Trattografia probabilistica e fMRI nella pianificazione - - PowerPoint PPT Presentation

Trattografia probabilistica e fMRI nella pianificazione neurochirurgica

Domenico Lizio

SC Fisica Sanitaria, ASST Ospedale Niguarda, Milano

domenico.lizio@ospedaleniguarda.it

Basic Anatomy

The brain is full of

• neurons. These are
• rganised into two

types of “tissues”:

• Grey Matter (GM)
• White Matter (WM)

MRI Post-Mortem Grey Matter White Matter

Neurons are densely connected and have many dendrites Axons conduct electrical signals and are surrounded by myelin Myelin is a major factor in determining the MR signal and contrast

Basic Anatomy

Applications

• f MRI in

Neuroimaging

fMRI: finger-tapp. mano dx

Functional MRI

Mean diffusivity (MD) Fractional anisotropy (FA) Principal diffusion direction (PDD)

Diffusion MRI Structural MRI

T1-weighted T2-weighted Proton Density

Structural MRI

• Study of taxi drivers showing structural plasticity

Applications of MRI in Neuroimaging

Maguire et al.,PNAS, 2000

• Asperger Syndrome

Diffusion MRI

• White matter integrity - imaging tissue nature change
• Differences in brain connectivity in multiple tracts

Green = white matter tract ; Red/Yellow = statistically significant change in FA

Roine et al., Molecular Autism, 2015

• Parkinson’s Disease

Menke et al., Brain 2013

Look at tracts connected to regions

• f structural change

Diffusion MRI Structural MRI

• Stroke Therapy

Johansen-Berg, et al., Brain 2002

Functional MRI (Task)

Group: Correlations with improvement Single subject: responder

Functional MRI (Resting)

• Altered functional connectivity

• Surgical planning

Diffusion MRI Functional MRI (Task)

Bartsch et al., JMRI 2006

Structural MRI

Functional MRI

• Measures haemodynamic response to neural activity
• Task-based or resting-state-connectivity
• Intrinsic contrast BOLD (Blood Oxygen Level Dependent)
• Take many fast images (EPI): 5-30 min scan

Magnetic field perturbed Dephasing of nearby spins Loss of signal

BOLD Effect

• Oxy-haemoglobin

Diamagnetic (same as tissue)

• Deoxy-haemoglobin

Paramagnetic Δχ≈0.2 ppm

Magnetic field less perturbed Less dephasing More signal

BOLD Effect

Increased Neuronal Activity

CMRO2 CBV CBf

Analysis of Functional MRI

Task FMRI Resting-State fMRI & Connectivity

Images - Low Resolution FMRI

• A sequence of low resolution T2*-weighted volumes are

taken during the FMRI experiment

• Optimised for BOLD sensitivity and speed
• Take one volume every 1-3 seconds
• Often take around 200 volumes (10 minutes)
• An fMRI volume is shown here in orthogonal view

Functional MRI Artefacts

Distortion Signal Loss Physiological Noise

Hardware-related Physiological

... plus most diffusion artefacts (not eddy currents) and all structural artefacts

• Distortion due to B0 inhomogeneity (air in sinuses) -

acquisition-and-analysis related fixes needed (fieldmap)

• Physiological noise is more problematic near the brainstem -

acquire physiological measurements & do analysis fix

• Motion can also be a significant problem (some analysis fixes)

Functional MRI ‘‘Limitations’’

• Does not measure electrical activity
• Does not measure metabolic activity
• BOLD-FMRI is qualitative
• Sensitive to fast imaging artefacts
• Need good T2* sensitivity
• causes lost signal in inferior regions

Functional MRI Acquisition

Basic tips for acquisition

• Use optimised sequences/protocol for your scanner/site
• Get fieldmap (B0) for compensating distortion/signal-loss -

blip-up-blip-down is not an option for functional MRI

• For inferior-frontal/temporal areas apply acquisition

techniques to minimise signal loss - e.g. thin slices, slice angulation, z-shims, parallel imaging, ...

• Isotropic voxels (or close) are better for analysis generally
• For small FOV also take one single whole-brain EPI
• Biggest interaction of exp. design-acquisition-analysis so

think carefully about all parts before acquiring data!

Diffusion MRI

• Measures microstructure directionality and “integrity”,

particularly in WM

• Provides information on anatomical connectivity
• Need to acquire many “directions”: 5-30 min scan

• Random motion of particles due to thermal energy
• Water molecules collide and experience net displacement
• Displacement described by diffusion coefficient (D)
• Normally, diffusion is isotropic (equal in all directions)

What is diffusion?

• Diffusion is restricted by tissue boundaries, membranes, etc
• Marker for tissue microstructure (healthy and pathology)

Why is diffusion interesting?

