Current misinterpretations of the linear no-threshold hypothesis.

Abstract

Contrary to the "linear no-threshold hypothesis," which implies that "any amount, however small" of radiation energy is a serious cancer threat, it is shown here that only relatively quite large amounts of such energy can pose such a threat to a person or population. Key to doing this is to make a sharp distinction between the actual amount of the radiation agent imparted energy, epsilon, which must be expressed in units of joules, and the average concentration or density of energy, epsilon/m (i.e., absorbed dose), which is expressed in units of Gy. With any cellular system, e.g., in tissue culture, one can easily adjust the numbers of cells used at each dose point so that a clearly significant number of radiation-induced quantal responses (e.g., mutations, chromosome aberrations, malignant transformations, cell death), in the absorbed dose range of about 0.7 to 3 or more Gy, can be observed. However, if the number of cells is held constant as the absorbed dose is progressively reduced, a point is reached at which no significant excess is observable. This situation is frequently "remedied" by including more cells at that point, which, of course, can increase the number of malignant transformations sufficiently to render the excess statistically valid. However, because both axes are expressed in relative terms, the data point, despite having gained statistical significance, remains at the same location on the graph. This gives the false impression that no more of the agent energy was added or needed to achieve significance. However, if both coordinates are put in absolute terms, i.e., the actual number of quantal responses vs. imparted energy, and the same exercise of "improving the statistics" at low exposures is attempted, it then becomes evident that any point thus rendered significant must be relocated at a substantially higher energy point on the graph. This demonstrates unequivocally the fallacy in the proof of the "linear hypothesis" which is based on agent concentration response curves and not agent amount. It shows that the smaller the agent concentration (absorbed dose; epsilon/m), the larger the amount of radiation energy that must be added to the system in order to demonstrate a radiation-induced response. This suggests a minimum average energy requirement for production of a radiation-attributable cancer. It Ls concluded that the "linear hypothesis" should be abandoned as the cornerstone of radiation protection and practice.