Dear Asmin,

The discrepancies arise from differences in anatomical protocols. You can look at the definitions in the corresponding papers and keep the one that adapts better to your needs. The results should be fairly highly correlated.

Kind regards,

Eugenio

--

Juan Eugenio Iglesias

http://www.jeiglesias.com

From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Asmin Alam <asmin.alam23@gmail.com>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Monday, March 13, 2023 at 13:02
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] Hypothalamus segmentation using hypothalamic subunits vs ScLimbic

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Dear FreeSurfer Experts, 

I have a question regarding how the hypothalamus volumes are calculated using the hypothalamic subunits function, as opposed to the ScLimbic deep learning tool which is only currently available in the dev version of Freesurfer. 

My project consists of measuring the volume of the hypothalamus, so I thought of running both algorithms and comparing results to ensure they were consistent. However, they are quite different and I was wondering if there are certain flags/options I should be adding to ensure that the results will relate to each other and why that is the case. What is the key difference in how the hypothalamus is calculated by both these methods? How do I ensure my results are robust/trustworthy? What does noMB mean in the ScLimbic results?

I have tried running the ScLimbic function using the original T1 and the --conform flag to make sure that the voxels were isotropic, and then retried by using the nu.mgz as input  (as that's what the hypothalamus subunits function uses). 

Here are the results (also attached):

HYPOTHALAMIC SUBUNITS

subject	left anterior-inferior	left anterior-superior	left posterior	left tubular inferior	left tubular superior	right anterior-inferior	right anterior-superior	right posterior	right tubular inferior	right tubular superior	whole left	whole right
test	19.88	25.155	136.715	145.785	131.879	20.078	29.209	134.882	161.009	133.293	459.414	478.471

SC LIMBIC (T1-W and --conform)

# Subcortical Limbic Volumetric Stats

# Created by mri_sclimbic_seg

# NRows 12

# NTableCols 5

# ColHeaders Index SegId NVoxels Volume_mm3 StructName

1        26   469    471.6122    Left-Nucleus-Accumbens

2        58   460    459.8144    Right-Nucleus-Accumbens

3       819   588    571.3680    Left-HypoThal-noMB

4       820   631    586.4990    Right-HypoThal-noMB

5       821   667    707.3562    Left-Fornix

6       822   631    700.7991    Right-Fornix

7       843    58     60.5358    Left-MammillaryBody

8       844    57     64.1979    Right-MammillaryBody

9       865   414    396.2163    Left-Basal-Forebrain

10      866   448    450.1535    Right-Basal-Forebrain

11      869   165    170.6947    Left-SeptalNuc

12      870   151    157.4303    Right-SeptalNuc

SC LIMBIC (nu.mgz input)

# Subcortical Limbic Volumetric Stats

# Created by mri_sclimbic_seg

# NRows 12

# NTableCols 5

# ColHeaders Index SegId NVoxels Volume_mm3 StructName

1        26   513    519.7247    Left-Nucleus-Accumbens

2        58   526    537.3985    Right-Nucleus-Accumbens

3       819   575    570.7261    Left-HypoThal-noMB

4       820   613    604.3893    Right-HypoThal-noMB

5       821   657    675.3337    Left-Fornix

6       822   663    691.8721    Right-Fornix

7       843    51     53.4853    Left-MammillaryBody

8       844    58     61.4891    Right-MammillaryBody

9       865   473    483.7591    Left-Basal-Forebrain

10      866   487    496.4204    Right-Basal-Forebrain

11      869   145    153.3073    Left-SeptalNuc

12      870   138    142.8245    Right-SeptalNuc

I'm also not sure exactly what the flag "--crop" means for the hypothalamic subunits function. I left it to the default value of 184 but how will changing this affect my final result?

Below are also my codes for all three functions:

mri_segment_hypothalamic_subunits --s ${subjid} --sd ${sd} --crop 184

mri_sclimbic_seg --i ${sd}/${subjid}/mri//T1.mgz --o ${sd}/${subjid}/mri/sclimbic.mgz --write_volumes --conform 

mri_sclimbic_seg --i ${sd}/${subjid}/mri//nu.mgz --o ${sd}/${subjid}/mri/sclimbic.mgz --write_volumes 

Any help is appreciated. 

Thank you, 

Asmin

UCL Queen Square Institute of Neurology