Proton therapy is a cutting-edge radiotherapy modality offering superior dose localization and reduced damage to healthy tissues, made possible by the unique physical characteristics of protons. Accurate prediction of proton range during treatment planning is critical to its success. However, current methods relying on single-energy CT (SECT) together with heuristic calibration approaches (e.g., Hounsfield look-up tables) are limited by uncertainties in tissue characterization. Emerging multi-energy CT (DECT and PCCT) and proton CT (pCT) technologies aim to enhance range accuracy by addressing these limitations. This PhD research focuses on evaluating the imaging performance of the INFN proton CT prototype, developing novel calibration methods using ex vivo phantoms, and comparing these approaches to conventional SECT and cutting-edge multi-energy CT systems. Key outcomes include the characterization of pCT imaging performance, validation of phantom-based calibration for stopping power estimation, and an initial exploration of clinical applications for proton therapy planning. Collaborative studies with international research groups further demonstrated the potential of integrating pCT and multi-energy CT data to reduce uncertainties in dose calculation and improve inter-center consistency. The results highlight the advantages of proton imaging for robust treatment planning and pave the way for future advancements in clinical proton therapy. By combining hardware innovation, advanced reconstruction algorithms, and interdisciplinary collaboration, this work contributes to the optimization of proton therapy precision and its broader implementation in cancer care.

Proton Computed Tomography: a novel calibration approach for proton treatment planning

Fogazzi, Elena
2025

Abstract

Proton therapy is a cutting-edge radiotherapy modality offering superior dose localization and reduced damage to healthy tissues, made possible by the unique physical characteristics of protons. Accurate prediction of proton range during treatment planning is critical to its success. However, current methods relying on single-energy CT (SECT) together with heuristic calibration approaches (e.g., Hounsfield look-up tables) are limited by uncertainties in tissue characterization. Emerging multi-energy CT (DECT and PCCT) and proton CT (pCT) technologies aim to enhance range accuracy by addressing these limitations. This PhD research focuses on evaluating the imaging performance of the INFN proton CT prototype, developing novel calibration methods using ex vivo phantoms, and comparing these approaches to conventional SECT and cutting-edge multi-energy CT systems. Key outcomes include the characterization of pCT imaging performance, validation of phantom-based calibration for stopping power estimation, and an initial exploration of clinical applications for proton therapy planning. Collaborative studies with international research groups further demonstrated the potential of integrating pCT and multi-energy CT data to reduce uncertainties in dose calculation and improve inter-center consistency. The results highlight the advantages of proton imaging for robust treatment planning and pave the way for future advancements in clinical proton therapy. By combining hardware innovation, advanced reconstruction algorithms, and interdisciplinary collaboration, this work contributes to the optimization of proton therapy precision and its broader implementation in cancer care.
7-feb-2025
Inglese
computed tomography
stopping power
treatment planning
Tommasino, Francesco
Università degli studi di Trento
TRENTO
197
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/193453
Il codice NBN di questa tesi è URN:NBN:IT:UNITN-193453