NDLI: The use of the linear quadratic model in radiotherapy: a review

Content Provider	Springer Nature Link
Author	Jones, L. Hoban, P. Metcalfe, P.
Copyright Year	2001
Abstract	To be able to predict the impact of any radiotherapy treatment the physics of radiation interactions and the expected biological effect for any radiotherapy treatment situation (dose, fractionation, modality) must be both understood and modelled. This review considers the current use and accuracy of the linear quadratic model which can be used to consider the variation in tissue response with fraction size. Cell kill following radiation damage results from damage to the DNA which can take a variety of forms. In many cases the linear quadratic model is used to estimate the relative impact for different situations especially clinical studies relating to fraction size. This is mainly undertaken using parameters derived from the linear quadratic model such as biological effective dose and standard effective dose. The model has also been adapted to consider the effect of overall treatment time, repair during treatment (as occurs for brachytherapy treatments) and other situations. There are some concerns over its use, mainly in the small dose ranges (both total low doses and low doses per fraction) where studies have shown its inaccuracy. In other situations however it does appear to provide a reasonable estimate of relative clinical effect. As with all models, however results should never be considered out of clinical context.
Starting Page	132
Ending Page	146
Page Count	15
File Format	PDF
ISSN	01589938
Journal	Australasian Physics & Engineering Sciences in Medicine
Volume Number	24
Issue Number	3
e-ISSN	18795447
Language	English
Publisher	Springer Netherlands
Publisher Date	2001-01-01
Publisher Place	Dordrecht
Access Restriction	Subscribed
Subject Keyword	linear quadratic model radiobiological modelling fractionation review Biomedicine general Biophysics and Biological Physics Medical and Radiation Physics Biomedical Engineering Theoretical, Mathematical and Computational Physics
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Physics and Astronomy Biophysics Biomedical Engineering

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