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Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis
Sugama Chicklore1, Vicky Goh, Musib Siddique
1Clinical PET Centre, Division of Imaging Sciences and Biomedical Engineering, Kings College London, St Thomas' Hospital, London, UK.
Texture analysis of (18)F-Fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) scans reveals tumor heterogeneity. These radiomic features offer enhanced predictive and prognostic information beyond traditional standardized uptake values (SUV).
Area of Science:
- Oncological imaging
- Radiomics
- Medical image analysis
Background:
- Standardized uptake value (SUV) from (18)F-FDG PET/CT is limited for predicting tumor behavior.
- Medical images contain more information than visible to the naked eye, leading to radiomics.
- Radiomics extracts additional features via computational postprocessing.
Purpose of the Study:
- To review emerging texture analysis methods in (18)F-FDG PET/CT and other imaging modalities.
- To explore how voxel intensity variation provides predictive and prognostic information.
- To postulate underlying biological mechanisms for these findings.
Main Methods:
- Focus on literature describing texture analysis in (18)F-FDG PET/CT.
- Analysis of spatial variation and heterogeneity of voxel intensities.
- Review of computational postprocessing techniques for radiomic feature extraction.
Main Results:
- Texture analysis parameters reflect spatial variation and heterogeneity within tumors.
- These textural features may yield additional predictive and prognostic information.
- Potential for improved tissue characterization and treatment stratification.
Conclusions:
- Texture analysis in (18)F-FDG PET/CT offers enhanced predictive and prognostic capabilities.
- May lead to better stratification in clinical trials and individualized cancer treatment.
- Further research into underlying biological mechanisms is warranted.
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