Monte Carlo Simulations article

Since 1981, RTI has provided solutions for non-invasive x-ray quality assurance (QA) measurements and continues to deliver reliable results to ensure patient safety within most common clinical modalities such as radiography, mammography, CT, dental and fluoroscopy.

Research and development is an important branch of RTI’s mission. Future products are developed in a way that combines empirical knowledge, acquired through the company’s history, and Monte Carlo simulations for a more detailed understanding of the physical processes behind solid-state sensors used for x-ray QA.

Building the bridge between Monte Carlo and x-ray QA

The physical principles of non-invasive QA measurements lie in the interaction of radiation with matter. With the help of detectors, a signal can be extracted from the x-ray beam which is further analyzed in terms of radiation parameters such as air kerma, kVp, HVL and many more.

A single x-ray exposure results in a chain of energy transfer events which leads to the deposition of dose within the medium. All related basic interaction mechanisms are well known and depend on the probabilistic nature of the energy transport between x-ray photons and the interacting medium.

Clinical x-rays exhibit a complex spectrum of energies and many event chains should be considered for a fully analytic description of one exposure and a large number of random processes would have to be included and repeated for millions of particles. Here, Monte Carlo (MC) methods can be utilized to increase RTI’s expertise in the field of x-ray QA.

MC simulations use repeated random sampling to predict the outcome of deterministic processes and complex systems, with many coupled degrees of freedom, can be modelled. They are well suited to compute the energy transport of a particle based on probability distributions and make it possible to record all possible interactions, until the initial particle is absorbed and related event chains are terminated.

Confirming the presence: MC model of Cobia

To confirm that MC methods are a helpful tool for RTI’s present and future work, a model description of the Cobia is evaluated with PENELOPE, a Fortran-based MC code for simulating particle transport. To run the computation, an input file is defined. Required parameters include particle energy or spectrum, geometric specification of the interacting media and boundary conditions, such as material properties and interacting probabilities, as well as intended output data.

Following output examples are of specific interest when evaluating RTI detectors:

Results of computing pulse height spectra offer the possibility to follow spectral changes upon attenuation and lead to a deeper understanding of material choices, cf. Figure 1.
Calculation of energy deposition can be used to estimate the sensor signal and related QA parameters like dose and HVL, cf. Figure 2.

RTI has found that MC simulations manage to calculate signal ratios of typical Cobia measurements. They are also a useful tool for R&D projects regarding maintenance and future product development. MC methods provide opportunities for testing detector configurations, performing detailed attenuation studies, and computing x-ray spectra when clinical systems are unavailable. Development time and cost decrease, knowledge increases and resources are saved.

Of course, validation continues to be necessary but the advantages of using MC methods in early R&D studies are obvious and RTI will continue to use modern methods to provide modern QA Solutions.

Figure 1: Pulse Height Spectra for the 4 diode rings of the Cobia detector after passing different filtrations of brass.

The shape of the energy spectrum changes depending on attenuation of the primary radiation. Soft radiation, i.e. low energetic photons, is absorbed by the filter with increasing thickness of brass (top to bottom). The total intensity decreases with the fraction of characteristic x-rays increasing, cf. beam hardening.

Figure 2:
Cobia measurements are performed at different settings of kVp. The measured signal ratios used for the kV/TF algorithm are presented by dotted lines.

Comparison is made to simulated signal ratios, represented by solid lines, with ratios being calculated from the MC simulation of energy deposition within the diode rings (S1-S4). RQR spectra for MC input files are comparable to kVp settings.

Monte Carlo Simulations Poster (PDF)

Petty Cartemo. Since 2016, Dr. Petty Cartemo has been an R&D physicist at RTI Headquarters, Mölndal, Sweden. She works with the development of mathematical models for the measurement of QA relevant parameters, sensor development as well as calibration methods.

Petty has a doctoral degree in Nuclear Engineering and is specialized on experimental techniques within radiation protection and nuclear safety.

Published in EFOMP News, Issue 04/2020 Winter, page 43-44