Question regarding the LIT output

[jaspermaes123]

We ran LIT on our data with the following command: ./run_lit_containerized.sh --mask_image path_to_mask --input_image path_to_input --output_directory path_to_output --fastsurfer

We were wondering if the volumes obtained in the aseg+DKT.stats file already take into account the lesion? I mean that the regions that are within the lesion or partly overlap are labeled as lesion and are not used for the volume calculation?

Thank you!

[ClePol]

Dear Jasper,

the --fastsurfer flag is only a temporary (undocumented) option to run FastSurfer after the lesion inpainting and to place the lesion mask in some segmentations and surfaces (essentially everything until the last step below). This will likely be removed in future versions, when LIT will be fully integrated with FastSurfer. We recommend to run:

./run_lit_containerized.sh --mask_image path_to_mask --input_image path_to_input --output_directory /path/to/output
./run_fastsurfer_container.sh --t1 /path/to/output/inpainting_volumes/inpainting_result.nii.gz --output /path/to/output

The run_fastsurfer_container.sh is located at https://gist.github.com/ClePol/cdbbca94df4cc84cc1fb373b4ba8b40d, or you can run the FastSurfer docker according to the FastSurfer documentation.
Then you'd have to transfer the lesion label manually and recalculate the stats files:

# calculates aseg+DKT.stats including lesion volume
# for output diectorty: /path/to/output
SUBJECTS_DIR=/path/to/
SID=output

docker run -u $(id -u):$(id -g) --rm -v "$SUBJECTS_DIR/$SID/:/fastsurfer_output/" --entrypoint "/bin/bash" deepmi/lit:0.5.0 -c \
        "python3 /inpainting/postprocessing/lesion_to_segmentation.py \
            -i '/fastsurfer_output/mri/aparc.DKTatlas+aseg.deep.mgz' \
            -m '/fastsurfer_output/inpainting_volumes/inpainting_mask.nii.gz' \
            -o '/fastsurfer_output/mri/aparc.DKTatlas+aseg+lesion.deep.mgz'"
docker run -u $(id -u):$(id -g) --rm -v "$SUBJECTS_DIR/$SID/:/fastsurfer_output/" --entrypoint "/bin/bash" deepmi/fastsurfer:cpu-v2.4.2 -c \
        "python3.10 -s /fastsurfer/FastSurferCNN/segstats.py \
            --segfile /fastsurfer_output/mri/aparc.DKTatlas+aseg+lesion.deep.mgz \
            --segstatsfile /fastsurfer_output/stats/aseg+DKT+lesion.stats \
            --normfile /fastsurfer_output/mri/orig_nu.mgz \
            --threads 1 --empty --excludeid 0 --sd /fastsurfer_output --sid $SID \
            --ids 2 4 5 7 8 10 11 12 13 14 15 16 17 18 24 26 28 31 41 43 44 46 47 49 50 51 52 53 54 58 60 63 77 99 251 252 253 254 255 1002 1003 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1034 1035 2002 2003 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2034 2035 \
            --lut /fastsurfer/FastSurferCNN/config/FreeSurferColorLUT.txt measures \
            --compute Mask\(/fastsurfer_output/mri/mask.mgz\) BrainSeg BrainSegNotVent SupraTentorial SupraTentorialNotVent SubCortGray rhCerebralWhiteMatter lhCerebralWhiteMatter CerebralWhiteMatter"

Note that this will also include regions that overlap or are adjacent to the lesion - I will look into excluding those regions in the FastSurfer integration which is currently in developement.
Hope this helps!

[jaspermaes123]

Thank you, that helps a lot!