diffusion tensor imaging ii: techniques and applications

Diffusion Tensor Imaging II: Techniques and applications

Jennifer Campbell

•  scalar maps from diffusion imaging •  connectivity analysis •  complex subvoxel fiber microstructure •  diffusion contrast for functional imaging?

Diffusion Tensor Imaging II: Techniques and applications

Diffusion Imaging

Tissue structures determine which directions of motion are most probable

P(r | r0,! d) =1

| D | (4"! d)3• exp (r # r0)T D#1(r # r0)

4! d

$%&

'()

The diffusion tensor

Dxx Dxy Dxz

Dyx Dyy Dyz

Dzx Dzy Dzz

!

"

###

$

%

&&&

λ1

λ3 λ2

e1

Maps obtainable from the diffusion tensor

RGB plot: principal eigenvector (e1)

direction, scaled by FA

trace of diffusion tensor

(mean diffusivity)

anisotropy index: fractional anisotropy (FA)

anisotropy index: fractional anisotropy (FA)

trace of diffusion tensor

(mean diffusivity)

RGB plot: principal eigenvector (e1)

direction, scaled by FA

FA = 32

(!1" !)2 + (! 2 " !)2 + (! 3" !)2

(!12 + !2

2 + ! 32 )

MD = ! = trace / 3 = !1 + ! 2 + ! 3

3

Maps obtainable from the diffusion tensor

•  scalar maps from diffusion imaging •  connectivity analysis •  complex subvoxel fiber microstructure •  diffusion contrast for functional imaging?

Diffusion Tensor Imaging II: Techniques and applications

Applications: Stroke

•  Moseley (1990): ADC decreases in ischemia. •  Causes: cell membrane permeability decreases lead to cellular swelling

(currently debate about exact mechanism) •  Early diagnosis: diffusion MRI can identify regions of ischemia within

30 minutes of arterial occlusion, while T2 images show changes only after 2 hours

•  Chronic stroke can also cause Wallerian degeneration, leading to reduced FA

Applications: Multiple Sclerosis T2 FA

Bammer et al, MRM 2000

PD (left); T1 (right)

MD (left); FA (right)

increased MD and reduced FA in halo around ring-enhancing lesion

Applications: Multiple Sclerosis

Applications: Cancer •  ADC higher in cysts and cystic components of tumours,

where diffusion is free. Can be used to differentiate cysts from solid tumours (difficult to differentiate with T1, T2)

Kono K et al. AJNR Am J Neuroradiol 2001;22:1081-1088

•  tumour grading •  examine white matter tracts

proximal to tumours; infiltration vs. displacement

•  evaluation of treatment of cancer: ADC is lower in radiation damaged tissue

DW ADC

Applications: Dyslexia

•  Subjects with reading difficulty exhibited decreased FA bilaterally in temporo-parietal areas involved in visual, auditory, and language processing

Klingsberg et al, Neuron 2000

Tract-based spatial statistics (TBSS)

Smith et al., NIMG 2006

•  reduces problems associated with, e.g., partial volume averaging, misalignment

•  project highest FA value in region (“centre of tract”) onto average FA skeleton

•  scalar maps from diffusion imaging •  connectivity analysis •  complex subvoxel fiber microstructure •  diffusion contrast for functional imaging?

Diffusion Tensor Imaging II: Techniques and applications

Diffusion MRI Tractography

Diffusion MRI Tractography

Diffusion MRI Tractography

human, postmortem Klinger method

nonhuman, tracer injection

human, in vivo

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

A: inclusion or stopping mask based on thresholding a scalar map, e.g., fractional anisotropy (FA)

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

B: tract-delineating regions of interest (ROIs):

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

B: tract-delineating regions of interest (ROIs): - may be intermediate points or expected end points -“way points” or “obligatory passages”

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

C: exclusion masks

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

C: exclusion masks

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

B: tract-delineating regions of interest (ROIs): - may be intermediate points or expected end points -“way points” or “obligatory passages”

Tract delineation

Calamante et al. NeuroImage 2010.

tractography constraints: B: tract-delineating regions of interest (ROIs): - may be intermediate points or expected end points -“way points” or “obligatory passages”

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

D: curvature constraints

Tract delineation

tractography constraints: Calamante et al. NeuroImage 2010.

D: curvature constraints E: other inclusion or exclusion criteria, e.g., tract length

Tractography of major white matter fasciculi

Catani et al. Cortex 2008.

