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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Lars M. Rimol, PhD
Norwegian University of Science and Technology (NTNU)
Trondheim,
Norway
On Mon, Oct 27, 2014 at 9:59 AM, Lars M. Rimol <lari...@gmail.com>
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
(attached p-maps:
lh_0-1000_wmarea_s30_log10p_inflated_lateral.tif vs.
lh_0-1000_wmarea_s30_log10p_inflated_lateral.tif).
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 (attached file:
lh_diff_vo-v2_rawdata_lateral.tif shows timepoint1 -
timepoint2).
In addition, I ran an lme analysis with the same subjects and
found results very similar to those for the entire sample
(attached file: lh_2tp_01000_pmap_lateral.tif ).
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
---------------------------------------------------------------------------
---------------------------------------------------------------------------
---
Douglas N Greve Tue, 09 Sep 2014 08:24:37 -0700
This is tough to interpret, but basically, yes it would be
0-.004mm2/year. It is not quite right to say that it is at that
vertex
because of smoothing, but in that area. It is also hard to say
what the
total change would be for a cluster. One could sum the changes
over the
cluster vertices, but that would probably over-estimate the
change.
doug
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
_______________________________________________
yours,
Lars M. Rimol, PhD
Norwegian University of Science and Technology (NTNU)
Trondheim,
Norway
