Modeling the Interplay Between Tumor Volume Regression and Oxygenation in Uterine Cervical Cancer During Radiotherapy Treatment

Antonella Belfatto, Marco Riboldi, Delia Ciardo, Federica Cattani, Agnese Cecconi, Roberta Lazzari, Barbara Alicja Jereczek-Fossa, Roberto Orecchia, Guido Baroni, Pietro Cerveri

Research output: Contribution to journalArticle


This paper describes a patient-specific mathematical model to predict the evolution of uterine cervical tumors at a macroscopic scale, during fractionated external radiotherapy. The model provides estimates of tumor regrowth and dead-cell reabsorption, incorporating the interplay between tumor regression rate and radiosensitivity, as a function of the tumor oxygenation level. Model parameters were estimated by minimizing the difference between predicted and measured tumor volumes, these latter being obtained from a set of 154 serial cone-beam computed tomography scans acquired on 16 patients along the course of the therapy. The model stratified patients according to two different estimated dynamics of dead-cell removal and to the predicted initial value of the tumor oxygenation. The comparison with a simpler model demonstrated an improvement in fitting properties of this approach (fitting error average value

Original languageEnglish
Article number7027782
Pages (from-to)596-605
Number of pages10
JournalIEEE Journal of Biomedical and Health Informatics
Issue number2
Publication statusPublished - Mar 1 2016



  • Radiation response
  • radioresistance
  • radiosensitivity
  • tumor growth

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

Cite this