Nearly all energy deposition by ionizing radiation, including indirectly ionizing radiation, is the result of the interaction of a charged particle with an atom or molecule of the irradiated material. Those interactions occur randomly along the paths of the charged particles and result in substantial variation in the energy lost by the particle in successive short increments of its path. Nonstochastic dosimetry quantities, linear energy transfer and absorbed dose, describe energy loss and deposition in terms of the expectation value at a point in space and are ideal descriptors of irradiation in many situations. However, at low absorbed doses, the deposition of energy in small volumes is strongly influenced by random variations in the number and magnitude of the charged particle interactions in the volume and a probability density function (PDF) is needed to fully describe the energy imparted. The study of the stochastic nature of energy deposition has come to be known as microdosimetry, while the study of the variation in the number of ion pairs produced in very small volumes is known as nanodosimetry.
The measurement of the PDF of energy imparted in micrometer scale objects, using low-pressure proportional counters or semiconductor detectors, is a powerful tool for evaluating unknown radiation fields such as in space and near high- energy-particle accelerators. Experimental evaluation of the PDF of energy imparted has also provided an improved understanding of the variation of initial damage in biological targets and now provides data for validating the results of track structure simulations used to explore the consequences of irradiation modalities. An understanding of the stochastic nature of energy deposition, or ionization, facilitates exploration of the consequences of irradiation and serves as a basis for modeling effects ranging from soft errors in microcomputers to mutations in biological systems and effectiveness of ion therapy. This report describes the factors influencing the stochastic nature of energy deposition, experimental and computational methods for evaluating it, and applications made possible by applying an understanding of the stochastic nature of energy imparted.