Monte Carlo simulations of nuclear medicine imaging systems

PD Habib ZAIDI, Ph.D


Geneva University Hospital, Division of Nuclear Medicine, CH-1211 Geneva, Switzerland




Abstract. Recent innovations in biomedical imaging research make extensive use of computerized mathematical modelling tools which play an increasingly decisive role within the healthcare technology sector. To understand, visualize or interact with complex anatomical structures and physical and biochemical processes and optimize imaging instrumentation design aspects and data collection protocols, it is necessary to create models that represent these systems. Research in this area is thus aimed at developing models that exhibit sufficient mathematical and physical rigor to capture realism, and which can also support imaging systems design and modelling of patient data.

This talk reflects the tremendous increase in interest in standalone (SPECT and PET) and dual-modality (PET/CT and PET/MR) molecular imaging as both clinical and research imaging modalities in the past decade. It offers an overview of imaging physics with special emphasis on recent progress made in instrumentation design and integration of multimodality imaging in patient diagnosis and therapy planning. The widespread availability of high performance computing and popularity of Monte Carlo simulations stimulated the development of computational anthropomorphic models of the human anatomy and dedicated simulation tools for medical imaging modalities. The use of the Monte Carlo method to simulate radiation transport has become the most accurate means of simulating nuclear medical imaging systems with the aim of optimizing instrumentation design or improving quantitation and predicting absorbed dose distributions and other quantities of interest in diagnostic procedures and radiation treatments of cancer patients using either external or radionuclide radiotherapy. As a consequence of this generalized use, many questions are being raised, primarily about the need and potential of Monte Carlo techniques, but also about how accurate they really are, how close to patient anatomy are the anthropomorphic models used, and what would it take to apply them clinically and make them widely available to the medical imaging community at large. Many of these questions will be answered when Monte Carlo techniques will be implemented and used for more routine calculations and for in-depth investigations.

A detailed description of Monte Carlo modelling of medical imaging systems, the functionality of computer codes widely used and development of anthropomorphic mathematical and voxel-based phantoms will be provided together with practical applications of the Monte Carlo method in a clinical and research environment.