RADRESPRO
Radiation Response Models for Personalised Radiation Oncology
| Coordinatore | QUEEN'S UNIVERSITY BELFAST
Organization address
address: University Road contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 294˙219 € |
| EC contributo | 294˙219 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2013-IOF |
| Funding Scheme | MC-IOF |
| Anno di inizio | 2014 |
| Periodo (anno-mese-giorno) | 2014-06-01 - 2017-05-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
QUEEN'S UNIVERSITY BELFAST
Organization address
address: University Road contact info |
UK (BELFAST) | coordinator | 294˙219.60 |
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Obiettivo del progetto (Objective)
'Clinical radiotherapy for cancer has seen dramatic improvements in recent years, driven by developments in imaging and delivery techniques. However, the ability to deliver radiation is now out-stripping radiotherapy planning techniques. Despite the goal of radiotherapy – tumour control – being primarily biological, radiotherapy planning tools focus on a purely physical metric: dose. This has significantly hampered the translation of knowledge gained from laboratory radiobiology to clinical settings. This project will lay the foundation for a unified model of therapeutic in vivo radiation responses by developing a computational model to describe these systems in a bottom-up fashion, integrating not only macroscopic parameters such as tumour size and dose, but also microscopic parameters such as radiation track structure and the cellular micro-environment. As part of this project, collaboration will be developed between the radiation biology group in the Centre for Cancer Research and Cell Biology, Queen's University Belfast, and Massachusetts General Hospital. The applicant will take advantage of time spent in MGH to gain skills and experience in the delivery of proton therapy, broadening his technical background and placing him in a strong position to contribute to the development of this increasingly important treatment modality upon his return to the EU. These models will enable a more natural integration of physical and biological parameters into radiation response models, facilitating improved knowledge transfer from laboratory to clinical practice. Through this, they can be used to address outstanding questions in modern radiotherapy, such as identifying the optimum dose distribution and delivery schedule for individual patients, and understanding the differences in biological responses to different types of radiation.'