Radiation transmission-based measurements of two-phase flow phenomena have become increasingly popular in the past decades. The advancement in radiation detection technology has propelled detector efficiency, spatial resolution, and acquisition rates, which make these types of tools attractive for research studies. Conventional instrumentation deployed in two-phase flow measurements such as wire mesh sensors and needle probes are intrusive and ill-suited for high-temperature and high-pressure environments. Radiation based measurements do not suffer from these drawbacks due to the non-intrusive nature of these system, which further strengthens the case for the application of these method. The accuracy of radiation-transmission measurements of two-phase flows is dependent on the type of radiation, geometric arrangement, elemental composition of the working fluid, and temporal behavior of the flow. The latter temporal dependency results in an inherit bias arising from the radiation transmission process and the measurement conditions. This phenomenon leads to a deviation between the estimated and the ideal void fraction; this deviation is called dynamic bias and is often neglected in radiation transmission measurements reported in the open literature. This error was first theorized in 1971, since then, only a handful of studies have attempted to quantify the effects of this error using idealized signals. The present study characterizes the behavior of the dynamic bias in two-phase flow measurements as a function of the sampling integration period and other relevant parameters. The derived expression is used to numerically estimate the dynamic bias build-up for different type of signals (rectangular, sinusoidal, and triangular functions). Noise is then added to the signal for two separate cases, a fixed activity source representative of radioisotopic sources, and an adjustable emission source representative of x-ray tubes. The sampled void fraction and its variance, as well as the dynamic bias variance are analyzed for these cases. Additional simulations are then carried out for signals representative of two-phase flows using actual experimental data obtained with wire mesh sensors in the TOPFLOW facility. The experimental data used for the characterization of the dynamic bias range from bubbly to annular flow regimes.