Computational Phantoms for Radiation Dosimetry: A 40-Year History of Evolution
One of the most dynamic areas of research in radiation protection, radiological imaging, and radiotherapy is the modeling of human anatomy for Monte Carlo-based radiation transport and dose simulations. Radiation dosimetry aims to determine the amount and distribution pattern of energy deposited in various parts of the human body by internal or external radiation sources. To protect against occupational exposures, regulatory limits are set for radiation doses associated with radiosensitive organs. In both diagnostic radiology and nuclear medicine, internal and external photons traverse through the body to form an image, depositing radiation energy along the way. Radiotherapy, on the other hand, attempts to deliver a lethal dose to the target while sparing the adjacent healthy tissues from the adverse effects of radiation. Accurate radiation dosimetry is essential but also
quite challenging for three reasons: (1) there are many diverse exposure scenarios resulting in unique spatial and temporal relationships between the source and human body; (2) an exposure can involve multiple radiation types which are governed by rather different radiation physics principles including photons (and gamma rays), electrons, positrons, alpha particles, neutrons, and protons; (3) the human body consists of three-dimensional (3D) inhomogeneous tissues of various geometric shapes and densities, leading to extremely complex radiation interaction patterns. It is not practical to make direct measurement of radiation doses using physical detectors inside the human body. Consequently, dose estimates for select organs of interest have always depended on physical or computational “anthropomorphic models” that mimic the interior and exterior anatomical features of the human body.