Re: [Freesurfer] Contents of Freesurfer digest...

[David Kamson]

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Martin, thank you for these comments. These are extremely valuable!

Although my patients had tumors, these are cured (this is why I have so few of 
them…) and have no residual mass effect/deformity beyond biopsy tracks / small 
resection cavities. Thus far, I was able to get pretty accurate looking 
segmentations of deep nuclei on aseg. Segmentation issues were associated with 
the surface structures (e.g.  dura/falx being misclassified as gray or brain 
tissue adjacent to resection cavities are correctly classified as brain but 
GM/WM often misclassified).

I’m OK restricting the analysis to ventricular and deep GM volume, since what 
I’m trying to measure is marked atrophy of these structure after chemotherapy 
which I guess is in the range of 1-5%/year. The changes are mostly marked 
enough to enable a visual qualitative analysis, however, quantitative data 
would be clinically more helpful to clarify when, and how much change to expect 
after treatment.

Do you think increasing the number of time points analyzed (I have 4-6 scans 
per year for each patient) could eliminate the noise from head 
positioning/slicing as long as the volumetric trends remain consistent? Again, 
the data would be normalized per individual and I would not use absolute volume 
for any comparative analysis.

Thank you again. This message board is of incredible value!

Best regards,
David




--

Message: 1
Date: Wed, 09 Oct 2019 10:48:48 +0200
From: Martin Reuter 
mailto:mreu...@nmr.mgh.harvard.edu>>
Subject: Re: [Freesurfer] Questions re slice thickness, aseg and
longitudinal analysis
To: Freesurfer support list 
mailto:freesurfer@nmr.mgh.harvard.edu>>
Message-ID:
<7a4d059cb5cb42f390e03f523677a3362d17cb81.ca...@nmr.mgh.harvard.edu>
Content-Type: text/plain; charset="UTF-8"

Hi David,

I am not very optimistic:

5mm is too thick for FreeSurfer (recommendation is 1 up to 1.5). You
will certainly get something, but it can be very unreliable and
completely wrong. Especially longitudinally these thick slices will
induce large variance due to different head positioning (and different
slice angulations) in the scanner.

Furthermore, FreeSurfer does not take Gad-Enhanced images. Also it will
not work if tumor lesions are present.

About your questions:

1. Surfaces update the aseg, but if you are only interested in the
volumes, you can skip this expensive step (potentially at the cost of
slightly higher noise levels in your measurements).

2. I think not (see above). 5mm is too low.

3. Theoretically yes, but I have never tested if the scripts will do
it. You could run up to the aseg in the cross, then create base (up to
aseg) and then run the longs up to aseg. Not even sure you really need
the base aseg. You might be able to just run the initial base
registration step, obtain the transformations and median norm.mgz
image, could be sufficient for the long runs.

4. No. Gad images won't work.

Best, Martin


   External Email - Use Caution
Freesurfers,

First of all, I'd like to express my gratitude to the community for
the support that keeps researchers like myself afloat!


I have a unique set of oncology patients that I want to evaluate for
brain atrophy in a retrospective longitudinal analysis.
I was thinking about using Aseg.auto results to assess longitudinal
volume changes, but before I invest all the time I wanted to check
with the community whether this makes any sense at all:

The dataset that looks like this:
- 22 patients (no control dataset [yet])
- 10-25 MRIs per patient acquired over 2-8 years in relatively
uniform intervals
- Patients had most of their scans on the same scanner, but
scanners differed widely between patients
- All patients have axial T1 post gadolinium scans of 1x1x5mm
resolution (3D acquisition available in <10%)
- About 80% of scans have an axial pre-contrast T1 sequence
- All scans are skullstripped (third party algorithm)

I'm looking for crude changes, no subtleties; volumes of interest
are:
- Whole brain volume
- White matter volume
- Ventricular volume (mainly lateral ventricle)
- Subcortical gray matter volume (whole thalamus most importantly)

I ran a few test analyses and to my surprise I was able to generate
pretty acceptable surfaces, however, topology fixing took about 24H
per scan, and I feel aseg.auto contained all the volumetric data I
was really interested in.

