This paper describes a feature selection methodology for longitudinal radiomics that is able to select reproducible delta radiomics features that are informative due to their change during treatment, which can potentially be used for treatment decisions concerning adaptive radiotherapy.
Acknowledgement from the authors
Author PL acknowledges financial support from ERC advanced grant (ERC-ADG-2015, n° 694812 - Hypoximmuno). This research is also supported by the Dutch Technology Foundation STW (grant n° 10696 DuCAT & n° P14-19 Radiomics STRaTegy), which is the applied science division of NWO, and the Technology Programme of the Ministry of Economic Affairs. Author PL also acknowledges financial support from the EU 7th framework program (ARTFORCE - n° 257144, REQUITE - n° 601826), SME Phase 2 (EU proposal 673780 – RAIL), EUROSTARS (DART), the European Program H2020-2015-17 (BD2Decide - PHC30-689715 and ImmunoSABR - n° 733008), Interreg V-A Euregio Meuse-Rhine ("Euradiomics"), Kankeronderzoekfonds Limburg from the Health Foundation Limburg and the Dutch Cancer Society