Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Imaging acquisition and processing
Poster (digital)
Physics
A simple proton-radiography system for accurate RSP measurements in proton therapy
Francesco Olivari, The Netherlands
PO-1591

Abstract

A simple proton-radiography system for accurate RSP measurements in proton therapy
Authors:

Francesco Olivari1, Emiel van der Graaf1, Marc-Jan van Goethem1, Sytze Brandenburg1

1University Medical Center Groningen (UMCG), CRCG, Groningen, The Netherlands

Show Affiliations
Purpose or Objective

Proton radiography (pRG) can be used to optimize proton relative stopping power (RSP) predictions from X-ray-imaging-based techniques to improve the quality of proton therapy treatment plans. In this work, we present a simulation study for a simple pRG-system with the potential of being routinely used in the clinic and with sufficient RSP accuracy to be used for improving X-ray-based RSP predictions.

Material and Methods

The simulated pRG-system consists of a thin and finely 2D-pixelated detector measuring the energy deposited by primary protons (protons produced at the source) and their fluence distribution. The mean energy deposited per primary proton is converted into residual range in water with a calibration function. By irradiating the detector without and with a sample placed before the screen the RSP of the material is obtained from the residual range difference and sample thickness.

The RSPs of 12 different materials (Gammex human-tissue-equivalent materials, plastics, metals, and carbon) have been determined from Monte Carlo simulations. To estimate the accuracy of our method in the simulation framework, the RSPs obtained with the screen are compared with reference RSPs obtained from simulations of irradiations of a water tank in which the residual range of protons is determined: the RSP of a material is derived from the range shift with a sample before the tank and the sample thickness.

The system is realized experimentally with a scintillator screen coupled with a CCD camera (Figure 1): the light yield, which is proportional to the energy deposit in the screen, is measured. The mean light yield per incident primary proton is calculated using the data of the fluence distribution scored with simulations as a proxy of the real fluence distribution, and it is converted into residual range in water. For the materials considered in simulations, the experimental RSPs are determined with the screen and compared with reference RSPs derived from residual range measurements in a water tank.


Results

The simulations show an agreement within 1% of the RSPs derived from the screen and those from the water tank for all materials. The experimental results show an agreement within 1% for 6 materials (3 are human-tissue-equivalent), while the agreement is better than 5% for all materials (Table 1). The agreements are similar with the results from Monte Carlo simulations and experiments of [1]. The RSPs of 5 of the Gammex materials were also derived in [2,3]: our results agree with theirs within from 1% to 6%, except for lung (discrepancies around 10%).


Conclusion

The method proposed seems to have the potential to provide RSP predictions with an accuracy better than 1%: in the simulations done, this was possible for all materials considered; in the experiments, for half of the materials.


[1] doi.org/10.1016/j.nimb.2018.09.015

[2] doi.org/10.1088/1361-6560/ab9981

[3] doi.org/10.1088/0031-9155/61/22/8085