Radiomics and dosiomics for predicting local control after carbon-ion radiotherapy in skull-base chordoma

Giulia Buizza, Chiara Paganelli, Emma D’ippolito, Giulia Fontana, Silvia Molinelli, Lorenzo Preda, Giulia Riva, Alberto Iannalfi, Francesca Valvo, Ester Orlandi, Guido Baroni

Research output: Contribution to journalArticlepeer-review


Skull-base chordoma (SBC) can be treated with carbon ion radiotherapy (CIRT) to improve local control (LC). The study aimed to explore the role of multi-parametric radiomic, dosiomic and clinical features as prognostic factors for LC in SBC patients undergoing CIRT. Before CIRT, 57 patients underwent MR and CT imaging, from which tumour contours and dose maps were ob-tained. MRI and CT-based radiomic, and dosiomic features were selected and fed to two survival models, singularly or by combining them with clinical factors. Adverse LC was given by in-field recurrence or tumour progression. The dataset was split in development and test sets and the mod-els’ performance evaluated using the concordance index (C-index). Patients were then assigned a low-or high-risk score. Survival curves were estimated, and risk groups compared through log-rank tests (after Bonferroni correction α = 0.0083). The best performing models were built on features describing tumour shape and dosiomic heterogeneity (median/interquartile range validation C-in-dex: 0.80/024 and 0.79/0.26), followed by combined (0.73/0.30 and 0.75/0.27) and CT-based models (0.77/0.24 and 0.64/0.28). Dosiomic and combined models could consistently stratify patients in two significantly different groups. Dosiomic and multi-parametric radiomic features showed to be promising prognostic factors for LC in SBC treated with CIRT.

Original languageEnglish
Article number339
Pages (from-to)1-15
Number of pages15
Issue number2
Publication statusPublished - Jan 2 2021


  • Dosiomics
  • Machine learning
  • Oncology
  • Particle therapy
  • Personalized medicine
  • Radiology
  • Radiomics

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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