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Research of Biological Dose Conversion Platform Based on a Modified Linear Quadratic Model. | LitMetric

AI Article Synopsis

  • The study focuses on enhancing the linear-quadratic (LQ) model to create a new dose conversion platform that better captures radiation responses for high and acute doses.
  • Researchers improved the LQ model by using piecewise fitting to match biological dose curves with experimental data, addressing inaccuracies found in the traditional model for higher doses.
  • The modified model shows that calculated treatment values are consistent regardless of α/β ratios, helping to explain the differences seen in hypofractionated versus conventional dose treatments.

Article Abstract

The study aimed to develop a novel dose conversion platform by improving linear-quadratic (LQ) model to more accurately describe radiation response for high fraction/acute doses. This article modified the LQ model via piecewise fitting the biological dose curve using different fractionated dose and optimizing the consistency between mathematical model and experimental data to gain a more reasonable transform. That mathematical development of the LQ model further amended certain deviations of various cell curves with high doses and implied the rationality of the present model at low dose range. The modified biologically effective dose model that solved the dilemma of inaccurate LQ model had been used in comparing between hypofractionated and conventional fractioned dose. It has been verified that the calculated values are similar in the treatment of same efficacy, no matter what α/β is, and provided a more rational explanation for significant differences among various hypofractionations. The equivalent uniform dose based on the subsection function could represent arbitrary inhomogeneous dose distributions including high-dose fractions, providing a foundation for the implementation of detailed evaluation of different cell dose effects.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6440057PMC
http://dx.doi.org/10.1177/1559325819828623DOI Listing

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