Periodic Reporting for period 1 - RAPTOR (Real-time Adaptive Particle Therapy of Cancer)
Periodo di rendicontazione: 2021-03-01 al 2023-05-31
The RAPTOR (Real-time Adaptive Particle Therapy Of canceR) project is a European H2020-MSCA-ITN grant that aims at advancing particle therapy by incorporating online/real-time adaptation techniques to improve treatment outcomes for cancer patients.
Traditional radiotherapy relies on static treatment plans based on pre-treatment imaging, assuming that the patient's anatomy remains unchanged throughout the course of treatment. However, anatomical changes and uncertainties during treatment delivery can compromise treatment efficacy. The RAPTOR project aims at addressing this challenge by developing and implementing real-time adaptive PT strategies.
The main objectives of the RAPTOR project are i) to enable on-board volumetric image guidance for online adaptive PT planning; ii) to streamline the adaptive planning procedures through automated and rapidly adaptable treatment plan optimisation; and iii) to develop methods for independent verification of the adapted treatment plans.
Furthermore, RAPTOR aims at establishing comprehensive medical physics training focused on adaptive particle therapy, filling the current gap in education in this field. By providing a multidisciplinary, intercultural, and intersectoral platform for early-stage researchers (ESRs), RAPTOR offers a training initiative that addresses the complex clinical and industrial landscape of real-time adaptive particle therapy. Each ESR undertakes a research project to overcome specific challenges in the clinical implementation of adaptive PT therapy, benefiting from collaboration with world-renowned healthcare facilities and market-leading industrial partners. The RAPTOR project brings together leading experts in the field of particle therapy from different institutions across Europe. Through close collaboration and knowledge sharing, the consortium aims to accelerate the translation of advances in online adaptive therapy into clinical practice.
The project closes two fundamental gaps in European training by educating emerging researchers in all aspects of real-time adaptive particle therapy and offering interdisciplinary and intersectoral training. RAPTOR equips researchers with state-of-the-art techniques and procedures, fostering a holistic and creative mindset with a focus on future clinical and industrial applications.
In summary, RAPTOR aims to train a new generation of medical physicists and to personalize patient care in radiotherapy by implementing a treatment loop that involves continuous adjustment and adaptation of the radiotherapy treatment.
Traditional radiotherapy relies on static treatment plans based on pre-treatment imaging, assuming that the patient's anatomy remains unchanged throughout the course of treatment. However, anatomical changes and uncertainties during treatment delivery can compromise treatment efficacy. The RAPTOR project aims at addressing this challenge by developing and implementing real-time adaptive PT strategies.
The main objectives of the RAPTOR project are i) to enable on-board volumetric image guidance for online adaptive PT planning; ii) to streamline the adaptive planning procedures through automated and rapidly adaptable treatment plan optimisation; and iii) to develop methods for independent verification of the adapted treatment plans.
Furthermore, RAPTOR aims at establishing comprehensive medical physics training focused on adaptive particle therapy, filling the current gap in education in this field. By providing a multidisciplinary, intercultural, and intersectoral platform for early-stage researchers (ESRs), RAPTOR offers a training initiative that addresses the complex clinical and industrial landscape of real-time adaptive particle therapy. Each ESR undertakes a research project to overcome specific challenges in the clinical implementation of adaptive PT therapy, benefiting from collaboration with world-renowned healthcare facilities and market-leading industrial partners. The RAPTOR project brings together leading experts in the field of particle therapy from different institutions across Europe. Through close collaboration and knowledge sharing, the consortium aims to accelerate the translation of advances in online adaptive therapy into clinical practice.
The project closes two fundamental gaps in European training by educating emerging researchers in all aspects of real-time adaptive particle therapy and offering interdisciplinary and intersectoral training. RAPTOR equips researchers with state-of-the-art techniques and procedures, fostering a holistic and creative mindset with a focus on future clinical and industrial applications.
In summary, RAPTOR aims to train a new generation of medical physicists and to personalize patient care in radiotherapy by implementing a treatment loop that involves continuous adjustment and adaptation of the radiotherapy treatment.
Significant progress has been made in all Work Packages during this initial period. In WP1- Training, both schools were successfully conducted, with the third one being in preparation, and all ESRs completed their career development plans. WP5-Dissemination has also had a significant impact, marked by the launch of the RAPTOR website, regular social media posts and the bi-yearly RAPTOR newsletter.
In addition, significant results have been achieved by all ESRs in the three scientific work packages , thus resulting in five peer-reviewed publications and numerous oral and poster presentations at international conferences.
WP2 - Imaging focuses on enabling on-board volumetric image guidance for daily and future real-time adaptive PT planning. The team has achieved promising results by exploring strategies to create synthetic CT images from CBCT and MRI scans of both static and moving organs. These synthetic CTs serve as the basis for dose planning and adaptation. Moreover, methodological solutions, mainly based on deep learning, have been proposed for automatic contour segmentation and propagation (Smolders et al PMB 2023, Smolders et al PMB 2023) and dose accumulation.
