Skip to Main content Skip to Navigation
Theses

Predictive models of toxicity in intensity modulated radiotherapy

Abstract : This thesis is focused on the predictive models of irradiation induced toxicities in intensity modulated radiotherapy. Six different NTCP models were implemented and their parameters were identified at predicting late rectal and bladder toxicities in prostate cancer. Their predictive skills have been demonstrated on both organs. Second, LKB model was used to predict the irradiation induced acute esophagitis after nun-small-cell lung cancer. Then, the benefit of using EUD in prostate cancer IMRT inverse planning was evaluated. The evaluation of the proposed approach proved that the use of EUD significantly decreased both the dose in the bladder and rectum walls. Then, the incorporation of different biological models in IMRT optimization process has been realized. Objective functions were established for different biological factors like NTCP, EUD and TCP. Obtained results show the superiority of the optimization based on biological factors over the optimization relying only on physical factors. Finally, classical NTCP models were corrected to deal with another radiobiological parameter, the α/β ratio. With this additional factor, NTCP models can be extended to predict toxicity for patients with different dose fractionation, these kinds of treatments being more and more clinically used.
Complete list of metadata

https://tel.archives-ouvertes.fr/tel-00855266
Contributor : ABES STAR :  Contact
Submitted on : Thursday, August 29, 2013 - 11:12:11 AM
Last modification on : Wednesday, September 14, 2022 - 10:20:04 AM
Long-term archiving on: : Monday, December 2, 2013 - 8:53:53 AM

File

ZHU_Jian.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-00855266, version 1

Citation

Jian Zhu. Predictive models of toxicity in intensity modulated radiotherapy. Signal and Image processing. Université Rennes 1, 2013. English. ⟨NNT : 2013REN1S017⟩. ⟨tel-00855266⟩

Share

Metrics

Record views

340

Files downloads

540