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

On Mon, Oct 27, 2014 at 9:59 AM, Lars M. Rimol larilin@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

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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

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