Transcript Crossing-fibres - University of Oxford

Measuring Diffusion Properties in Tissue:
The Diffusion Tensor & Derived Indices
Gwenaëlle Douaud
FMRIB, University of Oxford
ISMRM Weekend course – 5th of May 2012
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Historical description of the diffusion tensor
• Formalised by Peter Basser and colleagues (1994a; 1994b)
 In an isotropic, unconstrained environment:
D = scalar
 In an anisotropic, constrained environment:
D = 33 definite symmetric positive
D = “diffusion tensor”
ISMRM Weekend course – 5th of May 2012
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Historical description of the diffusion tensor
 In an anisotropic, constrained environment:
D = 33 definite symmetric positive
D = “diffusion tensor”
1
2
3
with i  {1,2,3}
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Diffusion tensor indices: Mean Diffusivity
• Formalised by Peter Basser and Carlo Pierpaoli (1995; 1996)
 Magnitude of diffusion
Bammer, 2003
• First clinical application: brain ischemia (Moseley et al., 1990; Warach et al., 1992)
 Visible only 3 hours after onset of stroke
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Warach et al., 1995
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Diffusion tensor indices: diffusion anisotropy
• Formalised by Peter Basser and Carlo Pierpaoli (1995; 1996)
 Anisotropy of diffusion
Bammer, 2003
RA = “Relative Anisotropy”
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Diffusion tensor indices: diffusion anisotropy
• Formal comparison of three anisotropy indices (Papadakis et al., 1999)
 FA: mapped diffusion anisotropy with the greatest detail and SNR
 VR: provided the strongest CNR, but with  noise contamination, resolution
 RA: intermediate between FA and VR
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Diffusion tensor indices: diffusion anisotropy
• Further comparison between FA and RA (Hasan et al., 2004)
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Fractional Anisotropy and Mean Diffusivity:
ROI and voxel-based/TBSS analysis
• Developmental study: anatomical and tractography-defined ROI (Lebel et al., 2008)
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Fractional Anisotropy and Mean Diffusivity:
ROI and voxel-based/TBSS analysis
• Developmental study: comparison between ROI and VBD (Snook et al., 2007)
 The discrepancies related to:
- ROI approach inherently limited
- issues with the spatial normalisation for VBD analysis
- masking localised changes by averaging all the voxels within a ROI
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Fractional Anisotropy and Mean Diffusivity:
ROI and voxel-based/TBSS analysis
• Increasing sensitivity and interpretability of results compared with voxel-based
approaches based purely on non-linear registration: TBSS (Smith et al., 2006)
TBSS
VBD
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Mean
Control
Mean
Patient
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Fractional Anisotropy and Mean Diffusivity:
ROI and voxel-based/TBSS analysis
• Large developmental and ageing study using TBSS (Westlye et al., 2010)
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Fractional Anisotropy and Mean Diffusivity:
first applications
• Development (review in Beaulieu et al., 1999)
• Ageing (review in Moseley, 2002)
• Cognitive performance (review in Moseley et al., 2002)
• White matter diseases (review in Horsfield and Jones, 2002):
multiple sclerosis (Horsfield et al., 1998), Alzheimer’s
disease (Hanyu et al., 1998), ALS, CJD etc.
• Psychiatric diseases (review in Lim and Helpern, 2002):
schizophrenia (Buchsbaum et al., 1998), alcoholism
(Pfefferbaum et al., 2000) , depression etc.
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Fractional Anisotropy and Mean Diffusivity:
Two complementary measures
• An intriguing finding in multiple sclerosis (Ciccarelli et al., 2001)
White matter
Patient
Control
basal ganglia
 Increased FA in the basal ganglia in MS: selective Wallerian degeneration, with the
intact connections showing an increase of their coherence?
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Fractional Anisotropy and Mean Diffusivity:
Two complementary measures
• Same findings seen in the basal ganglia in Huntington’s disease (Douaud et al., 2009)
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• Using the information from the PDD (Schwartzmann et al., 2005)
1
2
3
Douaud et al., 2009
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• Decrease of the dispersion of the PDD in Huntington’s disease (Douaud et al., 2009)
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Beyond Fractional Anisotropy and Mean Diffusivity:
the Mode of anisotropy
• No difference in the white matter of mild cognitive impairment (MCI) patients
using MD or FA (Douaud et al., 2011)
 Mode of anisotropy (MO): 3rd moment of the tensor, introduced by Basser (1997),
formalised by Ennis and Kindlamnn (2006).
