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TOF-ULET: In-beam Stopping Power Estimation using Prompt Gamma Timing towards Adaptive Charged Particle Therapy

Julius Friedemann Werner*, V. Ferrero, Marco Aglietta, P. Cerello, E. Fiorina, Andreas Bolke, Jona Gabriel Kasprzak, Anna Vignati, F. Pennazio, Magdalena Rafecas

*Corresponding author for this work

Abstract

The precision of charged particle therapy dose deposition is its main advantage to conventional radiotherapy and its weakness when encountering range uncertainties in clinical practice. We offer a new perspective on treatment verification by introducing a technique to estimate electronic stopping power during the treatment from the measurement of time between particle target entry and prompt gamma detection (TOF-ULET). For the estimation of electronic stopping power, we developed a lightweight analytical model for axial particle motion inside the patient. We used Monte Carlo simulations of a homogenous PMMA phantom as a first test of our method, achieving ~ 6 % estimation errors for 170 MeV and 189 MeV protons. The in-beam estimation of electronic stopping power opens up new opportunities in treatment adaptation between fractions by not only indicating significant deviations from the treatment plan, but also offering a current estimate of the patients' anatomy along the beam path and - using conversion models - the delivered dose.
Original languageEnglish
Title of host publication2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Publication date26.01.2024
DOIs
Publication statusPublished - 26.01.2024
Event2022 IEEE Nuclear Science Symposium and Medical Imaging Conference - Milan, Italy
Duration: 05.11.202212.11.2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Research Areas and Centers

  • Academic Focus: Biomedical Engineering
  • Centers: Center of Imaging Sciences (CIS)

DFG Research Classification Scheme

  • 2.22-32 Medical Physics, Biomedical Technology

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