MSPrad · Algorithmic development of proton radiography for image-guided proton radiotherapy of lung cancer.
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2021-09-01 → 2023-08-31
- EU contribution
- €224,934
- Participants
- 1
- Scheme
- MSCA-IF
Lines connect the coordinator with its partners.
Results in brief
Algorithmic development of proton radiography for image-guided proton radiotherapy of lung cancer.
The purpose of this project was to improve a lung cancer patient’s outcome following proton beam radiotherapy (PBT) treatment, by exploiting a new instrument – the proton radiography imager. Lung cancer has unmet needs; it is common (48,500 diagnosed every year) and difficult to treat (5-year survival rate is 16.4%). In 2018, it was the most common cause of cancer death in the UK, costing £2.4 billion/year to the economy. PBT is available in the UK since 2021. It has the potential to improve cancer survival odds because it has clinical benefits over traditional radiotherapy. PBT is used to treat cancer by delivering a strong dose of radiation to the tumour, while avoiding damage to healthy tissues; meaning the treatment is less toxic to patients. However, this method is not as effective for lung cancer because the tumour moves as the patient breathes, making it difficult to hit the target accurately. A solution to help PBT reach its potential is to adapt the treatment by following the tumour with real-time imaging. The aim of this project is to develop a first-of-its-kind proton imager for lung cancer treatment. The instrument aims to generate patient images called proton radiographs to guide PBT towards targeting tumours while sparing healthy tissue. Preliminary studies show that image guided PBT may improve the two-year survival rate by 17% with respect to current practices; it is therefore an important project for society. The overall objectives of the current action were to set down the theoretical and experimental bases to demonstrate the potential of this imaging device. This included developing an image reconstruction methodology for this type of device, demonstrating the potential of the technology and reconstruction method through computer simulations, then building a prototype device, and characterising image quality achievable with it. A reconstruction method was developed, and it was demonstrated that it consistently provides the best image quality amongst existing methodologies for fast proton imaging. This was achieved first through Monte Carlo simulations. Then, a prototype device was built, and it was demonstrated, through experimental datasets acquired at 3 healthcare centres – University College London Hospitals (UCLH), Mayo Clinic Arizona and the Marburg Ion Therapy Centre – that high image quality can be achieved with images that can be produced in real time.
Data: CORDIS, © European Union
Project objective
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.
Original text from CORDIS.
Participants
- UNIVERSITY COLLEGE LONDON · LondonCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union