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Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
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Haralick texture feature analysis for quantifying radiation response heterogeneity in murine models observed using
Irene Vrbik1, Samantha J Van Nest2, Phiranuphon Meksiarun3
1The Department of Statistics, University of British Columbia Okanagan Campus, Kelowna, BC, Canada.
Plos One
|February 16, 2019
Summary
Haralick textural analysis quantifies tumour heterogeneity in response to radiation therapy. This method reveals dose-dependent variations in glycogen production, offering a novel approach to understanding radiation response in murine models.
Area of Science:
- Biomedical Engineering
- Medical Physics
- Cancer Research
Background:
- Tumour heterogeneity significantly impacts radiation therapy outcomes.
- Understanding this heterogeneity is crucial for effective treatment planning.
- Current methods for assessing tumour response lack quantitative precision.
Purpose of the Study:
- To implement Haralick textural analysis for quantifying tumour heterogeneity.
- To assess the response of irradiated tumours in a murine model using Raman spectroscopy.
- To investigate the relationship between Haralick features and radiation dose.
Main Methods:
- Haralick textural analysis applied to Raman spectroscopic maps of tumour glycogen production.
- Focus on five key Haralick features: homogeneity, local homogeneity, contrast, entropy, and correlation.
- Utilized a murine model with tumours exposed to clinically relevant radiation doses.
Main Results:
- Haralick features successfully quantified the heterogeneity of tumour response to radiation.
- Statistically significant, dose-dependent variations in glycogen production heterogeneity were observed.
- The selected Haralick features demonstrated sensitivity to radiation-induced changes.
Conclusions:
- Haralick textural analysis provides a quantitative method for assessing tumour heterogeneity in response to radiation.
- This approach can enhance our understanding of radiation therapy efficacy.
- Future applications include analyzing patient tumour biopsies for personalized treatment strategies.
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