학술논문

TOF-ULET: In-beam Stopping Power Estimation using Prompt Gamma Timing towards Adaptive Charged Particle Therapy
Document Type
Conference
Source
2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2022 IEEE. :1-3 Nov, 2022
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Nuclear Engineering
Photonics and Electrooptics
Signal Processing and Analysis
Protons
Estimation error
Adaptation models
Computational modeling
Medical treatment
Timing
X-ray imaging
Language
ISSN
2577-0829
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.