# How can I compute/extract volume from specific portion of the Spinal Cord?

### Description

Hi!
I would like to compute (i.e. extract) volume from specific part of the spinal cord based on a binary mask. Here is what I am working with as an input:

And here is a mask based on which I want to compute volume:

My question is, is this possible to do this with SCT or do I need some external tool (if so, which one)?

Thanks!

Thank you for reaching out.

What do you mean by “from specific part of the spinal cord”? Did you mean at specific vertebral levels? Eg: your spinal cord segmentation mask would be divided into smaller chunks, and you would compute the volume of each chunk?

The simplest way to compute the volume from your mask is to do the following:

``````sct_analyze_lesion -m FILE_SEG -s FILE_SEG
``````

Which gives you something like this:

``````Averaged measures...
Volume [mm^3] = 5780.0+/-0.0
(S-I) Length [mm] = -14.77+/-0.0
Equivalent Diameter [mm] = 6.08+/-0.0

Total volume = 5780.0 mm^3
``````

It also outputs an XLS file.

Also see this related thread: Get spinal cord volume

Cheers

Well, I think this will work, but to clarify my answer. So, I have 3D T1 image of the brain with portion of the spinal cord. I am able to detect C2-C3 discs on it, but I also label specific portion of the spine myself.

Based on that segmentation, I want to compute volume in the region specified by the segmentation image.

I think that your answer gives me that, just not sure how will this compute voxel volume in the 3D T1 image I am starting with (picture 1 I presented), if I pass segmentation files (-m and -s) for parameters only?

Hi,

I’m sorry but I don’t understand exactly what you are trying to do. For example, would you like to compute the spinal cord volume at the vertebral level C2? (as opposed to in the whole spinal cord segmentation)

Yes, that’s exactly right.

OK, so the easiest way to do it is via the `sct_process_segmentation` function, which computes the CSA across specified slices, and also the length along the spinal cord axis. So the volume is obtained by multiplying the CSA by the length, across the desired section.

For example, this command:

``````sct_process_segmentation -i t2_seg.nii.gz -vert 2:5 -vertfile t2_seg_labeled.nii.gz -perlevel 1
``````

Produces this output CSV file:

Timestamp SCT Version Filename Slice (I->S) VertLevel MEAN(area) STD(area) MEAN(angle_AP) STD(angle_AP) MEAN(angle_RL) STD(angle_RL) MEAN(diameter_AP) STD(diameter_AP) MEAN(diameter_RL) STD(diameter_RL) MEAN(eccentricity) STD(eccentricity) MEAN(orientation) STD(orientation) MEAN(solidity) STD(solidity) SUM(length)
2021-05-08 15:49:49 git-master-0e160998510b22bba054b783eb5fb02bad26bfd8 /Users/julien/sct_example_data/t2/t2_seg.nii.gz 123:142 5 70.4404020395912 3.165339525195910 1.0998381733640000 0.30803310573138400 11.159472817536400 0.7344994621451710 7.262288820889050 0.36952222511890100 12.485934023396700 0.3119704366560290 0.8110842295450590 0.02956961820477710 12.646025854995200 2.5255817424078500 0.9548061920833870 0.014867402258882200 16.313040876736400
2021-05-08 15:49:49 git-master-0e160998510b22bba054b783eb5fb02bad26bfd8 /Users/julien/sct_example_data/t2/t2_seg.nii.gz 143:164 4 75.28273913053960 1.831122923241610 1.7173171447440500 0.057093624422294900 11.879833730279900 0.3729248045994530 7.743264536291100 0.2451173130109210 12.378087789081900 0.26961910178519700 0.7787209170044820 0.024361284639158600 5.411266928681170 3.219113990898190 0.9644938668858960 0.012093599820291500 17.993721013739200
2021-05-08 15:49:49 git-master-0e160998510b22bba054b783eb5fb02bad26bfd8 /Users/julien/sct_example_data/t2/t2_seg.nii.gz 165:187 3 73.20349600691700 1.8235438192796300 1.2958122048452000 0.2921364138287500 8.529272398004250 1.568547458559680 7.9206579168289 0.18483796129947200 11.769555120942800 0.2840328280740710 0.738395988126062 0.022692478457855400 1.1219337088010900 0.875112677251581 0.9700775123035080 0.009623211434786300 18.618070488799600
2021-05-08 15:49:49 git-master-0e160998510b22bba054b783eb5fb02bad26bfd8 /Users/julien/sct_example_data/t2/t2_seg.nii.gz 188:206 2 74.69254399438870 2.199616050901140 -0.0934919956523575 0.49520090153859700 4.6772083171808300 0.45615364077585600 8.213377034419330 0.19546718308872300 11.525913909952300 0.09324897006695110 0.7012927666730590 0.014861024252918800 1.067714651009060 1.03883812533707 0.9783464998305020 0.008655405991361460 15.251867063005000

Now to get the volume per vertebral level, you can simply multiply column MEAN(area) by column SUM(length), which gives you this (some columns were removed for clarity):

Slice (I->S) VertLevel MEAN(area) SUM(length) Volume (mm^3)
123:142 5 70.4404020395912 16.313040876736400 1149.0971578456
143:164 4 75.28273913053960 17.993721013739200 1354.61660506504
165:187 3 73.20349600691700 18.618070488799600 1362.90784868334
188:206 2 74.69254399438870 15.251867063005000 1139.20075160007
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