Abstract
Diffusion anisotropy is the most fundamental and important parameter in the description of cardiac fibers using diffusion tensor magnetic resonance imaging (DTI), by reflecting the microstructure variation of the fiber. It is, however still not clear how the diffusion anisotropy is influenced by different contiguous structures (collagen, cardiac myocyte, etc.). In this paper, a virtual cardiac fiber structure is modeled, and diffusion weighted imaging (DWI) and DTI are simulated by the Monte Carlo method at various scales. The influences of the water content ratio in the cytoplasm and the extracellular space and the membrane permeability upon diffusion anisotropy are investigated. The simulation results show that the diffusion anisotropy increases with the increase of the ratio of water content between the intracellular cytoplasm and the extracellular medium. We show also that the anisotropy decreases with the increase of myocyte membrane permeability.
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Le Bihan, D.: Looking into the functional architecture of the brain with diffusion MRI. International Congress Series. Elsevier, Amsterdam (2006)
Kingsley, P.B.: Introduction to diffusion tensor imaging mathematics: Part I. Tensors, rotations, and eigenvectors. Concepts in Magnetic Resonance Part A 28, 101–122 (2006)
Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R.: Apparent diffusion coefficients from high angular resolution diffusion imaging: Estimation and applications. Magnet. Reson. Med. 56, 395–410 (2006)
Özarslan, E., Koay, C.G., Basser, P.J.: Remarks on q-space MR propagator in partially restricted, axially-symmetric, and isotropic environments. Magnetic Resonance Imaging 27, 834–844 (2009)
Tuch, D.S.: Q-ball imaging. Magnet. Reson. Med. 52, 1358–1372 (2004)
Le Bihan, D., Poupon, C., Amadon, A., Lethimonnier, F.: Artifacts and pitfalls in diffusion MRI. Journal of Magnetic Resonance Imaging 24, 478–488 (2006)
Assaf, Y., Freidlin, R.Z., Rohde, G.K., Basser, P.J.: New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter. Magnetic Resonance in Medicine 52, 965–978 (2004)
Severs, N.J.: The cardiac muscle cell. Bioessays 22, 188–199 (2000)
Duh, A., Mohori, A., Stepinik, J.: Computer simulation of the spin-echo spatial distribution in the case of restricted self-diffusion. Journal of Magnetic Resonance 148, 257–266 (2001)
Cai, C., Chen, Z., Cai, S., Zhong, J.: Propagator formalism and computer simulation of restricted diffusion behaviors of inter-molecular multiple-quantum coherences. Physica B: Condensed Matter 366, 127–137 (2005)
Fieremans, E., De Deene, Y., Delputte, S., Özdemir, M.S., D’Asseler, Y., Vlassenbroeck, J., et al.: Simulation and experimental verification of the diffusion in an anisotropic fiber phantom. Journal of Magnetic Resonance 190, 189–199 (2008)
Avram, L., Özarslan, E., Assaf, Y., Bar-Shir, A., Cohen, Y., Basser, P.J.: Three-dimensional water diffusion in impermeable cylindrical tubes: theory versus experiments. NMR in Biomedicine 2, 888–898 (2008)
Heidi, J.B., Timothy, E.J.B.: Diffusion MRI, 1st edn., p. 8. Elsevier, Amsterdam (2009)
Kingsley, P.B.: Introduction to diffusion tensor imaging mathematics: Part II. Anisotropy, diffusion-weighting factors, and gradient encoding schemes. Concepts in Magnetic Resonance Part A 28, 123–154 (2006)
Kingsley, P.B.: Introduction to diffusion tensor imaging mathematics: Part III. Tensor calculation, noise, simulations, and optimization. Concepts in Magnetic Resonance Part A 28, 155–179 (2006)
Skeletal, M., Reid, R.H.J., Lucia, L.B.: Histology for Pathologists, 3rd edn., p. 201. Williams & Wilkins, Baltimore (2009)
Bihan, D.L.: The ’wet mind’: water and functional neuroimaging. Physics in medicine and biology 52, R57–R90 (2007)
Iaizzo, P.A.: Handbook of Cardiac Anatomy, Physiology, and Devices, 2nd edn. (2009)
Friedrich, M.G.: Myocardial edema—a new clinical entity? Nature Reviews Cardiology (2010)
Egan, J.R., Butler, T.L., Au, C.G., Tan, Y.M., North, K.N., Winlaw, D.S.: Myocardial water handling and the role of aquaporins. Biochimica et Biophysica Acta (BBA)-Biomembranes 1758, 1043–1152 (2006)
Ogura, T., Imanishi, S., Shibamoto, T.: Osmometric and water-transporting properties of guinea pig cardiac myocytes. The Japanese Journal of Physiology 52, 333–342 (2002)
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Wang, L., Zhu, YM., Li, H., Liu, W., Magnin, I.E. (2011). Simulation of Diffusion Anisotropy in DTI for Virtual Cardiac Fiber Structure. In: Metaxas, D.N., Axel, L. (eds) Functional Imaging and Modeling of the Heart. FIMH 2011. Lecture Notes in Computer Science, vol 6666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21028-0_12
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DOI: https://doi.org/10.1007/978-3-642-21028-0_12
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