introduction to freesurfer
TRANSCRIPT
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Post Your Questions!
http://surfer.nmr.mgh.harvard.edu/cgi-bin/fsurfer/questions.cgi
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Why FreeSurfer?
• Anatomical analysis is not like functional analysis – it is completely stereotyped.
• Registration to a template (e.g. MNI/Talairach) does not account for individual anatomy.
• Even if you do not care about the anatomy, anatomical models allow functional analysis not otherwise possible.
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ICBM Atlas
12 DOF(Affine)
Why not just register to an ROI Atlas?
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Subject 1Subject 2 aligned with Subject 1
(Subject 1’s Surface)
Problems with Affine (12 DOF) Registration (you will get sick of this slide)
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Surface and Volume Analysis
Cortical Reconstructionand Automatic Labeling
Inflation and FunctionalMapping
Surface FlatteningSurface-based Inter-subjectAlignment and Statistics
Automatic SubcorticalGray Matter Labeling
Automatic Gyral White Matter Labeling
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Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
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Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
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Why Is a Model of the Cortical Surface Useful?
Local functional organization of cortex is largely 2-dimensional! Eg, functional mapping of primary visual areas:
From (Sereno et al, 1995, Science). Also, smooth along surface
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Flat Map of Monkey Visual Areas
D.J. Felleman and D.C. Van Essen, CC, 1991
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What Can One Do With A Surface Model?
left primary visual cortex right visual hemifield
desired shape of activity pattern required shape of stimulus
goal: use model to impose desired activity pattern on V1
Collaboration with Jon Polimeni and Larry Wald.
w=k log(z+a)
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Tangential Resolution Measured with Surface-based Analysis
Collaboration with Jon Polimeni and Larry Wald.
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Tangential Resolution Measured with Surface-based Analysis
Collaboration with Jon Polimeni and Larry Wald.
14Thanks to Larry Wald for this slide.
M-G-H
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Surfaces: White and Pial
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Inflation
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Inflated surface with cuts superior temporal
Metrically optimal flat map
calcarine
central
sylvian
anterior
posterior
Surface Flattening – Whole Hemisphere
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Surface Model
• Mesh of triangles gives a measurable size
• Allows us to measure Area, Curv., Thickness (distance b/w vertices)
• Vertex = point of 6 triangles
• Triangles/Faces ~ 150,000 per hemi
• 1:1 correspondence of vertices
• XYZ at each vertex
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Cortical Thickness
white/gray surface
pial surface
lh.thickness, rh.thickness
• Distance between white and pial surfaces
• One value per vertex
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A Surface-Based Coordinate System
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Comparing Coordinate Systems and Brodmann Areas
Cumulative histogram (red=surface,
blue=nonlinear Talairach)
Ratio of surface accuracy to volume accuracy
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Automatic Surface SegmentationPrecentral
Gyrus Postcentral Gyrus
Superior Temporal GyrusBased on individual’s folding pattern
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Inter-Subject AveragingS
ubje
ct 1
Sub
ject
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Native Spherical Spherical
Surface-to- Surface
Surface-to- Surface
GLM
Demographics
mri_glmfit cf. Talairach
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Borrowed from (Halgren et al., 1999)
Visualization
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Rosas et al., 2002
Kuperberg et al., 2003
Gold et al., 2005
Rauch et al., 2004Salat et al., 2004
Fischl et al., 2000
Sailer et al., 2003
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Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
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Volume Analysis: Automatic Individualized Segmentation
• Surface-based coordinate system/registration appropriate for cortex but not for thalamus, ventricular system, basal ganglia, etc…
• Anatomy is extremely variable – measuring the variance and accounting for it is critical (more in the individual subject talk)!
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Volumetric Segmentation (aseg)
Caudate
Pallidum
Putamen
Amygdala
Hippocampus
Lateral Ventricle
Thalamus
White Matter
Cortex
Not Shown:Nucleus AccumbensCerebellum
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Volume Differences Predictive of AD
LH RH0
0.5
1
1.5
2
2.5
blue=ctrl (25), cyan=questbl (71), y=converters (21), red=AD (17)
late
ral-v
entr
icle
vol
ume
(pct
bra
in)
Data courtesy of Drs Marilyn Albert and Ron Killiany
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Combined Segmentation
aparc+aseg
aseg
aparc
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Gyral White Matter Segmentation
Nearest Cortical Labelto point in White Matter
wmparc
+ +
aparc
aparc+aseg
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Summary• Why Surface-based Analysis?
– Function has surface-based organization– Visualization: Inflation/Flattening– Cortical Morphometric Measures– Inter-subject registration
• Automatically generated ROI tuned to each subject individually
Use FreeSurfer Be Happy
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MGHBruce Fischl
Allison StevensNick Schmansky
Andre van der KouweDoug GreveDavid Salat
Evelina BusaLilla Zöllei
Koen Van LeemputSita KakunooriRuopeng Wang
Rudolph Pienaar Krish Subramaniam
Diana Rosas
Acknowledgements
UC San DiegoAnders Dale
MITPolina Golland
B. T. Thomas YeoMert Sabuncu
Florent SegonnePeng Yu
Ramesh Sridharan
MGHJean Augustinack
Martin ReuterAnastasia Yendiki
Jon PolimeniKristen Huber
UCLMarty Sereno
NINDS
MGH (past)Brian T Quinn
Xiao HanNiranjini Rajendran
Jenni Pacheco
Sylvester CzannerGheorghe Postelnicu
Sean Marrett