Tractography: warnings •  Diffusion MRI tractography results include many false

positives and false negatives: priors are essential. –  Tractography is good for segmentation of parts of pathways, but

segmenting the entire pathway can be challenging (false negatives). –  Characterizing unknown new anatomy is much more difficult than

studying known anatomy (false positives). –  Example: Thomas et al. (Brain, 2005) report increase in fiber count

in corticobulbar tract on unaffected hemisphere in cerebral palsy: is this due to reorganization, or is this tract easier to trace due to the absence of callosal inputs from the affected hemisphere?

•  Tractography does not distinguish between afferent and efferent pathways, or between mono- and multisynaptic connections.

Probabilistic tractography: incorporating uncertainty

Jeurissen et al. HBM 2010.

Probabilistic tractography: incorporating uncertainty

Tract delineation techniques •  define tract delineating

ROIs manually with well-defined protocol (e.g., Mori et al., 2005; Wakana et al., 2007, Catani et al., 2008)

•  define tract delineating ROIs using fMRI activations (e.g., Powell et al., 2006; Ghaderi et al., ISMRM 2012)

•  define tract delineating ROIs automatically (e.g., using population atlas - Rose et al. 2010)

Catani et al. Cortex 2008.

Tract delineation techniques •  define tract delineating

ROIs manually with well-defined protocol (e.g., Mori et al., 2005; Wakana et al., 2007, Catani et al., 2008)

•  define tract delineating ROIs using fMRI activations (e.g., Powell et al., 2006; Ghaderi et al., ISMRM 2012)

•  define tract delineating ROIs automatically (e.g., using population atlas - Rose et al. 2010)

Powell et al. NeuroImage 2006.

Ghaderi et al., ISMRM 2012

Tract delineation techniques •  define tract delineating

ROIs manually with well-defined protocol (e.g., Mori et al., 2005; Wakana et al., 2007, Catani et al., 2008)

•  define tract delineating ROIs using fMRI activations (e.g., Powell et al., 2006; Ghaderi et al., ISMRM 2012)

•  define tract delineating ROIs automatically (e.g., using population atlas - Rose et al. 2010)

Rose et al. Brain Connectivity 2011.

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

Assaf et al, 2011

Tractometry

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

Luck et al, NIMG 2010

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

Tract Asymmetry Index (AI): AI = (C - I) / (C + I)

Rose et al., Brain Connectivity 2011

What is tractography useful for? Connectomics

Bastiani et al., NIMG 2012

Network properties: •  small worldedness •  network efficiency •  hub location

•  3D visualization aid: localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy Johansen-Berg et al., Nature 2003.

Thalamic segmentation

What is tractography useful for? •  3D visualization aid:

localization, education, investigation

•  tool to determine region in which to analyze scalar maps

•  tool to investigate tract-specific properties, e.g., tract length, tract count, tract asymmetry, network properties

•  segmentation of neuroanatomical structures based on connectivity

•  investigation of fiber anatomy

Schmamann et al. Brain 2007.

Applications: Epilepsy

Yogarajah et al. NeuroImage 2008.

Findings:

  decreased left intratract FA in L TLE

  22% reduction in left tract volume in L TLE

Applications: Multiple Sclerosis

Stikov et al, ISMRM 2013

•  scalar maps from diffusion imaging •  connectivity analysis •  complex subvoxel fiber microstructure •  diffusion contrast for functional imaging?

Diffusion Tensor Imaging II: Techniques and applications

Probability of water displacement orientation distribution function (ODF)

Probability of water displacement orientation distribution function (ODF)

Diffusion tensor model

High Angular Resolution Diffusion Imaging (HARDI)

QBI DTI

High Angular Resolution Diffusion Imaging (HARDI)

Crossing fiber reconstruction approaches •  multi-tensor approaches (Alexander et al., Parker et al.,

others)

•  Mixture models (Gaussian (Tuch et al.); Wishart (Jian et

al.))

•  ball and multi-stick (Behrens et al.)

•  diffusion spectrum imaging (DSI) (Wedeen et al.)

•  q-ball imaging (QBI) (Tuch et al.)

•  Composite hindered and restricted model of diffusion (CHARMED) (Assaf et al.)

•  spherical deconvolution (Tournier et al., •  Anderson, others) •  other variants…

Multi-tensor model

Hosey et al. 2008

Tuch et al. 2002

Behrens’ ball and stick model

Behrens et al. 2007

Diffusion weighted MRI sequence TE

G

90° 180° echo

G

ΔδΔ

δ b = ! 2G2" 2 (# $" / 3)

•  b value indicates the magnitude of the diffusion weighting:

q=γGδ

Diffusion Spectrum Imaging (DSI)

3D diffusion pdf

2D diffusion Orientation Distribution Function

(ODF)

Wedeen et al. ; Canales-Rodrigue et al.

q-ball imaging

Tuch et al. MRM 2004

•  direct calculation of the 2D diffusion ODF

•  calculation uses Funk-Radon transform

Composite hindered and restricted model of diffusion

(CHARMED)

restricted compartment

Crossing fiber detection: QBI vs. Deconvolution

QBI diffusion ODF Deconvolved fiber ODF

Tournier et al. NIMG 2008.

