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A New Formula of NTCP Based On LKB Model

J Zhang1*, J Shen2, Z Dai3, C Chen4, H Liu5, (1) Zhongnan Hospital of Wuhan University, Wuhan, ,CN, (2) Zhongnan hospital of Wuhan University, Wuhan, ,CN, (3) Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, 44, CN, (4) ZhongNan Hospital of Wuhan University, Wuhan, ,CN, (5) Zhongnan hospital of Wuhan University, Wuhan, ,CN,

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: facilitate the use of quantitative modeling of biological effects for treatment planning, an a simpler function equivalent to the Lyman formula [1] is introduced as for calculating normal tissue complication probability (NTCP).

Methods: first provide an approximation of Lyman-Kutcher–Burman (LKB) formula with three parameters (n, m, TD50) as a function of equivalent uniform dose(EUD). Organ parameters for the new formula are given in terms of Lyman model m and TD50, and conversely m and TD50 are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model.

Results: new formalism with sigmoidal shape indicates symmetry about TD50, which is similar to LKB model, and the difference of NTCP between the two formula are smaller than 0.1%. The parameters (n, m, TD50) are fitted to the tolerance data of Emani at al [2] based on strict mathematical deduction. The model parameters obtained in this work can match the data better than that given by Burman et al, since data fitting in their work were done “by eye” rather than a statistical method. Most of parameters in present study are very closed to that of Burman. A mistake for the parameters of larynx in Burman’s data is also detected and corrected in present study.


Conclusion: We have found a formula to represent NTCP as a function of EUD, and this formula may well be useful. Tables of OAR parameters have been given, fitted with published clinical data. Parameters obtained in this study are more mathematical and can match the data better than previous work.

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