Journal
SCIENTIFIC REPORTS
Volume 5, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/srep11075
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Funding
- QuIC-ConCePT project
- EFPIA companies
- Innovative Medicine Initiative Joint Undertaking (IMI JU) [115151]
- National Institute of Health [NIH-USA U01 CA 143062-01]
- CTMM framework (AIRFORCE project) [030-103]
- EU
- euroCAT (IVA Interreg)
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FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly investigated as imaging biomarkers. As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins. We focused on the implications of the manner in which this discretization is implemented. Two methods were evaluated: (1) RD, dividing the SUV range into D equally spaced bins, where the intensity resolution (i.e. bin size) varies per image; and (2) RB, maintaining a constant intensity resolution B. Clinical feasibility was assessed on 35 lung cancer patients, imaged before and in the second week of radiotherapy. Forty-four textural features were determined for different D and B for both imaging time points. Feature values depended on the intensity resolution and out of both assessed methods, RB was shown to allow for a meaningful inter-and intra-patient comparison of feature values. Overall, patients ranked differently according to feature values-which was used as a surrogate for textural feature interpretation-between both discretization methods. Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.
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