My concrete questions are:
1) Does the full autorecon pipeline affect Aseg.auto? If there is no
benefit, I could reduce the per scan analysis time from 28 hours to
1-2 h.
2) Would this low-resolution dataset be accepted by reviewers if used
for Aseg? Should I do any quantitative validation beyond a visual
quality analysis of Aseg?
3) Can I perform a longitudinal analysis only for the Aseg results?
4) Is it OK to use T1-gad images for the 

[Freesurfer] Questions re slice thickness, aseg and longitudinal analysis

[David Kamson]

External Email - Use Caution

Freesurfers,


First of all, I'd like to express my gratitude to the community for the support 
that keeps researchers like myself afloat!



I have a unique set of oncology patients that I want to evaluate for brain 
atrophy in a retrospective longitudinal analysis.

I was thinking about using Aseg.auto results to assess longitudinal volume 
changes, but before I invest all the time I wanted to check with the community 
whether this makes any sense at all:


The dataset that looks like this:

- 22 patients (no control dataset [yet])

- 10-25 MRIs per patient acquired over 2-8 years in relatively uniform intervals

- Patients had most of their scans on the same scanner, but scanners differed 
widely between patients

- All patients have axial T1 post gadolinium scans of 1x1x5mm resolution (3D 
acquisition available in <10%)

- About 80% of scans have an axial pre-contrast T1 sequence

- All scans are skullstripped (third party algorithm)


I'm looking for crude changes, no subtleties; volumes of interest are:

- Whole brain volume

- White matter volume

- Ventricular volume (mainly lateral ventricle)

- Subcortical gray matter volume (whole thalamus most importantly)


I ran a few test analyses and to my surprise I was able to generate pretty 
acceptable surfaces, however, topology fixing took about 24H per scan, and I 
feel aseg.auto contained all the volumetric data I was really interested in.


My concrete questions are:

1) Does the full autorecon pipeline affect Aseg.auto? If there is no benefit, I 
could reduce the per scan analysis time from 28 hours to 1-2 h.

2) Would this low-resolution dataset be accepted by reviewers if used for Aseg? 
Should I do any quantitative validation beyond a visual quality analysis of 
Aseg?

3) Can I perform a longitudinal analysis only for the Aseg results?

4) Is it OK to use T1-gad images for the analysis?


I'd appreciate any input!


Best regards,

David O. Kamson, MD PhD

Neuro-oncology fellow

Johns Hopkins Hospital &

National Institutes of Health


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[Freesurfer] Custom brain segmentation to equal sized regions

[david . kamson]

Freesurfers,

Is there a way to segment each hemisphere to an identical number of equal
sized regions which are as close in size and location as possible to their
contralateral homotopic regions.
Eg. I’d like to segment the left hemisphere to regions with a 2 cm2
surface and do the same for the right in order to compare asymmetries in
these small regions. Anybody had done this before?

David

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[Freesurfer] Data visualization

[david . kamson]

Hi FreeSurfers,

I have a question regarding data visualization:
Instead of  presenting population average cortical thickness overlay of
the right hemisphere on the  right and of the  left hemisphere on the
left,
I’d like to show thickness data from epileptogenic hemisphere on one side
(let’s say left) and from the non-epileptogenic hemisphere on the other
(let’s say right).

I.e. I’d like to average population thickness data from mixed right and
left lobes to visualize study findings in epileptogenic vs.
non-epileptogenic hemispheres.
Is there a neat way to accomplish this?


Sincerely,

David Olayinka Kamson, MD, PhD

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[Freesurfer] Age verification

[david . kamson]

What is the youngest age group the present freesurfer templare has been
validated for?
I’d appreciate (and quote) relevant paper suggestions.

Thanks,
David

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