1. High accuracy proton relative stopping power measurement
- Author
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J.K. Van Abbema, Marcel J. W. Greuter, A. Van der Schaaf, Aleksandra Biegun, J. Mulder, M. J. van Goethem, Sijtze Brandenburg, E.R. van der Graaf, Research unit Medical Physics, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), and Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE)
- Subjects
IONS ,PARAMETERIZATION ,Nuclear and High Energy Physics ,Photon ,Proton ,Physics::Medical Physics ,Monte Carlo method ,THERAPY ,Imaging phantom ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,RATIO ,0302 clinical medicine ,Calibration ,Range (statistics) ,Stopping power (particle radiation) ,EXPERIMENTAL-VERIFICATION ,Instrumentation ,Proton therapy ,High accuracy proton range measurement ,RANGE UNCERTAINTIES ,CALIBRATION ,Physics ,NUMBERS ,Relative stopping powers ,Computational physics ,030220 oncology & carcinogenesis - Abstract
Proton therapy is a fast growing treatment modality for cancer and is in selected cases preferred over conventional radiotherapy with photons because of the highly conformal dose distribution that can be achieved with protons due to their steep dose gradients. However, these steep gradients also make proton therapy sensitive to range uncertainties. Proton ranges are calculated from proton stopping powers relative to that in water (Relative Stopping Power, RSP). The RSPs needed for a treatment plan can be estimated from CT (Computed Tomography) data of a patient. High accuracy reference values of RSPs are required to assess the accuracy of these CT based estimates. In this paper we present a water phantom that enables accurate measurement of depth dose profiles in water. Experimental RSPs with a relative standard uncertainty smaller than 0.4% (1 σ ) for samples with a water equivalent thickness of about 2 cm can be derived from the measured depth dose distributions. Most CT based RSP estimates use an approximate RSP model based on the Bethe-Bloch formula without the shell, density, Barkas and Bloch correction. In the Geant4 Monte Carlo code these corrections are included and RSP calculations with this code are expected to be more accurate. In this work, a set of 32 well defined (composition and density), mostly clinically relevant materials is used to assess the correspondence between RSPs that were measured, that were estimated from the approximate RSP model and that were calculated from Monte Carlo simulations. With the measured RSPs we provide a ground-truth bench mark to test the validity of RSPs derived from CT imaging and Monte Carlo simulations.
- Published
- 2018
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