A Combined FEM/Genetic Algorithm for Vascular Soft tissue Elasticity Estimation

Tissue elasticity reconstruction is a parameter estimation effort combining imaging, elastography, and computational modeling to build maps of soft tissue mechanical properties. One application is in the characterization of atherosclerotic plaques in diseased arteries, wherein the distribution of elastic properties is required for stress analysis and plaque stability assessment. In this paper, a computational scheme is proposed for elasticity reconstruction in soft tissues, combining finite element modeling (FEM) for mechanical analysis of soft tissues and a genetic algorithm (GA) for parameter estimation. With a model reduction of the discrete elasticity values into lumped material regions, namely the plaque constituents, a robust, adaptive strategy can be used to solve inverse elasticity problems involving complex and inhomogeneous solution spaces. An advantage of utilizing a GA is its insistence on global convergence. The algorithm is easily implemented and adaptable to more complex material models and geometries. It is meant to provide either accurate initial guesses of low-resolution elasticity values in a multi-resolution scheme or as a replacement for failing traditional elasticity estimation efforts.

[1]  B. Garra,et al.  Elastography: Ultrasonic imaging of tissue strain and elastic modulus in vivo , 1996 .

[2]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[3]  J D Humphrey,et al.  Mechanics of the arterial wall: review and directions. , 1995, Critical reviews in biomedical engineering.

[4]  I Céspedes,et al.  Fundamental mechanical limitations on the visualization of elasticity contrast in elastography. , 1995, Ultrasound in medicine & biology.

[5]  Faouzi Kallel,et al.  Tissue elasticity reconstruction using linear perturbation method , 1996, IEEE Trans. Medical Imaging.

[6]  M. Doyley,et al.  Evaluation of an iterative reconstruction method for quantitative elastography , 2000 .

[7]  R D Kamm,et al.  Mechanical properties of model atherosclerotic lesion lipid pools. , 1994, Arteriosclerosis and thrombosis : a journal of vascular biology.

[8]  A.R. Skovoroda,et al.  Tissue elasticity reconstruction based on ultrasonic displacement and strain images , 1995, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[9]  A. Sarvazyan.  Shear acoustic properties of soft biological tissues in medical diagnostics , 1993 .

[10]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[11]  H S Borovetz,et al.  Identification of elastic properties of homogeneous, orthotropic vascular segments in distension. , 1995, Journal of biomechanics.

[12]  T K Foo,et al.  Techniques for high‐resolution MR imaging of atherosclerotic plaque , 1994, Journal of magnetic resonance imaging : JMRI.

[13]  N Bom,et al.  Characterization of plaque components and vulnerability with intravascular ultrasound elastography. , 2000, Physics in medicine and biology.

[14]  M. R. Kaazempur-Mofrad,et al.  Cyclic strain in human carotid bifurcation and its potential correlation to atherogenesis: Idealized and anatomically-realistic models , 2003 .

[15]  V. Mow,et al.  Biphasic creep and stress relaxation of articular cartilage in compression? Theory and experiments. , 1980, Journal of biomechanical engineering.

[16]  van Dh Dick Campen,et al.  A mixture approach to the mechanics of skin. , 1987, Journal of biomechanics.

[17]  G. V. R. Born,et al.  INFLUENCE OF PLAQUE CONFIGURATION AND STRESS DISTRIBUTION ON FISSURING OF CORONARY ATHEROSCLEROTIC PLAQUES , 1989, The Lancet.

[18]  R. Kamm,et al.  Distribution of Circumferential Stress in Ruptured and Stable Atherosclerotic Lesions A Structural Analysis With Histopathological Correlation , 1993, Circulation.

[19]  Elisabeth Brusseau,et al.  On the potential of the Lagrangian speckle model estimator to characterize atherosclerotic plaques in endovascular elastography: in vitro experiments using an excised human carotid artery. , 2005, Ultrasound in medicine & biology.

[20]  A. McCulloch,et al.  Modelling cardiac mechanical properties in three dimensions , 2001, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[21]  N Iftimia,et al.  OCT-based arterial elastography: robust estimation exploiting tissue biomechanics. , 2004, Optics express.

[22]  Michel Dauzat,et al.  Consensus Concerning the Morphology and the Risk of Carotid Plaques , 1997 .

[23]  Brett E. Bouma,et al.  Mechanical Analysis of Atherosclerotic Plaques Based on Optical Coherence Tomography , 2004, Annals of Biomedical Engineering.

[24]  E. Halpern,et al.  Characterization of Human Atherosclerosis by Optical Coherence Tomography , 2002, Circulation.

[25]  Frits Mastik,et al.  A finite element model for performing intravascular ultrasound elastography of human atherosclerotic coronary arteries. , 2004, Ultrasound in medicine & biology.

[26]  Ho,et al.  Molecular geometry optimization with a genetic algorithm. , 1995, Physical review letters.

[27]  J. Ophir,et al.  Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues , 1991, Ultrasonic imaging.

[28]  Abbas Samani,et al.  Measuring the elastic modulus of ex vivo small tissue samples. , 2003, Physics in medicine and biology.

[29]  Francis A. Duck,et al.  Physical properties of tissue : a comprehensive reference book , 1990 .

[30]  Brett E. Bouma,et al.  Tissue Elasticity Estimation with Optical Coherence Elastography: Toward Mechanical Characterization of In Vivo Soft Tissue , 2005, Annals of Biomedical Engineering.