Hi Lars,

two thoughts that came up reading this thread:
- each vertex has usually more than 3 triangles (your first mail), the number differs depending on where you are. With a uniform mesh you'd have nearly 60 degree angles so you'd have approx 6 triangles at a vertex.
- wm volume can increase when area shrinks. If especially the slucii move further outside the whole surface gets more spherical, decreasing area, but increasing volume.

Best, Martin

On 10/29/2014 08:44 AM, Bruce Fischl wrote:

Hi Lars

yes, it seems plausible, particularly since it is so universal.

cheers
Bruce

On Wed, 29 Oct 2014, Lars M. Rimol wrote:

Hi Bruce (and Jorge),

Yes, it's the wm surface.  I have also done the analyses with the pial
surface and the results are similar to wm surface.

To your second question: White matter volume increased over this time period
(lme analysis; controls: logP = 8.49, patients: logP =  6.34).

Since the cortical analyses were done using lme, which can handle missing
data, some of the subjects have only one time point. So I created a
difference map for
those subjects for whom we have data on both time points, to see if area on
the first time point is consistently larger than on the second time point.
Almost all subjects
showed larger values on tp1 than tp2 and the maps of average area change
(across subjects) confirm that.
In addition, I ran an lme analysis with the same subjects and found results
very similar to those for the entire sample.

Would you agree that this apparent reduction in cortical area seems
plausible? There is a reduction over time in raw data, and pial surface area
show the same trend as wm surface,
and the lme analysis with only subjects that have data on both time points
shows very similar results as the lme with all subjects.
On the other hand, I suppose we wouldn't expect increased wm volume together
with reduced area?

As for the effect size maps, I have worked on finding a way to represent
change in area over time that is intuitive for a reader not familiar with
FreeSurfer:
I figured one solution could be to log transform the dependent variable (wm
or pial area). This way the significance tests are done with log transformed
data and for purposes of illustration
I do exp(beta)*100-100 on the beta for time, which ensures that if there is
e.g. a 1% reduction, the figure shows -1, and 1 for a 1% increase. I find
this is a good way of demonstrating the
effects (attached figure:
lh_wmarea_logtransf_expBeta2_s30_inflated_lateral.tif ). What do you think?

I could of course also transform the dependent variable into percentages.
That is, baseline == 100 and tp2 expressed in percent of baseline. However,
I find this to be a less attractive solution because we basically lose the
baseline values, and this makes the model less useful for all other
purposes. For instance, we can't investigate group differences at the
various time points within the model. Perhaps more importantly, it's unclear
what assumptions we are making. The lme assumes a normal distribution and
it's unclear to me what the distribution of such ratios are.


Thank you!

LMR

yours,
Lars M. Rimol, PhD
Norwegian University of Science and Technology (NTNU)
Trondheim,
Norway



      Bruce Fischl Sat, 06 Sep 2014 07:00:14 -0700

Hi Lars

      which surface are you using? If it's the white surface you might
      try looking at white matter volume to see if it is decreasing

cheers
Bruce

On Sat, 6 Sep 2014, Lars M. Rimol wrote:

Hi,

I have performed a longitudinal analysis using the lme module in FreeSurfer,
with this model: 

intercept(random effect) + centered age + group + group x centered age + sex

I tested the effect of time with this contrast vector [ 0 1 0 0 0 ].
Dependent variable is  area.

Here, mapping the second beta means mapping the effect size for (change
over) time. In the beta map, I find values from 0 to 0.004.  I would
interpret that to mean that local area shrinks by at most 0.004 mm² per year
in the reference group. But I'm not 100% sure about the biological (or
geometrical) meaning of that.

Can I interpret this literally as the mean yearly shrinkage of the three
triangles surrounding a given vertex, the average of whose area comprises
the area score of the vertex, being 4/1000 mm? Of course, these maps are
smoothed with 30mm, so the real spatial resolution is nowhere near this....


Thank you!


--
yours,
Lars M. Rimol, PhD
St. Olavs Hospital
Trondheim,
Norway

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yours,
Lars M. Rimol, PhD
Norwegian University of Science and Technology (NTNU)
Trondheim,
Norway

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