Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT)

This article describes an accurate and fast method for fiber orientation mapping using multidirectional diffusion-weighted magnetic resonance (MR) data. This novel approach utilizes the Fourier transform relationship between the water displacement probabilities and diffusion-attenuated MR signal expressed in spherical coordinates. The radial part of the Fourier integral is evaluated analytically under the assumption that MR signal attenuates exponentially. The values of the resulting functions are evaluated at a fixed distance away from the origin. The spherical harmonic transform of these functions yields the Laplace series coefficients of the probabilities on a sphere of fixed radius. Alternatively, probability values can be computed nonparametrically using Legendre polynomials. Orientation maps calculated from excised rat nervous tissue data demonstrate this technique's ability to accurately resolve crossing fibers in anatomical regions such as the optic chiasm. This proposed methodology has a trivial extension to multiexponential diffusion-weighted signal decay. The developed methods will improve the reliability of tractography schemes and may make it possible to correctly identify the neural connections between functionally connected regions of the nervous system.

[1]  C. Westin,et al.  Magnetic Resonance in Medicine 51:321–330 (2004) Biexponential Diffusion Tensor Analysis of Human Brain Diffusion Data , 2022 .

[2]  V. Wedeen,et al.  Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI , 2000 .

[3]  E. Stejskal Use of Spin Echoes in a Pulsed Magnetic‐Field Gradient to Study Anisotropic, Restricted Diffusion and Flow , 1965 .

[4]  F. Schwabl,et al.  Quantum Mechanics , 1992 .

[5]  Sinisa Pajevic,et al.  Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: Application to white matter fiber tract mapping in the human brain , 1999, Magnetic resonance in medicine.

[6]  D. Le Bihan,et al.  Diffusion/perfusion MR imaging of the brain: from structure to function. , 1990 .

[7]  L. Frank Characterization of anisotropy in high angular resolution diffusion‐weighted MRI , 2002, Magnetic resonance in medicine.

[8]  P. Basser,et al.  New modeling and experimental framework to characterize hindered and restricted water diffusion in brain white matter , 2004, Magnetic resonance in medicine.

[9]  J. E. Tanner,et al.  Spin diffusion measurements : spin echoes in the presence of a time-dependent field gradient , 1965 .

[10]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[11]  D L Buckley,et al.  Visualization of neural tissue water compartments using biexponential diffusion tensor MRI , 2001, Magnetic resonance in medicine.

[12]  P. Basser,et al.  Estimation of the effective self-diffusion tensor from the NMR spin echo. , 1994, Journal of magnetic resonance. Series B.

[13]  Alan Connelly,et al.  Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution , 2004, NeuroImage.

[14]  P. Callaghan,et al.  Diffraction-like effects in NMR diffusion studies of fluids in porous solids , 1991, Nature.

[15]  Yaniv Assaf,et al.  The effect of rotational angle and experimental parameters on the diffraction patterns and micro-structural information obtained from q-space diffusion NMR: implication for diffusion in white matter fibers. , 2004, Journal of magnetic resonance.

[16]  P. Basser Relationships between diffusion tensor and q‐space MRI † , 2002, Magnetic resonance in medicine.

[17]  D. Tuch Q‐ball imaging , 2004, Magnetic resonance in medicine.

[18]  D. Tuch High Angular Resolution Diffusion Imaging of the Human Brain , 1999 .

[19]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[20]  Bengt Jönsson,et al.  Restricted Diffusion in Cylindrical Geometry , 1995 .

[21]  S. Lessell,et al.  The histology and histochemistry of the rat's optic nerve and chiasm. , 1977, American journal of ophthalmology.

[22]  P. Callaghan Principles of Nuclear Magnetic Resonance Microscopy , 1991 .

[23]  S. Arridge,et al.  Detection and modeling of non‐Gaussian apparent diffusion coefficient profiles in human brain data , 2002, Magnetic resonance in medicine.

[24]  C F Hazlewood,et al.  Nuclear magnetic resonance measurement of skeletal muscle: anisotrophy of the diffusion coefficient of the intracellular water. , 1976, Biophysical journal.

[25]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[26]  T. Chenevert,et al.  Anisotropic diffusion in human white matter: demonstration with MR techniques in vivo. , 1990, Radiology.

[27]  J. Tsuruda,et al.  Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. , 1990, Radiology.

[28]  G. Arfken Mathematical Methods for Physicists , 1967 .

[29]  V. Wedeen,et al.  Diffusion MRI of Complex Neural Architecture , 2003, Neuron.

[30]  Graham J. L. Kemp,et al.  Fast computation, rotation, and comparison of low resolution spherical harmonic molecular surfaces , 1999, J. Comput. Chem..

[31]  R Mark Henkelman,et al.  Orientational diffusion reflects fiber structure within a voxel , 2002, Magnetic resonance in medicine.

[32]  Kalvis M. Jansons,et al.  Persistent angular structure: new insights from diffusion magnetic resonance imaging data , 2003 .

[33]  P. Basser Inferring microstructural features and the physiological state of tissues from diffusion‐weighted images , 1995, NMR in biomedicine.

[34]  Daniel C. Alexander,et al.  Probabilistic Monte Carlo Based Mapping of Cerebral Connections Utilising Whole-Brain Crossing Fibre Information , 2003, IPMI.

[35]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[36]  T. Mareci,et al.  Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging , 2003, Magnetic resonance in medicine.

[37]  N. Makris,et al.  High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity , 2002, Magnetic resonance in medicine.

[38]  D. Norris,et al.  Biexponential diffusion attenuation in various states of brain tissue: Implications for diffusion‐weighted imaging , 1996, Magnetic resonance in medicine.

[39]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[40]  B. Vemuri,et al.  Generalized scalar measures for diffusion MRI using trace, variance, and entropy , 2005, Magnetic resonance in medicine.

[41]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.