Anisotropic WM conductivity reconstruction based on diffusion tensor magnetic resonance imaging: a simulation study

ABSTRACT

The present study aims to estimate the in vivo anisotropic conductivities of the White Matter (WM) tissues by means of Magnetic Resonance Electrical Impedance Tomography (MREIT) technique. The realistic anisotropic volume conductor model with different conductivity properties (scalp, skull, CSF, gray matter and WM) is constructed based on the Diffusion Tensor Magnetic Resonance Imaging (DT- MRI) from a healthy human subject. The Radius Basic Function (RBF)-MREIT algorithm of using only one magnetic flux density component was applied to evaluate the eigenvalues of the anisotropic WM with target values set according to the DT-MRI data based on the Wolter’s model, which is more physiologically reliable. The numerical simulations study performed on the five-layer realistic human head model showed that the conductivity reconstruction method had higher accuracy and better robustness against noise. The pilot research was used to judge the feasibility, meaningfulness and reliability of the MREIT applied on the electrical impedance tomography of the complicated human head tissues including anisotropic characteristics.

The present study aims to estimate the in vivo anisotropic conductivities of the White Matter (WM) tissues by means of Magnetic Resonance Electrical Impedance Tomography (MREIT) technique. The realistic anisotropic volume conductor model with different conductivity properties (scalp, skull, CSF, gray matter and WM) is constructed based on the Diffusion Tensor Magnetic Resonance Imaging (DT- MRI) from a healthy human subject. The Radius Basic Function (RBF)-MREIT algorithm of using only one magnetic flux density component was applied to evaluate the eigenvalues of the anisotropic WM with target values set according to the DT-MRI data based on the Wolter’s model, which is more physiologically reliable. The numerical simulations study performed on the five-layer realistic human head model showed that the conductivity reconstruction method had higher accuracy and better robustness against noise. The pilot research was used to judge the feasibility, meaningfulness and reliability of the MREIT applied on the electrical impedance tomography of the complicated human head tissues including anisotropic characteristics.

Cite this paper

nullYan, D. , Xu, W. and Li, J. (2010) Anisotropic WM conductivity reconstruction based on diffusion tensor magnetic resonance imaging: a simulation study.*Journal of Biomedical Science and Engineering*, **3**, 776-784. doi: 10.4236/jbise.2010.38103.

nullYan, D. , Xu, W. and Li, J. (2010) Anisotropic WM conductivity reconstruction based on diffusion tensor magnetic resonance imaging: a simulation study.

References

[1] He, B. (2005) Neural engineering. Kluwer Academic Publishers, Norwell.

[2] Haueisen, J., Tuch, D.S., Ramon, C., Schimpf, P.H., Wedeen, V.J., George, J.S. and Belliveau, J.W. (2002) The influence of brain tissue anisotropy on human EEG and MEG. NeuroImage, 15(1), 159-166.

[3] Wolters, C.H., Anwander, A., Tricoche, X., Weinstein, D., Koch, M.A. and MacLeod, R.S. (2006) Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling. NeuroImage, 30(3), 813-826.

[4] Basser, P.J., Mattiello, J. and Lebihan, D. (1994) MR diffusion tensor spectroscopy and imaging. Biophysical Journal, 66(1), 259-267.

[5] Tuch, D.S., Wedeen, V.J., Dale, A.M., George, J.S. and Belliveau, J.W. (1999) Conductivity tensor mapping of the human brain using diffusion MRI. Annals of the New York Academy of Sciences, 888, 314-316.

[6] Wolters, C.H. (2002) Influence of tissue conductivity inhomogeneity and anisotropy on EEG/MEG based source localization in the human brain. Leipzig University, Leipzig.

[7] Wang, K., Zhu, S.A., Mueller, B., Lim, K., Liu, Z.M. and He, B. (2008) A new method to derive WM conductivity from diffusion tensor MRI. IEEE Transactions on Bio- medical Engineering, 55(10), 2481-2486.

[8] Goncalves, S., de Munck, J.C., Heethaar, R.M. and da Silva, F.L. (2003) In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head. IEEE Transactions on Biomedical Engineering, 50(6), 754-767.

