Summary
Proton therapy is a new radiotherapy modality which aims to maximize dose deposition in tumors, while sparing surrounding healthy tissues. It is uniquely suited for the treatment of non-small cell lung cancer, a deadly cancer of current unmet needs. Improving the prognosis of non-small cell lung cancer is an important health and wellbeing milestone, which was identified as one of Europe’s societal challenge in the Horizon 2020 programme. However, the expected benefits of proton therapy are largely impaired by patient motion (breathing) during treatment. A potential solution is to adapt the treatment in real-time by following the location of the tumour with imaging.
The overreaching goal of this action is to enable real-time tumor tracking for accurate lung tumor treatment in proton radiotherapy. To do so, a radiographic device, developed by the prospective group, will use the proton treatment source to generate quasi real-time images (proton radiographs) to mitigate the impact of breathing on treatment quality. However, due to the poor image quality of current radiographs, rapid image quality optimization algorithms are mandatory to allow real-time adaptation.
This action focuses on producing the necessary algorithms and validation to use proton radiographs in real time. The three main objectives are to (1) develop a proton radiography image quality enhancement (resolution and noise) algorithm based on deconvolution, (2) implement a tumor position tracking algorithm from high-quality proton radiographies, and (3) perform a full experimental validation on the integrated image-guided proton therapy unit.
This work will be carried out at University College London (UCL) and its affiliated hospital (UCLH), under the supervision of Prof. Gary Royle and co-supervision of Dr. Charles-Antoine Collins Fekete. It will be a synergistic combination of the applicant’s experience in image reconstruction/analysis and UCL’s expertise on proton physics and therapy.
The overreaching goal of this action is to enable real-time tumor tracking for accurate lung tumor treatment in proton radiotherapy. To do so, a radiographic device, developed by the prospective group, will use the proton treatment source to generate quasi real-time images (proton radiographs) to mitigate the impact of breathing on treatment quality. However, due to the poor image quality of current radiographs, rapid image quality optimization algorithms are mandatory to allow real-time adaptation.
This action focuses on producing the necessary algorithms and validation to use proton radiographs in real time. The three main objectives are to (1) develop a proton radiography image quality enhancement (resolution and noise) algorithm based on deconvolution, (2) implement a tumor position tracking algorithm from high-quality proton radiographies, and (3) perform a full experimental validation on the integrated image-guided proton therapy unit.
This work will be carried out at University College London (UCL) and its affiliated hospital (UCLH), under the supervision of Prof. Gary Royle and co-supervision of Dr. Charles-Antoine Collins Fekete. It will be a synergistic combination of the applicant’s experience in image reconstruction/analysis and UCL’s expertise on proton physics and therapy.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101023220 |
| Start date: | 01-09-2021 |
| End date: | 31-08-2023 |
| Total budget - Public funding: | 224 933,76 Euro - 224 933,00 Euro |
Cordis data
Original description
Proton therapy is a new radiotherapy modality which aims to maximize dose deposition in tumors, while sparing surrounding healthy tissues. It is uniquely suited for the treatment of non-small cell lung cancer, a deadly cancer of current unmet needs. Improving the prognosis of non-small cell lung cancer is an important health and wellbeing milestone, which was identified as one of Europe’s societal challenge in the Horizon 2020 programme. However, the expected benefits of proton therapy are largely impaired by patient motion (breathing) during treatment. A potential solution is to adapt the treatment in real-time by following the location of the tumour with imaging.The overreaching goal of this action is to enable real-time tumor tracking for accurate lung tumor treatment in proton radiotherapy. To do so, a radiographic device, developed by the prospective group, will use the proton treatment source to generate quasi real-time images (proton radiographs) to mitigate the impact of breathing on treatment quality. However, due to the poor image quality of current radiographs, rapid image quality optimization algorithms are mandatory to allow real-time adaptation.
This action focuses on producing the necessary algorithms and validation to use proton radiographs in real time. The three main objectives are to (1) develop a proton radiography image quality enhancement (resolution and noise) algorithm based on deconvolution, (2) implement a tumor position tracking algorithm from high-quality proton radiographies, and (3) perform a full experimental validation on the integrated image-guided proton therapy unit.
This work will be carried out at University College London (UCL) and its affiliated hospital (UCLH), under the supervision of Prof. Gary Royle and co-supervision of Dr. Charles-Antoine Collins Fekete. It will be a synergistic combination of the applicant’s experience in image reconstruction/analysis and UCL’s expertise on proton physics and therapy.
Status
CLOSEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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