Risk assessment Tools for severe side Effects after breasT Radiotherapy: radiation safety through biological extended models and dIgital twinS

Projektinformationen

TETRIS

ID Finanzhilfevereinbarung: 101166699

EK-Unterschriftsdatum 28 Juni 2024

Startdatum 1 Oktober 2024

Enddatum 30 September 2027

Finanziert unter

• Euratom Research and Training Programme (EURATOM)

Gesamtkosten

€ 3 842 468,75

EU-Beitrag

€ 3 493 218,75

Koordiniert durch

FONDAZIONE IRCCS ISTITUTO NAZIONALE DEI TUMORI
Italy

Periodic Reporting for period 1 - TETRIS (Risk assessment Tools for severe side Effects after breasT Radiotherapy: radiation safety through biological extended models and dIgital twinS)

Berichtszeitraum: 2024-10-01 bis 2026-03-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The TETRIS project addresses a critical challenge in modern cancer care: how to improve long-term safety and quality of life for cancer survivors after radiotherapy. While radiotherapy is an essential and highly effective treatment, exposure to ionising radiation can lead to severe late effects, including cardiopulmonary diseases and second cancers, which may occur years after treatment.
In this context, TETRIS aims to broaden the concept of radioprotection beyond treatment delivery, shifting the focus towards a lifelong, patient-centred approach to risk management. The project specifically focuses on breast cancer, one of the most common cancers worldwide, where large populations of survivors make the long-term impact of treatment particularly relevant at both clinical and societal levels.
The overall objective is to develop innovative tools and strategies that enable personalised risk assessment and more effective prevention of late adverse effects. This includes the integration of clinical, treatment-related, imaging, and biological information into predictive models, as well as the development of digital technologies supporting clinical decision-making and follow-up care. A key innovation of the project is the exploration of digital twin approaches, namely patient-specific digital representations that integrate multiple sources of data to support dynamic risk prediction and more adaptive, data-driven management of survivorship.
By providing clinicians with individualised risk profiles, enabling more tailored survivorship pathways, and introducing novel digital approaches such as patient-specific digital twins, TETRIS is expected to contribute to safer radiotherapy practices, improved patient outcomes, and more efficient healthcare resource allocation. The project is aligned with European priorities on cancer care, data-driven healthcare, and innovation in non-power applications of ionising radiation.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

During the first reporting period, substantial progress was made in establishing the scientific and technical foundations of the project.
A key achievement was the large-scale collection and preparation of retrospective clinical data for model development and validation. The dataset already exceeds initial expectations in terms of patient numbers and will support robust statistical analyses. In parallel, a significant effort was dedicated to harmonising definitions of clinically relevant outcomes, ensuring consistency across datasets and enabling reliable comparison and integration of results.
Important advances were achieved in the development of methodologies for extracting quantitative information from medical images routinely acquired during radiotherapy. Standardised pipelines were established to derive imaging-based indicators related to cardiac, pulmonary, and breast tissue characteristics, ensuring reproducibility across centres and compatibility with real-world clinical data.
In addition, curated genetic and transcriptomic risk indicators were selected and implemented within reproducible computational frameworks. These biological data streams, together with clinical and treatment-related information, form the basis for more comprehensive and biologically informed risk prediction models.
Work also progressed in the development of predictive modelling strategies, including approaches for selecting and validating models for personalised risk estimation. While some activities required additional time due to the complexity of integrating heterogeneous datasets and completing administrative procedures, all critical issues have now been resolved and development activities are progressing as planned.
Significant progress was also made in the design of a clinical software platform intended to support the use of personalised risk information in routine practice. The initial architecture, functional specifications, and interoperability requirements were defined, together with early steps towards regulatory compliance.
Finally, the project established the conceptual and computational foundations for patient-specific digital representations, integrating diverse data sources through advanced modelling approaches. In parallel, the protocol for a prospective clinical study was developed to support future validation and refinement of these approaches in real-world settings.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

TETRIS goes beyond the current state of the art by proposing an integrated and personalised approach to radioprotection that combines clinical, dosimetric, imaging, and biological information. Traditionally, risk assessment in radiotherapy has relied mainly on dose-based models; TETRIS expands this approach by incorporating multiple dimensions of patient-specific variability.
The project has developed the foundation for advanced predictive models that can more accurately estimate the risk of long-term adverse effects. The integration of imaging-derived biomarkers and molecular information represents a significant innovation, enabling a more biologically informed understanding of treatment-related risks.
Another key advancement is the development of digital twin concepts applied to radiotherapy. By creating dynamic digital representations of patients that can evolve over time, TETRIS opens the possibility for continuous risk assessment and adaptive follow-up strategies, which are not currently available in routine care.
The planned clinical software platform further extends the impact by translating complex modelling results into usable tools for clinicians, supporting decision-making and improving communication with patients.
To ensure successful uptake, further steps will be important, including continued validation of models in large and diverse populations, demonstration of clinical utility in real-world settings, and alignment with regulatory and standardisation frameworks. Integration into healthcare systems and access to appropriate infrastructures will also be key to long-term impact.