[9] Lai, Y., van Drongelen, W., Ding, L., Hecox, K.E., Towle, V.L., Frim, D.M. and He, B. (2005) Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings. Clinical Neurophysiology, 116(2), 456-465.

[10] Birgül, ?., Eyübo?lu, B.M. and ?der, Y.Z. (2003) Current constrainted voltage scaled reconstruction (CCSVR) algorithm for MR-EIT and its performance with different probing current patterns. Physics in Medicine and Biology, 48, 653-671.

[11] ?der, Y.Z. and Birgül, ?. (1998) Use of the magnetic field generated by the internal distribution of injected currents for electrical impedance tomography (MR-EIT). Elektrik, Turkish Journal of Electrical Engineering and Computer Sciences, 6(3), 215-225.

[12] Khang, H.S., Lee, B.I., Oh, S.H., Woo, E.J., Lee, S.Y., Cho, M.H., Kwon, O., Yoon, J.R. and Seo, J.K. (2002) J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): Phantom experiments for static resistivity images. IEEE Transactions on Medi- cal Imaging, 21(6), 695-702.

[13] Kwon, O., Lee, J.Y. and Yoo, J.R. (2002) Equipotential line method for magnetic resonance electrical impedance tomography (MREIT). Inverse Problems, 18(2), 1089-1100.

[14] ?zdemir, M.S., Eyübo?lu, B.M. and ?zbek, O. (2004) Equipotential projection-based magnetic resonance elec- trical impedance tomography and experimental realization. Physics in Medicine and Biology, 49(20), 4765-4783.

[15] Seo, J.K., Yoon, J.R., Woo, E.J. and Kwon, O. (2003) Reconstruction of conductivity and current density imaging using only one component of magnetic field measure- ments. IEEE Transactions on Biomedical Engineering, 50(9), 1121-1124.

[16] Oh, S.H., Lee, B.I., Woo, E.J., Lee, S.Y., Cho, M.H., Kwon, O. and Seo, J.K. (2003) Conductivity and current density image reconstruction using harmonic Bz algori- thm in magnetic resonance electrical impedance tomo- graphy. Physics in Medicine and Biology, 48(19), 3101- 3116.

[17] Oh, S.H., Lee, B.I., Woo, E.J., Lee, S.Y., Kim, T.S., Kwon, O. and Seo, J.K. (2005) Electrical conductivity images of biological tissue phantom in MREIT. Physi- ological Measurement, 26(2), S279-S288.

[18] ?der, Y.Z. and Onart, S. (2004) Algebric reconstruction for 3D magnetic resonance-electrical impedance tomog- raphy (MREIT) using one component of magnetic flux density. Physiological Measurement, 25(1), 281-294.

[19] Park, C., Kwon, O., Woo, E.J. and Seo, J.K. (2004) Electrical conductivity imaging using gradient Bz de- composition algorithm in magnetic resonance electrical impedance tomography (MREIT). IEEE Transactions on Medical Imaging, 23(3), 388-394.

[20] Gao, N., Zhu, S.A. and He, B. (2005) Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement. Physics in Medicine and Biology, 50(11), 2675-2687.

[21] Gao, N., Zhu, S.A. and He, B. (2006) A new magnetic resonance electrical impedance tomography (MREIT) algorithm: the RSM-MREIT algorithm with applications to estimation of human head conductivity. Physics in Medicine and Biology, 51(12), 3067-3083.

[22] Gao, N. and He, B. (2008) Noninvasive imaging of bioimpedance distribution by means of current recon- struction magnetic resonance electrical impedance tomo- graphy. IEEE Transactions on Biomedical Engineering, 55(5), 1530-1539.

[23] Birgül, ?. and ?der, Y.Z. (1998) Use of magnetic field generated by the internal distribution of injected currents for electrical impedance tomography (MREIT). Elektrik, 6(3), 215-225.

[24] Seo, J.K., Pyo, H.C., Park, C., Kwon, O. and Woo, E.J. (2004) Image reconstruction of anisotropic conductivity tensor distribution in MREIT: Computer simulation study. Physics in Medicine and Biology, 49(18), 4371-4382.

[25] Zhang, Y.C., van Drongelen, W. and He, B. (2006) Estimation of in vivo brain-to-skull conductivity ratio in humans. Applied Physics Letters, 89(22), 223903- 2239033.

