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. 1998 Jul 1;41(4):945-50.
doi: 10.1016/s0360-3016(98)00128-x.

A little to a lot or a lot to a little: is NTCP always minimized in multiport therapy?

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Free article

A little to a lot or a lot to a little: is NTCP always minimized in multiport therapy?

M Zaider et al. Int J Radiat Oncol Biol Phys. .
Free article

Abstract

Purpose: We address the question of whether or not, for the same average (or integral) dose, a smaller uniform dose to an entire normal tissue structure always results in a lower normal tissue complication probability (NTCP) than does a proportionally larger dose to a partial volume of the same structure.

Methods and materials: A recent compilation of NTCP data and two theoretical formulations of the dependence of NTCP on dose and partial volume irradiated-the Lyman probit equation and the binomial model-are used to examine this question. Both models fit equally well available NTCP data.

Results: Empirical data indicate that for lung, kidney, and possibly liver (but not for esophagus, brain, or heart), given a fixed tumor dose and fixed integral dose, NTCP can be minimized by irradiating a partial volume fraction rather than the entire normal organ. The binomial model supports this interpretation, whereas the probit model predicts that for all organs uniform irradiation of the whole organ always results in the lowest possible NTCP.

Conclusions: In contrast to what is commonly believed, this study suggests that for at least two normal tissues, namely lung and kidney, there may be situations where "a lot to a little" (i.e., fewer treatment ports) will result in higher tumor control probability and better treatment plan than "a little to a lot" (i.e., multifield treatment). This finding, which is independent of the binomial or probit models used here, depends only on the accuracy of the empirical NTCP data. It is also interesting to note that: a) lung and kidney are commonly classified as parallel tissues, while the others have more of a serial architecture; and b) the choice of the NTCP model can have a profound impact on treatment planning decisions.

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