Water can diffuse more freely along white matter fibres than across them

Diffusion anisotropy in white matter

Diffusion anisotropy in white matter

Diffusion in white matter fibres is “anisotropic” Directionality of diffusion tells us about fibre integrity/structure and orientation

Displacement due to diffusion is approximately ellipsoidal Eigenvectors = axes of ellipsoid (direction of fibres) Eigenvalues = size of axes (strength of diffusion)

The diffusion tensor

Principal diffusion direction (PDD): what direction is greatest diffusion along? Info about fibre orientation Fractional anisotropy (FA): how elongated is the ellipsoid? Info about fibre integrity The diffusion tensor: Useful quantities Mean diffusivity (MD) Info about tissue integrity

The diffusion tensor: Useful quantities

Mean diffusivity (MD) Fractional anisotropy (FA) Principal diffusion direction (PDD)

Diffusion tensor imaging

At each voxel, fit the diffusion tensor model Can then calculate MD, FA, PDD from fitted parameters

Mean diffusivity (MD)

Control MD Acute Stroke

Mean diffusion coefficient across all directions Correlate of tissue integrity (white and gray matter) Example: MD is altered in acute and chronic stroke

Inequality of diffusion coefficient across different directions High in regions where diffusion is most directional Relates to integrity of white matter fibre bundles

Fractional Anisotropy (FA)

Principal diffusion direction (PDD)

Direction along which greatest diffusion occurs Relates to direction of fibre orientations Typically, will use this as starting point for fibre tracking

Diffusion tractography

Follow PDD to trace white matter fibers (“tractography”)

More complicated models: Crossing fiber populations

Diffusion tractography: Determionistic vs Probabilistic

• Deterministic assumes a single orientation at each voxel: one

streamline per seed voxel.

• Probabilistic assumes a distribution of orientations: multiple streamline

samples per seed voxel (drawn from probability distribution)

If diffusion is present, gradients cause a drop in signal. Greater Diffusion = Less Signal

Acquiring the image

Diffusion MRI Artefacts

Eddy Currents Hardware-related

+ Bulk/Pulsatile Motion … plus all the structural artefacts

• Eddy currents: both acquisition and analysis fixes available
• Distortion due to B0 inhomogeneity (air in sinuses)- acquisition-

and-analysis related fixes needed

• Bulk motion is corrected for in acquisition (navigators)
• Pulsatile motion is more problematic

Diffusion gradients encode tiny displacement Subject motion is also accidentally encoded Image artefacts if we try to combine data from multiple excitations (different motion)

Motion in Diffusion MRI

Linescan diffusion image

Can motion be avoided?

Subject restraints can reduce bulk motion, but... ...in the brain, there is significant non-rigid motion from cardiac pulsatility cardiac gating helps, but brain is never very still!

Single-shot echo-planar imaging (EPI)

Single-shot imaging freezes motion Most common method is echo-planar imaging (EPI) Images have serious distortion and limited resolution

Eddy Currents

Diffusion gradients create large eddy currents, which persist into acquisition window Distort the k-space trajectory, casing shears/scaling of images Eddy currents “resist” gradient field changes effective gradient fields

Diffusion MRI “Limitations”

• Does not measure axon size/density directly
• Does not measure single fibres (only average groups)
• More difficult to deal with crossing/kissing fibres
• Quantitative local measurements, but not

connectivity

• More difficult to do in pulsatile regions (e.g.

brainstem)

• More restricted by hardware and SNR
• Sensitive to fast imaging artefacts

Diffusion MRI: Acquisition

Basic tips for acquisition

• Best parameters can be quite hardware dependent (esp.

gradients) so check what is optimised for your scanner

• In general, b-value of 1000-1500 s/mm2 and 60+ directions

(tractography) or 12+ directions (FA, etc.) tend to give good results (but the more directions the better)

• Get one b=0 image for every 8-10 diffusion-weighted images
• Get a fieldmap (B0) for distortion correction - or alternatively, a

blip-up-blip-down

• Isotropic voxels (or close) are better for analysis generally
• Do not do oversampling on scanner (sometimes the default)
• Both single/multi-shell give good tractography

Parameter Value Relevant points

TE (Echo Time) 100 ms Limited by b-value Matrix size /Resolution 128x128 / 2 mm Limited by distortion, SNR Number of directions 6-60 Lower limit: tensor model Upper limit: scan stime b-value 1000 s/mm2 Larger b = more contrast Smaller b = more signal

Typical Diffusion Imaging Parameters

Diffusion MRI: Analysis

Basic stages in the diffusion analysis pipeline: Eddy Current & Motion Correction Fibre/ direction modelling Probalistic Tractography ‘‘Tensor’’ Fitting e.g. FA, MD

Behrens T .E.J. et al. NeuroImage, 2006 www.fmrib.ox.ac.uk/fsl

FSL tractography pipeline

Case Studies

Clinic: patient suffering from focal epilepsy with multiple daily motor seizures prevalent in the right upper limb. Diagnosis: clearly visible focal cortical dysplasia with FLAIR sequences contiguous to the primary motor region of the hand in the ascending frontal convolution. --> SEEG Pre-surgical question: CST and ThC sn fibre reconstruction in the hand component..

