Cell survival curve

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Proportions of surviving mammal cells to radiation as a function of its severity (in Gy). Black lines are acute radiations, while red lines are temporally fragmented. Solid lines represent neutron radiation and dashed lines X-ray radiation.

A cell survival curve is a curve used in radiobiology.

It depicts the relationship between the fraction of cells retaining their reproductive integrity and the absorbed dose.

Conventionally, the surviving fraction is depicted on a logarithmic scale, and is plotted on the y-axis against dose on the x-axis.

Cell survival as a function of radiation dose is graphically represented by plotting the surviving fraction on a logarithmic scale on the ordinate against dose on a linear scale on the abscissa. Cell surviving fractions are determined with in vitro or in vivo techniques. The type of radiation influences the shape of the cell survival curve. Densely ionizing radiations exhibit a cell survival curve that is almost an exponential function of dose, shown by an almost straight line on the log–linear plot. For sparsely ionizing radiation, however, the curves show an initial slope followed by a shoulder region and then become nearly straight at higher doses. Factors that make cells less radiosensitive are: removal of oxygen to create a hypoxic state, the addition of chemical radical scavengers, the use of low dose rates or multifractionated irradiation, and cells synchronized in the late S phase of the cell cycle. Several mathematical methods of varying degrees of complexity have been developed to define the shape of cell survival curves, all based on the concept of the random nature of energy deposition by radiation. The linear quadratic model is now most often used to describe the cell survival curve, assuming that there are two mechanisms to cell death by radiation: A single lethal event or an accumulation of harmful but non-lethal events. Cell survival fractions are exponential functions with a dose-dependent term in the exponent due to the Poisson statistics underlying the stochastic process. Whereas single lethal events lead to an exponent that is linearly related to dose, the survival fraction function for a two-stage mechanism carries an exponent proportional to the square of dose. The coefficients must be inferred from measured data, such as the Hiroshima Leukemia data. With higher orders being of lesser importance and the total survival fraction being the product of the two functions, the model is aptly called linear-quadratic.


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