Computational Phantoms for Organ Dose Calculations in Radiation Protection and Imaging

Abstract

Dosimetry for ionizing radiation has to do with the determination of amount and distribution pattern of the energy deposited in a part or parts of the human body from internal or external radiation sources. To protect against occupational exposures, dose limits for radiosensitive organs are recommended by international organizations and are adopted as national regulations. In both diagnostic radiology and nuclear medicine, X-ray photons and gamma rays traverse through body tissues to form images of the anatomy, depositing radiation energy in organs along the pathway via secondary electrons. 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, each of which is governed by different radiation physics principles, such as photons (X-ray photons, gamma rays, and positrons), electrons, alpha particles, neutrons, and protons; (3) the human body consists of a large number of anatomical structures of diverse shape, composition and density, leading to complex radiation interaction patterns. Since it is inconvenient to place a dosimeter inside the human body, organ dose estimates have been obtained mostly using a physical phantom or a computational phantom that mimics the interior and exterior anatomical features of the human body.Historically, the term phantom was used in most radiological science literature to mean a physical model of the human body. In the radiation protection community, however, the term has also been used to refer to a mathematically defined anatomical model that is distinctly different from a physiologically based model such as that related to respiration or blood flow. In this chapter, the phrases, ''computational phantom'' and ''physical phantom,'' are used to avoid confusion.

The stochastic digital human is now enrolling for in silico imaging trials—methods and tools for generating digital cohorts

“…These computational models have proved useful in areas of quality control of imaging systems [20,21] and in radiation dosimetry [22]. Even with more sophisticated geometrical structures [23][24][25] and more spatial detail, these approaches lack the ability to accurately represent the statistical variability found in humans, organs and tissues. While these simpler models remain practical and useful for some tasks, the lack of realism and variability makes them unsuitable for generating digital humans for in silico imaging trials.…”