Case Study No. 1: Motor-sensitive system

FLAIR T1W-3D SEEG

P6 - CST mano (ST+MEP) I2 - CST piede (ST+MEP) P1 - ThC mano (SEP) Q5 - ThC piede (SEP)

SEED CST: peduncle cerebral sx

(identified by DTI colormap)

SEED ThC: nVPL sx

(identified with connectivity- based seed classification)

WAYPOINTs: M1 - S1 hand (GM), exact points of the CST and ThC hand beams (WM) WAYPOINTS functional by SEEG information

Case Study No. 1: Motor-sensitive system

CST hand (RED) - CST foot (ORANGE) ThC hand (BLUE) - ThC foot (BLUE)

Case Study No. 1: Motor-sensitive system

Clinic: patient suffering from partial epilepsy with multiple daily motor seizures with prevalent involvement of the right shoulder. Diagnosis: clearly visible focal cortical dysplasia with FLAIR sequences contiguous to the primary motor region of the hand in the ascending frontal convolution. Pre-surgical question: identification of cortical areas and corresponding fibres responsible for the primary motor and sensitive functions of the contralateral hand.

T1W-3D FLAIR

Case Study No. 2: Motor-sensitive system

fMRI: finger-tapp. Right hand SEED CST: peduncle Cerebral sx

(identified by DTI colormap)

WAYPOINTs SEED ThC: nVPL sn

(identified with connectivity- based seed classification)

Case Study No. 2: Motor-sensitive system

SEEG planning (subsequent to FT) Case Study No. 2: Motor-sensitive system

Clinic: patient suffering from partial focal epilepsy with suspected left temporo-occipital ZE. Diagnostics: Negative MRI. --> SEEG Pre-surgical question: fibre tracking Radiation Optics sx.

Case Study No. 3: Visual System

FLAIR SEEG

V4 - OR sup (ST+VEP) V4 - OR sup (ST+VEP) V4 - OR sup (ST+VEP) F8-9 - OR sup (wm VEP)

WAYPOINTs OR sup:

• cont. V4 (gm)
• cont. F8-9 (wm)

SEED OR:

lGNB sx

O2 - OR inf (ST+VEP) O2 - OR inf (ST+VEP) O2 - OR inf (ST+VEP) E8 - OR inf (wm VEP)

WAYPOINTs OR inf:

• cont. O2 (gm)
• cont. E8 (wm)

WAYPOINTs: V1 over and undercalcium (GM), certain points along OR (WM)

Case Study No. 3: Visual System

Case Study No. 3: Visual System

Injury in the Seed region used for the reconstruction of the CST fasciculus.

Case Study No. 4:

Patient with Meningioma of the Tentory in the region of the cerebellar pedicle in the study for SRS with GK

Co-registered fasciculus with AX_Helmet

• Red-Yellow: CST Hand
• Blue-Blue: CST Foot

(overlap near the lesion)

Elaborazione per Trattamento in GK

Plan Plan1 Target Meningioma Total Treatment Time [min] 52.0 Prescription Isodose [%] 50 Prescription dose [Gy] 6.5 Maximum dose [Gy] 13.0 Average dose[Gy] 8.9 Minimum dose [Gy] 5.4 Number of shots 38(1) Gamma angle 90 TV - Target Volume [cm³] 3.884 Intersection TVÇPIV [cm³] 3.754 PIV50 - 50% Prescription Isodose Volume [cm³] corresponding to half of Prescription Dose 11.568 PIV - Volume [cm³] of the Prescription Isodose 4.185 Conformity Index - TVÇPIV/TV 0.97 Selectivity index - TVÇPIV/PIV 0.90 Gradient index - PIVh/PIV 2.76 Paddick Index: Conformity x Selectivity 0.867

Processing for GK treatment

• The diffusion tensor imaging (DTI) enables to investigate

cerebral white matter integrity non-invasively.

• The use of the probabilistic tractography method and

functional magnetic resonance imaging for the planning of the pre-surgical study is very useful. The main limitations of FT-DTI are:

• 1. reliability of the reconstructions following the brain-

shift

• 2. probability threshold to be used.

The main limitations of fMRI are: Design of experiment Requires adequate task performance Accurate and reproducible fMRI strongly depends on the patient’s cooperation

Conclusion

Acknowledgements

Team

• Dr. Luca Berta
• Dr. Paola Colombo
• Dr. Marco Felisi
• Dr. Stefania Nici
• Dr. Alberto Torresin