Type:
Educational Exhibit
Keywords:
Oncology, Neuroradiology brain, Paediatric, MR, MR-Functional imaging, Neural networks, Physics, Technical aspects, Localisation, Neoplasia, Multidisciplinary cancer care, Tissue characterisation
Authors:
T. Chandra1, K. Gupta2; 1Orlando/US, 2Chennai/IN
DOI:
10.26044/ecr2019/C-2977
Background
- Diffusion Tensor Imaging (DTI) is a novel method which has various applications in clinical neuroimaging and research
- Within the CNS,
water diffusion is more anisotropic in white matter and isotropic in gray matter and CSF
- This property can be exploited to highlight white matter changes in various pathological processes
- DTI is a powerful tool for assessment of microstructural integrity of the white matter qualitatively as well as quantitatively
Principle of Diffusion Imaging
- Water molecules in biological tissues are in constant movement,
governed by two major principles:
a.
Fick`s Law: Random diffusion due to concentration differences
b.
Temperature and ion-ion interactions
- Diffusion of water molecules can be restricted in various pathological conditions
Diffusion Imaging
- Detects the molecular motion of water and allows for quantitative assessment of the freedom of diffusion
- The addition of 2 strong,
symmetric gradients (Fig 2) to a EPI SE sequence,
this helps in differentiation of stationary from mobile water molecule
- If there is net movement of spins between the 2 gradients,
signal attenuation occurs (Fig 3)
b Value
- Represents the strength of ‘diffusion sensitizing gradients’(Fig 4)
- Expressed in s/mm2
- Larger b value –required to detect smaller magnitudes of water motion
Exponential Apparent Diffusion Coefficient- eADC
- Derived from dividing DWI by T2 images to remove effects of T2 shine through
- True restricted diffusion – dark on ADC,
bright on eADC
- ADC or eADC maps can be used depending on whether we want contrast to match (or be opposite to) the diffusion weighted images
Diffusion Tensor Imaging
- Tensor is a matrix of numbers derived from diffusion measurements in various directions
- DTI requires obtaining data from diffusion acquisitions with gradients in different directions in each acquisition to provide directional information
- The information is represented by 3 eigen values which represent the direction of 3 major axes of the ellipsoid and 3 eigen vectors that represent the magnitude in these directions
- In the white matter,
diffusion is anisotropic and is related to cell density and integrity,
axonal integrity and myelination status
- Tensor is a mathematical model of directional anisotropy of diffusion
- Diffusion tensor describes Gaussian diffusion distribution - a 3D ellipsoid with lengths and orientations of the 3 axes corresponding to the eigenvectors - λ1,
λ2 and λ3
- Acquisition in at least 6 directions required,
but clinically up to 30 directions are used
- From the tensor,
we can calculate:
a.
Direction of greatest diffusion
b.
Degree of anisotropy
c.
Diffusion constant in any direction