In vivo patient-specific real-time dosimetry for adaptive radiotherapy (VERIFIED). WP1 - Development of anthropomorphic phantoms (PIANOFORTE)

Errors in radiotherapy can have significant consequences for patients and generate public concern due to misconceptions surrounding ionizing radiation. To enhance the safety and efficacy of radiotherapy, the implementation of in vivo dosimetry is crucial. The VERIFIED project aims to advance individualized therapeutic procedures by utilizing patient-specific
information, real-time dose monitoring, and deep learning techniques in Adaptive Radiotherapy (ART). The primary objective of the project is to develop dynamic end-to-end methods that closely simulate real patient treatments. ART addresses the dynamic nature of radiotherapy targets, which can vary in position, shape, size, and biology over time. This variability necessitates continual adjustments to the treatment plan to ensure accurate dose delivery and minimize damage to adjacent critical structures. The WP1 from the VERIFIED project focuses on developing and characterizing anthropomorphic phantoms with movable and deformable inserts, specifically targeting lung and brain tumours for ART. These phantoms are essential for simulating realistic patient scenarios and conducting real-time
patient-specific dosimetry studies. The dynamic phantoms developed in this project mimic patient anatomy and physiological motion, including breathing motion, tumour size, and organ position changes during and after each treatment fraction. This will involve expertise in medical imaging, 3D modelling, and additive manufacturing to create customized phantoms tailored to specific tumour types. Objectives within Work Package 1 include the design and fabrication of anatomically accurate phantoms for lung, bladder, and brain tumors; incorporation of mechanisms to simulate breathing motion in lung phantoms and volume changes in bladder phantoms; and implementation of adjustable tumor sizes and organ
positions within all phantoms. These phantoms will be validated using imaging techniques and expert evaluation to ensure their anatomical fidelity. By leveraging real-time dosimetry, imaging, and deep learning, the VERIFIED project aims to enhance treatment efficacy, minimize toxicity, and reduce radiation-induced side effects. The integration of state-of-theart deep learning methods with patient-specific real-time dosimetry in ART-VMAT and realtime position imaging in hfGKRS addresses several unmet needs in adaptive radiotherapy.