Desenvolvimento de algoritmo de imagens absolutas de tomografia por impedância elétrica para uso clínico.

Abstract

Electrical Impedance Tomography is a non invasive imaging technique that can be used in clinical applications to infer living tissue impeditivity from boundary electrical measurements. Mathematically this is an non-linear ill-posed inverse problem. Usually a spatial high-pass Gaussian filter is used as a regularization method for solving the inverse problem. The main objective of this work is to propose the use of physiological and anatomical priors of tissue resistivity distribution within the thorax, also known as anatomical atlas, in conjunction with the Gaussian filter as regularization methods. The proposed methodology employs the finite element method and the Gauss-Newton algorithm in order to reconstruct three-dimensional resistivity images. The Approximation Error Theory is used to reduce discretization effects and mesh size errors. Electrical impedance tomography data and computed tomography images of physiological pulmonary changes collected in vivo in a swine were used to validate the proposed method. The images obtained are compatible with atelectasis, pneumothorax, pleural effusion and different ventilation pressures during mechanical ventilation. The results show that image reconstruction from swines with clinically significant information is feasible when both the Gaussian filter and the anatomical atlas are used as regularization methods.vi

A review of electrical impedance tomography in lung applications: Theory and algorithms for absolute images

“…Another possibility is the use of statistical priors [23,28] to build the regularization term of the problem. For thorax applications an anatomical and physiological atlas can be computed using segmented tomographic images and measured resistivities of the thorax tissues.…”

“…A review of EIT lung applications is timely since there is a profusion of theoretical and technological advances that are increasing the spatial resolution and the accuracy of the estimated electrical material properties [16,17,18,19,20,21,22,23,24,25,26,27]. Examples of these include the parallelization of the forward problem [17], the use of algorithms that do not require derivatives of the performance index [18,19], the regularizations based on anatomy and physiology [23,28], and the correction of the inversion problem caused by a reduced or simplified model [22]. Furthermore, an increase in image quality is likely to expand the set of medical applications.…”

Sistema de triagem de pericárdio bovino para manufatura de válvulas cardíacas por tomografia de impedância elétrica.

“…Neste caso, um modelo melhorado é o chamado Gap model que leva em consideração a existência de eletrodos na fronteira [27].…”

“…Vale ressaltar que v depende de ρ, logo deve-se encontrar uma distribuição de resistividade que seja pró-xima dos valores que são esperados, por exemplo como foi feito em Camargo [27] através do atlas anatômico [30].…”

“…Camargo [27] mostrou-se que, para a obtenção de imagens absolutas de TIE de tórax, a inclusão de informação a priori melhora significativamente a qualidade da imagem.…”