Minimum Matlab implementation of individual whole-body graph build-up in Sun, T., Wang, Z., Wu, Y. et al. Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging. Eur J Nucl Med Mol Imaging 49, 2994–3004 (2022).
- Make sure Matlab 2018b or above version is installed.
- Make sure Brain connectivity toolbox (https://sites.google.com/site/bctnet/) is in your Matlab path.
- The default visualization script is edited from https://github.com/okomarov/schemaball.
- (Optional) Install Brainnet viewer or connectomeviewer if you want to visualize the network.
- Prepare a list of organ SULs or SUVs for each subject as structured in the "subjects" folder.
- Run example.m to have a basic idea of how it works.
- Substitute your datapath and generate an individual network for your purpose.
The original paper can be found here https://doi.org/10.1007/s00259-022-05832-7. The related publications have used this method so far
- Identifying the individual metabolic abnormalities from a systemic perspective using whole-body PET imaging. European Journal of Nuclear Medicine and Molecular Imaging. 2022;49:2994–3004.
- Metabolic interactions between organs in overweight and obesity using total-body positron emission tomography. International Journal of Obesity 2024.
- Individual-specific metabolic network based on 18F-FDG PET revealing multi-level aberrant metabolisms in Parkinson's disease. Human Brain Mapping, 2024.
- Tau-PET abnormality as a biomarker for Alzheimer's disease staging and early detection: a topological perspective. Cereb Cortex. 2023.
- IG-GCN: Empowering e-Health Services for Alzheimer's Disease Prediction. IEEE Transactions on Consumer Electronics. 2024.
- Organs and Systems Glucose Metabolism Analysis in Different Smoking Groups for Lung Cancer Patients using Total-body PET/CT, IEEE Nuclear Science Symposium (NSS), Medical Imaging Conference (MIC) and Room Temperature Semiconductor Detector Conference (RTSD), Tampa, USA, 2024.