-1
Planar, disc-like 1~ 2:
e.g., areas of crossing fibres
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+1
Linear, cigar-like 2~ 3:
e.g., areas of one
predominating fibre
population
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Beyond Fractional Anisotropy and Mean Diffusivity:
the Mode of anisotropy
• Significant difference in the white matter of MCI patients, with an increase of MO
MCI>CON
AD>CON AD>CON
Douaud et al., 2011
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Beyond Fractional Anisotropy and Mean Diffusivity:
the Mode of anisotropy
• Significant increase of MO in MCI and AD also related to selective degeneration in
crossing fibres region (here, centrum semiovale)?
Douaud et al., 2011
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Beyond Fractional Anisotropy and Mean Diffusivity:
Parallel and Perpendicular Diffusivity
• Validated in animal models by Song and colleagues (2002; 2005)
 Parallel diffusivity or axial diffusivity: assessing axonal injury
= 1
 Perpendicular diffusivity or radial diffusivity: assessing myelin injury
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Beyond Fractional Anisotropy and Mean Diffusivity:
Parallel and Perpendicular Diffusivity
• Validated in humans using the model of callosotomy (Concha et al., 2006)
 Axonal degradation
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 Myelin degradation
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Diffusion tensor indices:
in vivo models and histological validation
• Basis of diffusion anisotropy in the brain: comprehensive review by Beaulieu (2002)
 Anisotropy due to membrane, not myelin
 Myelin modulates anisotropy
 Axonal cytoskeleton does not contribute to anisotropy
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Diffusion tensor indices:
in vivo models and histological validation
• Combined in vivo diffusion/histological study: animal model (van Camp et al., 2012)
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Diffusion tensor indices:
in vivo models and histological validation
• Combined in vivo diffusion/histological study: epilepsy (Concha et al., 2010)
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The depressing slide…
• Sensitivity to noise increases with higher order moments:
noise(MD) < noise(FA) < noise (MO)
• Crossing-fibres: effects can be averaged out
Groeschel et al., ISMRM 2011
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The depressing slide…
• Sensitivity to noise increases with higher order moments:
noise(MD) < noise(FA) < noise (MO)
• Crossing-fibres: effects can be averaged out
• Crossing-fibres: problematic interpretation of  and 
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The depressing slide…
• Sensitivity to noise increases with higher order moments:
noise(MD) < noise(FA) < noise (MO)
• Crossing-fibres: effects can be averaged out
• Crossing-fibres: problematic interpretation of  and 
• Crossing-fibres: not only influence on FA, but also MD (Vos et al., 2012)
Vos et al., ISMRM 2011
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The depressing slide…
• Sensitivity to noise increases with higher order moments:
noise(MD) < noise(FA) < noise (MO)
• Crossing-fibres: effects can be averaged out
• Crossing-fibres: problematic interpretation of  and 
• Crossing-fibres: not only influence on FA, but also MD
• Effect of partial volume effect on FA, MD etc. (Jones, ISMRM 2011)
Correction for CSF contamination? (Metzler-Baddeley et al., 2012)
• Choice of sequence: anisotropic voxels (Vos et al., ISMRM 2011)
• Choice of sequence: 12 orientations, 5 b-values: more sensitive to using MD
30 orientations, 2 b-values: more sensitive to  using FA
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…Take home message
• Choice of sequence: isotropic voxels, optimised for specific question
• FA and MD complementary to interpret results: higher FA is not necessarily better
•  and  give additional information (e.g., Salat et al., 2010)
• Do not forget about PVE, noise and crossing fibres to help interpret results
 If ambiguous interpretation: MO, dispersion of PDD, Westin indices (Westin et al., 1997)
Vos et al., ISMRM 2011
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…Take home message
• Choice of sequence: isotropic voxels, optimised for specific question
• FA and MD complementary to interpret results: higher FA is not necessarily better
•  and  give additional information (e.g., Salat et al., 2010)
• Do not forget about PVE, noise and crossing fibres to help interpret results
 If ambiguous interpretation: MO, dispersion of PDD, Westin indices (Westin et al., 1997)
• Crossing fibres helps detect subtle differences (Tuch et al., 2005; Douaud et al., 2011)
Tuch et al., 2005
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Special thanks to:
SHFJ, CEA, Orsay
FMRIB, University of Oxford
- Cyril Poupon
- Yann Cointepas
- Denis Riviere
- Jean-Francois Mangin
- Karla Miller
- Stamatios Sotiropoulos
- Timothy Behrens
- Steve Smith
- Peter Jezzard
- Saad Jbabdi
THANK YOU
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Other diffusion tensor-derived measures
• “Westin” indices describing the tensor shape: sphericity, linearity and planarity
(Westin et al., 1997)
• Inter-voxel measures: lattice index (Pierpaoli)
• Fourth moment: kurtosis (Assaf)
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