WP3-Intervention, focuses on streamlining planning procedures through automated and rapidly adjustable treatment plan optimization (Qiu et al PMB 2023). Fast dose optimization methods were successfully developed, and dosimetric uncertainties related to implementing fast dose optimization on CBCT were quantified. Additionally, a visualization tool for daily plan approval and a classification method for optimal adaptation strategies were outlined. Finally, a ultra-fast tool for reconstruction of the 4D dose delivery accounting for intrafractional changes has been developed.
WP4- Verification aims to develop methods for independent verification of adapted treatment plans. Significant advancements were made in Prompt Gamma Imaging (PGI) data processing speed, confirming its potential for reducing safety margins (Bertschi et al 2023 Phyro). Models for reconstructing the delivered dose distribution from prompt gamma data were implemented and evaluated through in-silico studies and initial phantom experiments. For Range Probing (RP), AI-based classification models were developed to identify treatment deviations and their sources, achieving promising accuracy levels and processing speed in in-silico studies. These models will be further validated with real-world RP data. Furthermore, a sophisticated 3D-printed end-to-end test phantom was designed and produced, along with a logfile-based dose reconstruction framework.
Overall, this first project period has seen significant accomplishments in all work packages, positioning the project for further success in its subsequent phases.
In addition, significant results have been achieved by all ESRs in the three scientific work packages , thus resulting in five peer-reviewed publications and numerous oral and poster presentations at international conferences.
WP2 - Imaging focuses on enabling on-board volumetric image guidance for daily and future real-time adaptive PT planning. The team has achieved promising results by exploring strategies to create synthetic CT images from CBCT and MRI scans of both static and moving organs. These synthetic CTs serve as the basis for dose planning and adaptation. Moreover, methodological solutions, mainly based on deep learning, have been proposed for automatic contour segmentation and propagation (Smolders et al PMB 2023, Smolders et al PMB 2023) and dose accumulation.
WP3-Intervention, focuses on streamlining planning procedures through automated and rapidly adjustable treatment plan optimization (Qiu et al PMB 2023). Fast dose optimization methods were successfully developed, and dosimetric uncertainties related to implementing fast dose optimization on CBCT were quantified. Additionally, a visualization tool for daily plan approval and a classification method for optimal adaptation strategies were outlined. Finally, a ultra-fast tool for reconstruction of the 4D dose delivery accounting for intrafractional changes has been developed.
WP4- Verification aims to develop methods for independent verification of adapted treatment plans. Significant advancements were made in Prompt Gamma Imaging (PGI) data processing speed, confirming its potential for reducing safety margins (Bertschi et al 2023 Phyro). Models for reconstructing the delivered dose distribution from prompt gamma data were implemented and evaluated through in-silico studies and initial phantom experiments. For Range Probing (RP), AI-based classification models were developed to identify treatment deviations and their sources, achieving promising accuracy levels and processing speed in in-silico studies. These models will be further validated with real-world RP data. Furthermore, a sophisticated 3D-printed end-to-end test phantom was designed and produced, along with a logfile-based dose reconstruction framework.
Overall, this first project period has seen significant accomplishments in all work packages, positioning the project for further success in its subsequent phases.
The project aims to go beyond the current state of the art by addressing challenges in all the components of a real-time adaptive PT treatment loop: imaging, intervention and verification.
The expected results until the end of the project include the development of potentially clinically implementable solutions, conceptual solutions that can be implemented independently of specific PT configurations, and a partial automation of workflows using machine learning. These results would contribute to the ideological shift from manual to automatic workflow and from local-specific procedures to a global standardized perspective.
The socio-economic impact of RAPTOR lies in the potential for significant improvements in cancer treatment outcomes, leading to improved patient well-being and quality of life. The wider societal implications include advancing medical physics education and training, fostering collaboration between academia and industry, and providing interdisciplinary opportunities for researchers.
Overall, the RAPTOR project addresses the challenges in implementing real-time adaptive PT and aims to advance clinical particle treatments, improve PT workflows, and shape the future of PT. The project has the potential to significantly impact the care of cancer patients and enhance the career prospects of researchers.
The expected results until the end of the project include the development of potentially clinically implementable solutions, conceptual solutions that can be implemented independently of specific PT configurations, and a partial automation of workflows using machine learning. These results would contribute to the ideological shift from manual to automatic workflow and from local-specific procedures to a global standardized perspective.
The socio-economic impact of RAPTOR lies in the potential for significant improvements in cancer treatment outcomes, leading to improved patient well-being and quality of life. The wider societal implications include advancing medical physics education and training, fostering collaboration between academia and industry, and providing interdisciplinary opportunities for researchers.
Overall, the RAPTOR project addresses the challenges in implementing real-time adaptive PT and aims to advance clinical particle treatments, improve PT workflows, and shape the future of PT. The project has the potential to significantly impact the care of cancer patients and enhance the career prospects of researchers.