Bloch Equations & Typical MRI Contrast
Nikolaus Weiskopf1,2

1Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom

Synopsis

Target Audience

Physicists, engineers or scientists with training in MRI who are interested in contrast mechanisms.

Learning Objectives

- Understand the main components of the Bloch equations

- Understand how variations in relaxation times affect image contrast

- Appreciate how tissue microstructure affects relaxation

- Learn about examples how image contrast is exploited in neuroimaging

Brief Overview

- In most biological applications the MRI signal originates from protons within water

- Bloch equations phenomenologically describe the evolution of magnetization over time including relaxation behavior described by T1, T2 and T2* time constants

- Bloembergen-Purcell-Pound (BPP) theory describes dipole-dipole and spin-lattice relaxation and thus T1, T2

- Relaxation in tissue can be significantly enhanced due to exchange between bulk water and bound water at macromolecular sites

- Governing T1, T2, T2* relaxation time constants are tissue dependent and thus generate image contrast

- Contrast between tissue types and pathological tissue states is the basis for clinical diagnostics

- Contrast is increasingly used to make inferences on the underlying tissue microstructure, such as myelin and iron mapping in the brain

Discussion

Magnetic resonance imaging (MRI) relies on the phenomenon of nuclear magnetic resonance due to the spin of the nucleus. In medicine and biology typically the net magnetization of an ensemble of protons, i.e. nucleus of the hydrogen atom, is imaged. The phenomenological Bloch equations [1] describe the evolution of the net magnetization, and its components, and captures such phenomena as the excitation due to radio-frequency (RF) fields, precession in a static magnetic field (B0), and relaxation of magnetization.

Relaxation processes, and in particular the tissue-dependency of relaxation, are a cornerstone of MRI in medical and biological applications, since they underlie the exquisite contrast between tissue types and pathological states. In the state of equilibrium, the magnetization is aligned with the axis of the main static magnetic field, i.e., only longitudinal but no transverse magnetization is present. An RF pulse can excite the spin system, reducing longitudinal and generating transverse magnetization. Relaxation is the return of the magnetization to the state of equilibrium. Two types of relaxation behavior are included in the Bloch equations and characterized by relaxation time constants. 1) The longitudinal relaxation (longitudinal relaxation time T1) describes the recovery of the longitudinal magnetization component aligned with the main field. 2) The transverse relaxation (transverse relaxation time T2, or in the presence of inhomogeneities in the static magnetic field the apparent/effective transverse relaxation time T2*) describes the decay of the transverse magnetization component perpendicular to the main field.

Longitudinal relaxation is driven by the exchange of energy between the nuclear spin system and the surrounding environment, i.e. lattice – thus called spin-lattice relaxation. The transverse relaxation is primarily driven by interaction between the magnetic dipoles of spins – thus called spin-spin relaxation. The Bloembergen-Purcell-Pound (BPP) theory provides an intuition for the mechanisms behind spin-lattice and spin-spin relaxation in homogeneous liquids and other model systems [2] and predicts their relaxation times T1 and T2. Unlike the model systems that [2] focused on, the structure of biological tissue is highly complex with an abundance of membranes and macromolecules, leading to further refinements of relaxation theory in tissue [3]–[5]. Although the relaxation mechanisms in tissue are not fully understood, it is known that relaxivity is increased due to water-binding sites at the protein-water interface where significant relaxation and solute-solvent energy transfer occur [3]. Such sites are found in macromolecules in the brain, particularly the cholesterol in myelin [6].

The dependence of T1 on local myelination [7] is widely used in T1-weighted anatomical imaging to delineate differently myelinated gray from white matter. Recently, quantitative T1 maps have been used as a standardized means of elucidating the subtle myeloarchitecture of the human cortex at high spatial resolution [8]. In a similar vein, T2 and T2* have been used as markers of myelination [9] or of iron content [10]. The simultaneous acquisition of multiple relaxation parameters was used to disentangle contrast mechanisms and provide a better characterization of brain tissue [11]–[13]. In addition, endogenous contrast may be complemented by exogenous contrast agents, such as injected Gadolinium compounds used for characterizing vasculature or the perfused status of tumours.