[26] Yao, Y., Zhu, S.A. and He, B. (2005) A method to derive FEM models based on BEM models. IEEE 27th Annual International Conference, Engineering in Medicine and Biology Society (EMBS), Shanghai, 1-4 September 2005, 1575-1577.

[27] Scott, G.C., Joy, M.L.G. and Armstrong, R.L. (1992) Sensitivity of magnetic-resonance current-density ima- ging. Journal of Magnetic Resonance, 97(2), 235-254.

[28] Awada, K.A., Jackson, D.R., Baumann, S.B., Williams, J.T., Wilton, D.R., Fink, P.W. and Prasky, B.R. (1998) Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Transactions on Biomedical Engineering, 45(9), 1135-1145.

[29] Ferree, T.C., Eriksen, K.J. and Tucker, D.M. (2000) Regional head tissue conductivity estimation for improved EEG analysis. IEEE Transactions on Biomedical Engi- neering, 47(12), 1584-1592.

[30] Gen?er, N.G. and Acar, C.E. (2004) Sensitivity of EEG and MEG measurements to tissue conductivity. Physics in Medicine and Biology, 49(5), 707-717.

[1] He, B. (2005) Neural engineering. Kluwer Academic Publishers, Norwell.

[2] Haueisen, J., Tuch, D.S., Ramon, C., Schimpf, P.H., Wedeen, V.J., George, J.S. and Belliveau, J.W. (2002) The influence of brain tissue anisotropy on human EEG and MEG. NeuroImage, 15(1), 159-166.

[3] Wolters, C.H., Anwander, A., Tricoche, X., Weinstein, D., Koch, M.A. and MacLeod, R.S. (2006) Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling. NeuroImage, 30(3), 813-826.

[4] Basser, P.J., Mattiello, J. and Lebihan, D. (1994) MR diffusion tensor spectroscopy and imaging. Biophysical Journal, 66(1), 259-267.

[5] Tuch, D.S., Wedeen, V.J., Dale, A.M., George, J.S. and Belliveau, J.W. (1999) Conductivity tensor mapping of the human brain using diffusion MRI. Annals of the New York Academy of Sciences, 888, 314-316.

[6] Wolters, C.H. (2002) Influence of tissue conductivity inhomogeneity and anisotropy on EEG/MEG based source localization in the human brain. Leipzig University, Leipzig.

[7] Wang, K., Zhu, S.A., Mueller, B., Lim, K., Liu, Z.M. and He, B. (2008) A new method to derive WM conductivity from diffusion tensor MRI. IEEE Transactions on Bio- medical Engineering, 55(10), 2481-2486.

[8] Goncalves, S., de Munck, J.C., Heethaar, R.M. and da Silva, F.L. (2003) In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head. IEEE Transactions on Biomedical Engineering, 50(6), 754-767.

[9] Lai, Y., van Drongelen, W., Ding, L., Hecox, K.E., Towle, V.L., Frim, D.M. and He, B. (2005) Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings. Clinical Neurophysiology, 116(2), 456-465.

[10] Birgül, ?., Eyübo?lu, B.M. and ?der, Y.Z. (2003) Current constrainted voltage scaled reconstruction (CCSVR) algorithm for MR-EIT and its performance with different probing current patterns. Physics in Medicine and Biology, 48, 653-671.

[11] ?der, Y.Z. and Birgül, ?. (1998) Use of the magnetic field generated by the internal distribution of injected currents for electrical impedance tomography (MR-EIT). Elektrik, Turkish Journal of Electrical Engineering and Computer Sciences, 6(3), 215-225.

[12] Khang, H.S., Lee, B.I., Oh, S.H., Woo, E.J., Lee, S.Y., Cho, M.H., Kwon, O., Yoon, J.R. and Seo, J.K. (2002) J-substitution algorithm in magnetic resonance electrical impedance tomography (MREIT): Phantom experiments for static resistivity images. IEEE Transactions on Medi- cal Imaging, 21(6), 695-702.

[13] Kwon, O., Lee, J.Y. and Yoo, J.R. (2002) Equipotential line method for magnetic resonance electrical impedance tomography (MREIT). Inverse Problems, 18(2), 1089-1100.

