Introduction to FreeSurfer surfer.nmr.mgh.harvard

1. Introduction to FreeSurfersurfer.nmr.mgh.harvard.edu

2. Why FreeSurfer? • Anatomical analysis is not like functional analysis – it is completely stereotyped. • Registration to a template (e.g. MNI/Talairach) doesn’t account for individual anatomy. • Even if you don’t care about the anatomy, anatomical models allow functional analysis not otherwise possible.

3. Why not just register to an ROI Atlas? 12 DOF (Affine) ICBM Atlas

4. Problems with Affine (12 DOF) Registration Subject 2 aligned with Subject 1 (Subject 1’s Surface) Subject 1

5. Surface and Volume Analysis Cortical Reconstruction and Automatic Labeling Inflation and Functional Mapping Automatic Subcortical Gray Matter Labeling Surface-based Intersubject Alignment and Statistics Automatic Gyral White Matter Labeling Surface Flattening

6. Talk Outline Cortical (surface-based) Analysis. Volume Analysis.

7. Surface Reconstruction Overview • Input: T1-weighted (MPRAGE,SPGR) • Find white/gray surface • Find pial surface • “Find” = create mesh • Vertices, neighbors, triangles, coordinates • Accurately follows boundaries between tissue types • “Topologically Correct” • closed surface, no donut holes • no self-intersections • Generate surface-based cross-subject registration • Label cortical folding patterns • Subcortical Segmentation along the way

8. Surface Model • Mesh (“Finite Element”) • Vertex = point of triangles • Neighborhood • XYZ at each vertex • Triangles/Faces ~ 150,000 • Area, Distance • Curvature, Thickness • Moveable

9. Surfaces: White and Pial

10. Cortical Thickness pial surface • Distance between white and pial surfaces • One value per vertex white/gray surface lh.thickness, rh.thickness

11. A Surface-Based Coordinate System

12. Comparing Coordinate Systems and Brodmann Areas Cumulative histogram (red=surface, blue=nonlinear Talairach) Ratio of surface accuracy to volume accuracy

13. Superior Temporal Gyrus Automatic Surface Segmentation Precentral Gyrus Postcentral Gyrus Based on individual’s folding pattern

14. Inter-Subject Averaging Spherical Spherical Native GLM Subject 1 Surface-to- Surface Demographics Subject 2 Surface-to- Surface cf. Talairach mri_glmfit

15. Visualization Borrowed from (Halgren et al., 1999)

16. Automatic Cortical Parcellation Spherical Atlas based on Manual Parcellations (40 of them) Map to Individual Thru Spherical Reg Fine-tune based on individual anatomy Note: Similar methodology to volume labeling More in the Anatomical ROI talk

17. Talk Outline Cortical (surface-based) Analysis. Volume Analysis.

18. 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)!

19. Cortex Lateral Ventricle White Matter Thalamus Caudate Putamen Pallidum Amygdala Hippocampus Volumetric Segmentation (aseg) Not Shown: Nucleus Accumbens Cerebellum

20. 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

21. FreeSurfer Directory Tree Each data set has its own unique SubjectId (eg, bert) • Subject • Subject Name bert scripts surf label mri stats orig.mgz T1.mgz brain.mgz wm.mgz aseg.mgz recon-all –i file.dcm–subject bert –all

22. Other File Formats • Surface: Vertices, XYZ, neighbors (lh.white) • Curv: lh.curv, lh.sulc, lh.thickness • Annotation: lh.aparc.annot • Label: lh.pericalcarine.label • Unique to FreeSurfer • FreeSurfer can read/write: • NIFTI, Analyze, MINC • FreeSurfer can read: • DICOM, Siemens IMA, AFNI