|Title||Automatic Treatment Planning for Proton Therapy: Investigations of Robustly Optimized Intensity Modulated Proton Therapy Incorporating LET/RBE Criteria and Physical and Biological Uncertainties|
|Scientific Area||Medical Physics|
|Funding (PT)||49 876,81 EUR|
|Funding (US)||50 000,00 USD|
|Leading Institutions||Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra)
Department of Radiation Physics, MD Anderson Cancer Center, UT Austin
|Start date||December 1, 2020|
|End date||November 30, 2020|
|Keywords||Computer-aided inverse planning, Radiotherapy, Protons, Robust optimization|
Compared with photon-based radiotherapy, proton radiotherapy (PR) has specific features that make it highly appropriate for cancer treatment. However, PR is much more vulnerable to uncertainties, not only to inter and intra-fractional anatomic variations but also to the uncertainties in relative biological effectiveness. AT@PT will apply robust beam angle and intensity modulation optimization methodologies to render radiation dose distributions less sensitive to uncertainties.
This project aims at achieving treatment planning solutions that are scalable, reliable, fast, and cost-effective. It will create opportunities to truly tailor radiation treatments to patients, potentially resulting in increased cure or reduced incidence of severe radiation-induced morbidity. The gain in treatment quality can even be obtained at a reduced cost due to automation, which can also support the selection of patients for novel expensive treatments.
The outcomes of the research activities, leveraged by the collaboration of the two research teams, can also result in knowledge transfer to industry and contribute to scientific job creation.
- Algorithms developed for scenario generation, beam angle and intensity modulation optimization;
- Scientific production (two manuscripts, at least, will be submitted to international journals; presentations in, at least, three international conferences (highly dependent on the global evolution of the pandemic situation) and one M.Sc. thesis).