[14] ?zdemir, M.S., Eyübo?lu, B.M. and ?zbek, O. (2004) Equipotential projection-based magnetic resonance elec- trical impedance tomography and experimental realization. Physics in Medicine and Biology, 49(20), 4765-4783.

[15] Seo, J.K., Yoon, J.R., Woo, E.J. and Kwon, O. (2003) Reconstruction of conductivity and current density imaging using only one component of magnetic field measure- ments. IEEE Transactions on Biomedical Engineering, 50(9), 1121-1124.

[16] Oh, S.H., Lee, B.I., Woo, E.J., Lee, S.Y., Cho, M.H., Kwon, O. and Seo, J.K. (2003) Conductivity and current density image reconstruction using harmonic Bz algori- thm in magnetic resonance electrical impedance tomo- graphy. Physics in Medicine and Biology, 48(19), 3101- 3116.

[17] Oh, S.H., Lee, B.I., Woo, E.J., Lee, S.Y., Kim, T.S., Kwon, O. and Seo, J.K. (2005) Electrical conductivity images of biological tissue phantom in MREIT. Physi- ological Measurement, 26(2), S279-S288.

[18] ?der, Y.Z. and Onart, S. (2004) Algebric reconstruction for 3D magnetic resonance-electrical impedance tomog- raphy (MREIT) using one component of magnetic flux density. Physiological Measurement, 25(1), 281-294.

[19] Park, C., Kwon, O., Woo, E.J. and Seo, J.K. (2004) Electrical conductivity imaging using gradient Bz de- composition algorithm in magnetic resonance electrical impedance tomography (MREIT). IEEE Transactions on Medical Imaging, 23(3), 388-394.

[20] Gao, N., Zhu, S.A. and He, B. (2005) Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement. Physics in Medicine and Biology, 50(11), 2675-2687.

[21] Gao, N., Zhu, S.A. and He, B. (2006) A new magnetic resonance electrical impedance tomography (MREIT) algorithm: the RSM-MREIT algorithm with applications to estimation of human head conductivity. Physics in Medicine and Biology, 51(12), 3067-3083.

[22] Gao, N. and He, B. (2008) Noninvasive imaging of bioimpedance distribution by means of current recon- struction magnetic resonance electrical impedance tomo- graphy. IEEE Transactions on Biomedical Engineering, 55(5), 1530-1539.

[23] Birgül, ?. and ?der, Y.Z. (1998) Use of magnetic field generated by the internal distribution of injected currents for electrical impedance tomography (MREIT). Elektrik, 6(3), 215-225.

[24] Seo, J.K., Pyo, H.C., Park, C., Kwon, O. and Woo, E.J. (2004) Image reconstruction of anisotropic conductivity tensor distribution in MREIT: Computer simulation study. Physics in Medicine and Biology, 49(18), 4371-4382.

[25] Zhang, Y.C., van Drongelen, W. and He, B. (2006) Estimation of in vivo brain-to-skull conductivity ratio in humans. Applied Physics Letters, 89(22), 223903- 2239033.

[26] Yao, Y., Zhu, S.A. and He, B. (2005) A method to derive FEM models based on BEM models. IEEE 27th Annual International Conference, Engineering in Medicine and Biology Society (EMBS), Shanghai, 1-4 September 2005, 1575-1577.

[27] Scott, G.C., Joy, M.L.G. and Armstrong, R.L. (1992) Sensitivity of magnetic-resonance current-density ima- ging. Journal of Magnetic Resonance, 97(2), 235-254.

[28] Awada, K.A., Jackson, D.R., Baumann, S.B., Williams, J.T., Wilton, D.R., Fink, P.W. and Prasky, B.R. (1998) Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Transactions on Biomedical Engineering, 45(9), 1135-1145.

[29] Ferree, T.C., Eriksen, K.J. and Tucker, D.M. (2000) Regional head tissue conductivity estimation for improved EEG analysis. IEEE Transactions on Biomedical Engi- neering, 47(12), 1584-1592.

[30] Gen?er, N.G. and Acar, C.E. (2004) Sensitivity of EEG and MEG measurements to tissue conductivity. Physics in Medicine and Biology, 49(5), 707-717.