Conclusion

MRI provides exquisite soft tissue contrast due to the tissue-dependent nature of magnetization relaxation. Characteristic relaxation times T1, T2 and T2* can offer insights into tissue microstructure at scales significantly smaller than the image voxel size. The consequent image contrast is widely exploited, e.g., in neuroimaging of gray and white matter structures.

Acknowledgements

No acknowledgement found.

References

[1] F. Bloch, “Nuclear Induction,” Phys. Rev., vol. 70, no. 7–8, pp. 460–474, Oct. 1946.

[2] N. Bloembergen, E. M. Purcell, and R. V. Pound, “Relaxation Effects in Nuclear Magnetic Resonance Absorption,” Phys. Rev., vol. 73, no. 7, pp. 679–712, Apr. 1948.

[3] S. H. Koenig, “Classes of hydration sites at protein-water interfaces: the source of contrast in magnetic resonance imaging,” Biophys. J., vol. 69, no. 2, pp. 593–603, Aug. 1995.

[4] W. D. Rooney, G. Johnson, X. Li, E. R. Cohen, S.-G. Kim, K. Ugurbil, and C. S. Springer, “Magnetic field and tissue dependencies of human brain longitudinal 1H2O relaxation in vivo,” Magn. Reson. Med. Off. J. Soc. Magn. Reson. Med. Soc. Magn. Reson. Med., vol. 57, no. 2, pp. 308–318, Feb. 2007.

[5] B. Halle and V. P. Denisov, “A new view of water dynamics in immobilized proteins.,” Biophys. J., vol. 69, no. 1, pp. 242–249, Jul. 1995.

[6] S. H. Koenig, “Cholesterol of myelin is the determinant of gray-white contrast in MRI of brain,” Magn. Reson. Med., vol. 20, no. 2, pp. 285–291, Aug. 1991.

[7] K. Schmierer, F. Scaravilli, D. R. Altmann, G. J. Barker, and D. H. Miller, “Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain,” Ann. Neurol., vol. 56, no. 3, pp. 407–415, Sep. 2004.

[8] A. Lutti, F. Dick, M. I. Sereno, and N. Weiskopf, “Using high-resolution quantitative mapping of R1 as an index of cortical myelination,” NeuroImage, vol. 93 Pt 2, pp. 176–188, Jun. 2014.

[9] M. F. Glasser and D. C. Van Essen, “Mapping human cortical areas in vivo based on myelin content as revealed by T1- and T2-weighted MRI,” J. Neurosci. Off. J. Soc. Neurosci., vol. 31, no. 32, pp. 11597–11616, Aug. 2011.

[10] C. Langkammer, N. Krebs, W. Goessler, E. Scheurer, F. Ebner, K. Yen, F. Fazekas, and S. Ropele, “Quantitative MR imaging of brain iron: a postmortem validation study,” Radiology, vol. 257, no. 2, pp. 455–462, Nov. 2010.

[11] C. Stüber, M. Morawski, A. Schäfer, C. Labadie, M. Wähnert, C. Leuze, M. Streicher, N. Barapatre, K. Reimann, S. Geyer, D. Spemann, and R. Turner, “Myelin and iron concentration in the human brain: a quantitative study of MRI contrast,” NeuroImage, vol. 93 Pt 1, pp. 95–106, Jun. 2014.

[12] M. F. Callaghan, G. Helms, A. Lutti, S. Mohammadi, and N. Weiskopf, “A general linear relaxometry model of R1 using imaging data,” Magn. Reson. Med., vol. 73, no. 3, pp. 1309–1314, Mar. 2015.

[13] N. Weiskopf, S. Mohammadi, A. Lutti, and M. F. Callaghan, “Advances in MRI-based computational neuroanatomy: from morphometry to in-vivo histology,” Curr. Opin. Neurol., vol. 28, no. 4, pp. 313–322, Aug. 2015.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)