Monte Carlo N-Particle Code Analysis of Multiple Gamma Camera Components from Varying Manufacturers

Carlos Nicolas Delgado

Abstract

TS33

Introduction: There is only one certainty about radioactive decay: its unpredictability. Nuclear physicists have invented ways to detect radioactive decay, and these detectors have a variety of components which affect their intrinsic and extrinsic detection efficiency. This begs the question, how do camera manufacturers determine the efficiency of their products? Originating from the Manhattan Project, the Monte Carlo Algorithm is an analytical mathematical tool used by nuclear physicists to study the designs of radiation detectors when a random variable, radioactive decay, determines the research outcome (1-2). The algorithm has been used to simulate the behavior of radioactive isotopes, creating millions of theoretical photon interactions for Nuclear Medicine, SPECT, CT and PET systems (1-2). This algorithm can test specific collimator thicknesses, crystal composition and thicknesses, photomultiplier tube arrays, and operational matrix sizes among many other variables for a range of radionuclide sources in order to determine which instrumentation specifications produce images with high spatial resolution (1-2). Manufacturers such as GE, Siemens, Phillips and Mediso utilize the MCNP code to test detector component variations for multiple radioactive sources (3). The program simulates radioactive decay for multiple isotopes, and this theoretical data is then compared to data obtained from actual radioactive point sources to analyze detector efficiency, spatial resolution, energy resolution, and detection quantum efficiency as they develop new machinery and evaluate cost efficiency; the latest version is the Monte Carlo N-Particle code (MCNP) (1-2-3). The purpose of this investigation is to analyze the accuracy of the MCNP’s ability to simulate radioactive decay behavior, and compare the theoretical data to actual data obtained from experiments with radioactive sources. Studying this relationship will help determine the MCNP’s validity in testing detector efficiency and provide avenues for future research.

Methods: Data was gathered from studies conducted by CDC (Centers for Disease Control and Prevention) analysts, manufacturer development, and independent researchers which focus on specific components such as collimators or scintillation crystals to analyze individual component efficiency in relation to total camera efficiency. Studies which compare components from multiple manufacturers will be used to determine MCNP validity in assessing quality control and efficiency of multiple gamma camera systems.

Results: The MCNP code provided data to simulate the necessary interactions to detector efficiency considering collimator, scintillation crystal, and image reconstruction algorithms for multiple sources of radiation across the four discussed manufacturers (5-6-7-8-9). Figures 1 and 2 provide an overview of simulated collimator data and detective quantum efficiency (DQE) v.s. spatial frequency for the defined manufacturers, while figures 3 and 4 provide an example of how Siemens uses the MCNP program to test detector specifications (5-6). The MCNP program operates at a 2% error range when comparing simulated values to experimental results with radioactive sources, indicating it's a valid tool for determining detector efficiency in camera development (7).

Conclusions: MCNP is a valid tool for analyzing detector efficiency and determining which components across manufacturers could create an amalgamated camera for each energy window, standardizing efficiency across all manufacturers. This would hopefully cut manufacturing costs and make nuclear medicine cameras more accessible to other countries. Additionally, a more efficient detection system would reduce scan times, patient doses, and radiation transportation dangers when shipping bulk doses over large distances, hence reducing occupational exposure. As nuclear medicine technology develops, so will its ability to become a safer, more accessible practice on a global scale, and MCNP will have an integral role in this process.