Radiomic Feature
The lesion radiomic feature extraction pipeline utilizes PyRadiomics to extract lesion features from T1-weighted, T2-FLAIR, and T2*-EPI images.
Usage
The pipeline contains three stages: 1) Preprocessing: processes MRI images to prepare for radiomic feature extraction, 2) Feature Extraction: extract radiomic features using PyRadiomics package, and 3) Consolidation: consolidates all participants' lesion radiomic feature data.
This pipeline can be run with or without a container. For containerized usage, Singularity can be used on a cluster or Docker locally. This pipeline can be run in individual or batch mode, meaning you can specify a certain subject and session or run the pipeline for all subjects in the folder, respectively.
These examples will run the pipeline in batch mode on the cluster. To run individually or locally/with a container, set --mode individual, or -c local/-c singularity/-c docker, respectively.
Step 1. Processing
This step processes raw T1, T2-FLAIR, and T2*-EPI images to prepare for extraction of radiomic features. By default, it runs bias correction, registration to FLAIR space, WhiteStripe normalization, MIMoSA, CSF extraction, splitting confluent lesions, and registration to EPI space. Skullstripping can be turned on if input images contain non-brain tissue.
Required flags:
-m or --mainpath: path to parent data folder
-t or --t1: T1 sequence name
-f or --flair: FLAIR sequence name
-e or --epi: EPI sequence name
--toolpath: path to pipeline folder
Other flags:
-p or --participant: participant ID (only needed for individual mode)
--ses: session ID (only needed for individual mode)
-n or --n4: run N4 bias correction. Default is TRUE
-s or --skullstripping: run skullstripping. Default is FALSE
-r or --registration: run registration. Default is TRUE
-w or --whitestripe: run WhiteStripe normalization. Default is TRUE
--mimosa: run MIMoSA segmentation. Default is TRUE
--threshold: threshold for generating MIMoSA mask. Default is 0.2
--csf: extract CSF mask. Default is TRUE
--step: step of pipeline - processing, extraction, consolidation. Default is processing
--mode: run pipeline individually or batch. Default is batch
-c or --container: which container to use: singularity, docker, local, cluster. Default is cluster
--sinpath: path to singularity image (only needed if using singularity container - don't need to specify if using takim cluster)
--dockerpath: path to docker image (only needed if using docker container)
-h or --help: show help message
bash /path/to/PennSIVE_neuro_pip/pipelines/radiomic_feature/code/bash/pyradiomics.sh -m /path/to/project -t "*_T1w.nii.gz" -f "*_FLAIR.nii.gz" -e "*_T2star.nii.gz" --toolpath /path/to/PennSIVE_neuro_pip
Step 2. Feature Extraction
This step extracts radiomic features.
Required flags:
-m or --mainpath: path to parent data folder
--step: step of pipeline - processing, extraction, consolidation. Default is preparation. This step is extraction
--toolpath: path to pipeline folder
Other flags:
-p or --participant: participant ID (only needed for individual mode)
--ses: session ID (only needed for individual mode)
--mode: run pipeline individually or batch. Default is batch
-c or --container: which container to use: singularity, docker, local, cluster. Default is cluster
--sinpath: path to singularity image (only needed if using singularity container - don't need to specify if using takim cluster)
--dockerpath: path to docker image (only needed if using docker container)
-h or --help: show help message
bash /path/to/PennSIVE_neuro_pip/pipelines/radiomic_feature/code/bash/pyradiomics.sh -m /path/to/project --step extraction --toolpath /path/to/PennSIVE_neuro_pip
Step 3. Consolidation
This step consolidates the radiomic features for all participants and sessions.
Required flags:
-m or --mainpath: path to parent data folder
--step: step of pipeline - processing, extraction, consolidation. Default is preparation. This step is consolidation
--toolpath: path to pipeline folder
Other flags:
-c or --container: which container to use: singularity, docker, local, cluster. Default is cluster
--sinpath: path to singularity image (only needed if using singularity container - don't need to specify if using takim cluster)
--dockerpath: path to docker image (only needed if using docker container)
-h or --help: show help message
bash /path/to/PennSIVE_neuro_pip/pipelines/radiomic_feature/code/bash/pyradiomics.sh -m /path/to/data --step consolidation --toolpath /path/to/PennSIVE_neuro_pip