Pediatric: if the time distance is small it should also work in paediatric images. You can just test it on a couple cases and if too many edits would be required, then simply use the cross sectional processed results.

There is no thorough analysis, but missingness is not a big problem if you use Linear Mixed Effects Modeling. You can even include subjects with a single time point (but make sure you run it also through the longitudinal stream so that that single image undergoes the same processing steps as the rest).

On 9. Jul 2018, at 15:50, Mohn, Johannes <mohn@mpib-berlin.mpg.de> wrote:

Dear FS Experts and Community,

we are working on a longitudinal dataset of structural T1w images in a pediatric sample assessed at 2 waves, 2 years apart (aged 6/7 and 8/9).
As far as we know, it is yet unresolved whether the Freesurfer longitudinal pipeline is robust in pediatric samples, where the head size is still changing or have there been any recent developments?
Also, is there any documentation on how missingness affects this Pipeline?

We look forward to your response

Thank you,

Laurel and Johannes

Jacobs Entwicklungsstudie

Max-Planck-Institut für Bildungsforschung
Max Planck Institute for Human Development
Lentzeallee 94
14195 Berlin

Tel.: 030-824 06 371
E-Mail: jacobs-studie@mpib-berlin.mpg.de

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