[Brains-users] SURFACES FAQ

[Hans Johnson]

http://www.psychiatry.uiowa.edu/wiki/index.php?title=BRAINS_FAQ


Surfaces
PROBLEM: (This question is from Ameet R. Upadhyaya, M.D. about our surface
measures)
   I had a question regarding the surface data that one can obtain for
generated surfaces 
   through the BRAINS2 software.  I was wondering how valid the data is that
is generated?  
   I have heard rumors from former attendees of the BRAINS2 workshop that
the surface generation
   is just for making "pretty pictures" but the data itself may be highly
faulty.  Any input that
   either you or your colleagues can provide would be most helpful.  Thanks
ANSWER:(Greg Harris provided this answer)
Our continuous tissue-classified image gives a reliable index of sub-voxel
tissue composition on a scale from 100% cerebro-spinal fluid through gray
matter to 100% white matter. This image is normalized with respect to
variations among T1, T2 and PD image acquisitions, even across scanners.
The key information for finding meaningful surfaces is the construction of
parametric iso-surfaces through the tissue-classified image, which we do
with GTS. Our iso-surface through all the 100% gray matter sub-voxel
positions gives us a surface that is always anatomically well-defined as to
separation of adjacent gyri, which solves an important problem with previous
thresholding methods. Working with 1 mm voxels, the gray matter manifold
surface is smooth, even "pretty"; but it is not anatomically false.
We estimate the cortical thickness at every GTS vertex in the gray matter
manifold by finding the closest point on another manifold representing 50%
gray matter, 50% white matter, and storing the thickness at the vertex as
the Euclidean distance to that point. It is important to remember that the
distance from 100% gray to 50% gray represents half the cortical thickness.
Measurement of an ROI or mask thickness (or "depth") gives you the mean and
standard deviation of these numbers, weighted by the area accounted for by
the "fan" of triangles arranged around each vertex.
Although the numbers obtained do not exactly equal those obtained on
post-mortem cryo-sections by holding up a ruler to the tissue after dividing
by 2, brains2 depth measures provide an accurate index that is stable across
similarly obtained MRI scans. Depth, area, and gray matter volume measures
from this brains2 workup process are meaningful scientific measures of the
cortical anatomy represented by the gray matter manifold enclosed by an ROI
or mask.
As to curvature measures, we only use them to separate sulci from gyri, and
as an accurate index of tightness of curvature of sulci or gyri. We have
used the standard curvature measure of Meyer, Desbrun, Schroeder and Barr,
that is used in FreeSurfer as well, but for our purpose of measuring
cortical sulci we have filtered the indentation-protrusion indexes, which
are negative for concavities and positive for convexities, to a convenient
index of the scale of human sulcal and gyral gross curvature, so as to
correctly pick out human sulci and gyri as connected regions. This, and only
this, aspect may be what deserves to be called "pretty pictures" because the
single-voxel-scale variations have been lost.