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Radiation Exposures

Chapter

Abstract

The discoveries of radioactivity and ionizing radiation in the late nineteenth century created an unprecedented revolution in the medical sciences. The ability to noninvasively image internal structures of the body and the ability to treat diseases with radiation sources changed medicine forever, and the changes and improvements continue to this day. Soon after the discovery of the marvelous powers of radiation, we became aware of the possible deleterious effects on the human body of excessive radiation exposures. Effects on the eyes and skin were observed soon after protracted exposures, and in a short time, elevated leukemia rates were seen among radiologists. Ionizing radiation is similar to electricity – its myriad uses in our lives make it impossible to imagine a world without it, and when properly used it provides enormous benefits. Misuse, however, can result in injury or even death. As the majority of pediatric nuclear medicine studies are for diagnostic purposes, the levels of activity are low, and the risk of short-term (“nonstochastic”) effects is not of concern. The focus is on the proper management of risks and benefits and avoidance of misadministrations. In therapeutic applications, the goal is to ensure effective treatment of disease while managing negative effects on normal tissues, often the active marrow. Another chapter in this text will deal specifically with dose reduction and optimization; this chapter will discuss methods and models for calculation of radiation dose for radiopharmaceuticals. Radiation dose from computed tomography (CT) will be briefly discussed as well, as positron emission tomography (PET) and single photon emission computed tomography (SPECT) studies are very commonly performed with a CT component, and the total radiation dose to the subject will be from both the nuclear medicine and CT components.

Keywords

Single Photon Emission Compute Tomography Compute Tomography Dose Index Medical Internal Radiation Dose Tissue Weighting Factor Compute Tomography Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleUSA

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