Assessing the agreement of radiomic tools for dosiomics: A multi‐software comparative study
The findings of this study indicate that, when properly configured, the tools show good overall agreement, with variability limited to specific features and pre-processing choices. While variations in program-specific resampling and FBS discretization implementation are present, their overall impact on dosiomic feature reproducibility remains minimal.
Authors
- G. Pirrone (ORCID: https://orcid.org/0000-0002-6113-6644)
- Annarita Fanizzi (ORCID: https://orcid.org/0000-0002-2729-9896)
- Michele Avanzo (ORCID: https://orcid.org/0000-0003-1711-4242)
- Cristina Garibaldi (ORCID: https://orcid.org/0000-0002-0090-1752)
- Eliana Gioscio (ORCID: https://orcid.org/0009-0007-8692-7593)
- T. Rancati (ORCID: https://orcid.org/0000-0002-7849-603X)
- Francesca Marturano (ORCID: https://orcid.org/0000-0002-5430-1234)
- E. Menghi (ORCID: https://orcid.org/0000-0002-8051-9640)
- Raffaella Massafra
- Andrea Bettinelli
- Marta Paiusco
- Lorenzo Placidi
Institutions
- Agostino Gemelli University Polyclinic (IT)
- Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IT)
- Istituto Oncologico Veneto (IT)
- Athinoula A. Martinos Center for Biomedical Imaging (US)
- Centro di Riferimento Oncologico (IT)
- Istituto Tumori Bari (IT)
- Fondazione IRCCS Istituto Nazionale dei Tumori (IT)
- European Institute of Oncology (IT)
Publication Details
- Journal
- Medical Physics
- Published
- 2025-12-21
- DOI
- https://doi.org/10.1002/mp.70203
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministero della Salute