Periodic Reporting for period 1 - NOVO (NEXT GENERATION IMAGING FOR REAL-TIME DOSE VERIFICATION ENABLING ADAPTIVE PROTON THERAPY)
Reporting period: 2024-03-01 to 2025-02-28
The European Commission published in 2021 Europe's Beating Cancer Plan, emphasizing patient-centered cancer care and promoting actions to enable personalised cancer treatment, improve the quality of life of cancer patients and their caregivers, and reduce inequalities in accessing high-quality cancer care across Europe. To meet these ambitious goals, scientific and technological breakthroughs in radiation therapy are needed, in particular for the treatment of radioresistant, hypoxic (oxygen-deprived) tumors associated with low survival rates, involving sophisticated and more accurate radiation dose delivery techniques and enabling personalised dose escalation while ensuring patient safety.
Proton therapy has the potential to offer the most conformal radiation dose to patients, and the number of proton therapy centers around the globe follows a significantly upwards and persisting trend. Adaptive proton therapy, by monitoring and adapting to changes in patient anatomy between treatment fractions, is required to enable safe delivery of proton therapy and to spare healthy tissues. However, truly personalised, dose escalated treatments with proton therapy are not yet possible due to the lack of real-time dose verification technology to truly empower patient-centered cancer treatment, important to improve curation and quality-of-life.
The NOVO (Next generation imaging for real-time dose verification enabling adaptive proton therapy) project aims at making real-time dose verification an integral component of proton therapy -based cancer care in the long-term, allowing precise control over radiation doses delivered to the tumor, as well as preventing unintended exposure of healthy surrounding tissues. We will develop the first proof-of-concept of a groundbreaking real-time dose verification technology adaptable to any proton therapy treatment. The proof-of-concept will be tested under pre-clinical conditions, bringing the envisaged technology concept to Technology Readiness Level 4.
Our high risk/ high gain approach builds on the synergy between: cutting-edge and low-cost organic scintillator technology to detect secondary radiation during treatment for non-invasive measurements; novel and fast image reconstruction algorithms, AI-accelerated models and AI-enhanced image reconstruction to allow simultaneous detection and imaging of multiple radiation species and tissue compositional analysis; tumor-tracking and imaging of tissue radio-sensitivity based on oxygen levels; and intelligent automation of decision-making schemes for real-time dose-guided adaptive therapy. We will also demonstrate technical robustness and trustworthiness of the AI methods used to ensure patient safety and address its effective integration within adaptive therapy clinical workflows.
The NOVO consortium covers the entire value chain of real-time dose verification development (technology providers, theory and modelling, technology integration and testing, and end-users) and will foster transdisciplinary collaborations between nuclear, medical, and high-energy physicists, chemists, mathematicians, computer scientists, oncologists, biologists, as well as European proton therapy centers.
Coordinated by Western Norway University of Applied Sciences (Norway), the NOVO consortium consists of Helmholtz Zentrum Dresden-Rossendorf, Target Systemelektronik and Fraunhofer Institute for Electronic Nano Systems (Germany), Bogazici University (Türkiye), University of Manchester (The United Kingdom) and University of Bergen and Haukeland University Hospital- Helse Bergen (Norway). The project is led by Ilker Meric.
Starting in March 2024 for a duration of four years, NOVO will receive European Union’s funding of almost 3.8 million € from the European Innovation Council as part of the EIC Pathfinder Open programme, under Horizon Europe. EIC Pathfinder supports the exploration of bold ideas for radically new technologies and finances high-risk / high gain and interdisciplinary cutting-edge science collaborations for technological breakthroughs.
Proton therapy has the potential to offer the most conformal radiation dose to patients, and the number of proton therapy centers around the globe follows a significantly upwards and persisting trend. Adaptive proton therapy, by monitoring and adapting to changes in patient anatomy between treatment fractions, is required to enable safe delivery of proton therapy and to spare healthy tissues. However, truly personalised, dose escalated treatments with proton therapy are not yet possible due to the lack of real-time dose verification technology to truly empower patient-centered cancer treatment, important to improve curation and quality-of-life.
The NOVO (Next generation imaging for real-time dose verification enabling adaptive proton therapy) project aims at making real-time dose verification an integral component of proton therapy -based cancer care in the long-term, allowing precise control over radiation doses delivered to the tumor, as well as preventing unintended exposure of healthy surrounding tissues. We will develop the first proof-of-concept of a groundbreaking real-time dose verification technology adaptable to any proton therapy treatment. The proof-of-concept will be tested under pre-clinical conditions, bringing the envisaged technology concept to Technology Readiness Level 4.
