pLGG Radioimmunomics and Clinicoradiomics

This code repository includes the data and source codes used in the manuscript "Multiparametric MRI Along with Machine Learning Predicts Prognosis and Treatment Response in Pediatric Low-Grade Glioma"

Software Requirements

• CaPTk, v1.8.1 (https://cbica.github.io/CaPTk/)
• Python3
• R v4.3
• MATLAB 2023A (v23.2)
  • Parallel Computing Toolbox
  • Statistics and Machine Learning Toolbox

Hardware Used for this Study

• CUBIC (HPC Cluster) (https://www.med.upenn.edu/cbica/cubic.html)
• AWS/EC2 for batch image pre-processing, segmentation, radiomic feature extraction

MRI Pre-processing and Tumor Segmentation:

• Required MRI sequences: T1, T1CE, T2, FLAIR (ADC optional)
• Pre-processing using BraTS Pre-processing Pipeline: https://github.com/d3b-center/peds-brain-seg-pipeline-public (under BSD 2-Clause license); (original codes can be accessed at https://cbica.github.io/CaPTk/preprocessing_brats.html)
• Tumor Segmentation, all details provided in: https://github.com/d3b-center/peds-brain-auto-seg-public (under BSD 2-Clause license)
• Skull-stripping to generate a brain mask: https://github.com/d3b-center/peds-brain-auto-skull-strip (under BSD 2-Clause license)
• Image normalization: https://github.com/d3b-center/peds-brain-seg-pipeline-public (under BSD 2-Clause license)
  • run_rescale.py
• Whole tumor generation:
  • run_wtmask.py
• Radiomic feature extraction, using CaPTk v1.8.1: https://github.com/d3b-center/peds-brain-seg-pipeline-public (under BSD 2-Clause license) (original codes can be accessed at https://cbica.github.io/CaPTk/ht_FeatureExtraction.html)
  • parameter file for radiomic feature extraction: radiomic_feature_params_20230725.csv
  • sample batch file: SampleBatchFile.csv

All these steps can be executed using the docker files provided at our GitHub repository: https://github.com/d3b-center/peds-brain-seg-pipeline-public (under BSD 2-Clause license). Portions of the code are adapted from "CaPTk" (https://cbica.github.io/CaPTk), licensed under CBICA Software License - https://www.med.upenn.edu/cbica/software-agreement.html. We have retained the original license information and copyright statements in the source files where this code is used. The original code can be accessed at https://cbica.github.io/CaPTk.

Immune Profiling:

• analyses/lgg_xcell_analyses

Radioimmunomic Analysis:

• analyses/Radioimmunomic_Signature

Clinicoradiomic Risk Stratification:

• analyses/Clinicoradiomics

Assessment of transcriptomic pathways associated with clinicoradiomic risk:

• analyses/lgg_risk_analysis