Savadjiev et al. NeuroImage 2008.

Beyond crossing: other complex subvoxel geometries

Curve Inference to distinguish fanning from bending fibers

subvoxel fanning of fibers

Campbell et al. ISMRM 2011.

Savadjiev et al. NeuroImage 2008.

Beyond crossing: other complex subvoxel geometries

Tractography: warnings •  Diffusion MRI tractography results include many false

positives and false negatives: priors are essential. –  Tractography is good for segmentation of parts of pathways, but

segmenting the entire pathway can be challenging (false negatives). –  Characterizing unknown new anatomy is much more difficult than

studying known anatomy (false positives). –  Example: Thomas et al. (Brain, 2005) report increase in fiber count

in corticobulbar tract on unaffected hemisphere in cerebral palsy: is this due to reorganization, or is this tract easier to trace due to the absence of callosal inputs from the affected hemisphere?

•  Tractography does not distinguish between afferent and efferent pathways, or between mono- and multisynaptic connections.

Tractography: warnings •  Diffusion MRI tractography results include many false

positives and false negatives: priors are essential. –  Tractography is good for segmentation of parts of pathways, but

segmenting the entire pathway can be challenging (false negatives).

Tractography: warnings •  Diffusion MRI tractography results include many false

positives and false negatives: priors are essential. –  Tractography is good for segmentation of parts of pathways, but

segmenting the entire pathway can be challenging (false negatives). –  Characterizing unknown new anatomy is much more difficult than

studying known anatomy (false positives).

Frey et al. 2006

Diffusion imaging of tissue microstructure

•  intra-axonal: anisotropically restricted

•  extracellular: hindered (anisotropically in fiber bundles)

•  cell bodies: isotropically restricted

•  CSF: not restricted or hindered 10 µm

•  AxCaliber (Assaf et al.) •  CHARMED (Assaf et al.) •  ActiveAx (Alexander et al., Zhang et al.) •  NODDI (Zhang et al.) •  Jespersen model •  restriction spectrum imaging (White and

Dale) •  diffusion basis spectrum imaging (Wang et

al.)

Diffusion imaging of tissue microstructure

q-space analysis of diffusion MRI data

McNab et al. ISMRM 2012

AxCaliber Aboitiz et al. (1993)

Composite hindered and restricted model of diffusion

(CHARMED)

restricted pool fraction F fractional anisotropy FA

NODDI: Neurite orientation dispersion

and density imaging •  a model of cellular structure that allows for complex subvoxel

fiber geometry (splay, curvature) •  estimated parameters include

•  intra-axonal (anisotropically restricted) signal fraction •  extra-axonal (anisotropically hindered) signal fraction •  isotropic signal fraction (CSF)

Zhang et al. NeuroImage 2012

NODDI: Neurite orientation dispersion

and density imaging

Axon volume fraction (AVF)

Diffusion imaging of tissue microstructure

courtesy Nikola Stikov

g-ratio = d / D

= 1/ (1+ MVF / AVF)

d D

21 µm

Diffusion imaging of tissue microstructure

Axon volume fraction (AVF)

g-ratio

Diffusion imaging of tissue microstructure

•  scalar maps from diffusion imaging •  connectivity analysis •  complex subvoxel fiber microstructure •  diffusion contrast for functional imaging?

Diffusion Tensor Imaging II: Techniques and applications

normal tissue

Diffusion tensor imaging (DTI)

cellular swelling: • MD decreases

Diffusion tensor imaging (DTI)

Diffusion contrast for functional imaging?

Le Bihan et al. PNAS 2006

•  stroke •  MS •  cancer •  trauma •  dyslexia •  epilepsy •  schizophrenia •  drug effects

Applications of diffusion MRI

•  ALS •  dementia •  CJD •  cerebral palsy •  blindsight •  depression •  therapy outcome •  meditation

•  neuroanatomy •  development •  aging •  surgical planning •  surgical outcome •  plasticity •  phenotype

characterization

Software packages •  FSL FDT (FMRIB, Oxford) •  DTI Studio (Johns Hopkins) •  Camino (Manchester/London)

•  CINCH (Stanford)

•  Mrtrix (Brain Research Institute, Melbourne) •  ExploreDTI (Utrecht/Cardif)

•  Diffusion Toolkit / TrackVis (Massachusetts General Hospital)

•  BrainVISA (NeuroSpin et al.)

•  MedInria (Inria) •  DiPy •  Fiber Navigator •  more …