Our high risk/ high gain approach builds on the synergy between: cutting-edge and low-cost organic scintillator technology to detect secondary radiation during treatment for non-invasive measurements; novel and fast image reconstruction algorithms, AI-accelerated models and AI-enhanced image reconstruction to allow simultaneous detection and imaging of multiple radiation species and tissue compositional analysis; tumor-tracking and imaging of tissue radio-sensitivity based on oxygen levels; and intelligent automation of decision-making schemes for real-time dose-guided adaptive therapy. We will also demonstrate technical robustness and trustworthiness of the AI methods used to ensure patient safety and address its effective integration within adaptive therapy clinical workflows.
The NOVO consortium covers the entire value chain of real-time dose verification development (technology providers, theory and modelling, technology integration and testing, and end-users) and will foster transdisciplinary collaborations between nuclear, medical, and high-energy physicists, chemists, mathematicians, computer scientists, oncologists, biologists, as well as European proton therapy centers.
Coordinated by Western Norway University of Applied Sciences (Norway), the NOVO consortium consists of Helmholtz Zentrum Dresden-Rossendorf, Target Systemelektronik and Fraunhofer Institute for Electronic Nano Systems (Germany), Bogazici University (Türkiye), University of Manchester (The United Kingdom) and University of Bergen and Haukeland University Hospital- Helse Bergen (Norway). The project is led by Ilker Meric.
Starting in March 2024 for a duration of four years, NOVO will receive European Union’s funding of almost 3.8 million € from the European Innovation Council as part of the EIC Pathfinder Open programme, under Horizon Europe. EIC Pathfinder supports the exploration of bold ideas for radically new technologies and finances high-risk / high gain and interdisciplinary cutting-edge science collaborations for technological breakthroughs.
During the first reporting period, progress towards the technology objectives (TOs) has been satisfactory overall, with varying degrees of completion across different targets. Here, we only report the progress towards the different TOs as these will be used to verify the scientific objectives (SOs) and are essentially needed to be achieved in order to ensure that the project reaches its main objective, the innovation objective (IO). Details of how TOs will be used to verify the SOs and thereby the main objective, the IO are provided in the DoA.
For TO.1 which aims to develop a proof-of-concept of NOVCoDA, approximately 37% of the planned work has been completed, including initial scintillator and DE design, data acquisition design, and preliminary validation activities. In contrast, no progress has been made yet on TO.2 which focuses on the joint evaluation of FN and PG emissions, as this work is scheduled for a later phase in line with the project plan.
Regarding TO.3 which targets the development of novel fast 3D image reconstruction, about 33% of the work has been achieved, with preliminary algorithm development and early simulations demonstrating promising results. For TO.4 the establishment of a robust framework linking FN and PG emissions to physical and biological dose has reached ~14% completion, with initial modelling strategies defined and early validation steps initiated. Finally, TO.5 which aims to leverage AI and ML for model enhancement and adaptive therapy system implementation, has seen ~33% progress, supported by the development and initial testing of AI/ML models. Evidence for all progress is documented in the relevant technical deliverables and is detailed in the following sections of this technical report.
For TO.1 which aims to develop a proof-of-concept of NOVCoDA, approximately 37% of the planned work has been completed, including initial scintillator and DE design, data acquisition design, and preliminary validation activities. In contrast, no progress has been made yet on TO.2 which focuses on the joint evaluation of FN and PG emissions, as this work is scheduled for a later phase in line with the project plan.
Regarding TO.3 which targets the development of novel fast 3D image reconstruction, about 33% of the work has been achieved, with preliminary algorithm development and early simulations demonstrating promising results. For TO.4 the establishment of a robust framework linking FN and PG emissions to physical and biological dose has reached ~14% completion, with initial modelling strategies defined and early validation steps initiated. Finally, TO.5 which aims to leverage AI and ML for model enhancement and adaptive therapy system implementation, has seen ~33% progress, supported by the development and initial testing of AI/ML models. Evidence for all progress is documented in the relevant technical deliverables and is detailed in the following sections of this technical report.
Results beyond the state of the art achieved in the first reporting period concern two novel scintillator materials by Target which have physical characteristics that surpass those from organic scintillators already in the market.