides the simulation of ultrasound acquisition with deformation and structure tracking, in this work, we also developed a new filtering technique that is able to remove the speckle texture without blurring the edges. The proposed filter presented the best results when compared to other nine filters from the literature. We also developed a metric that uses the speckle texture of the image to provide a parameter that may help the user decide the size of the window of the filter

Realistic deformable 3D numeric phantom for transcutaneous ultrasound

Abstract Introduction Numerical phantoms are important tools to design, calibrate and evaluate several methods in various image-processing applications, such as echocardiography and mammography. We present a framework for creating ultrasound numerical deformable phantoms based on Finite Element Method (FEM), Linear Isomorphism and Field II. The proposed method considers that the scatterers map is a property of the tissue; therefore, the scatterers should move according to the tissue strain. Methods First, a volume representing the target tissue is loaded. Second, parameter values, such as Young’s Modulus, scatterers density, attenuation and scattering amplitudes are inserted for each different regions of the phantom. Then, other parameters related to the ultrasound equipment, such as ultrasound frequency and number of transducer elements, are also defined in order to perform the ultrasound acquisition using Field II. Third, the size and position of the transducer and the pressures that are applied against the tissue are defined. Subsequently, FEM is executed and deformation is computed. Next, 3D linear isomorphism is performed to displace the scatterers according to the deformation. Finally, Field II is carried out to generate the non-deformed and deformed ultrasound data. Results The framework is evaluated by comparing strain values obtained the numerical simulation and from the physical phantom from CIRS. The mean difference between both phantoms is lesser than 10%. Conclusion The acoustic and deformation outcomes are similar to those obtained using a physical phantom. This framework led to a tool, which is available online and free of charges for educational and research purposes

EDGE-PRESERVING SPECKLE TEXTURE REMOVAL BY INTERFERENCE-BASED SPECKLE FILTERING FOLLOWED BY ANISOTROPIC DIFFUSION

Ultrasonography has an inherent noise pattern, called speckle, which is known to hamper object recognition for both humans and computers. Speckle noise is produced by the mutual interference of a set of scattered wavefronts. Depending on the phase of the wavefronts, the interference may be constructive or destructive, which results in brighter or darker pixels, respectively. We propose a filter that minimizes noise fluctuation while simultaneously preserving local gray level information. It is based on steps to attenuate the destructive and constructive interference present in ultrasound images. This filter, called interference-based speckle filter followed by anisotropic diffusion (ISFAD), was developed to remove speckle texture from B-mode ultrasound images, while preserving the edges and the gray level of the region. The ISFAD performance was compared with 10 other filters. The evaluation was based on their application to images simulated by Field II (developed by Jensen et al.) and the proposed filter presented the greatest structural similarity, 0.95. Functional improvement of the segmentation task was also measured, comparing rates of true positive, false positive and accuracy. Using three different segmentation techniques, ISFAD also presented the best accuracy rate (greater than 90% for structures with well-defined borders). (E-mail: [email protected]) (C) 2012 World Federation for Ultrasound in Medicine & Biology.Fapesp [09/12313-8, 07/53985-3]FAPES