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Ongoing clinical trials designed to explore the use of extracranial stereotactic radiosurgery (ESR) for different tumour sites use large doses per fraction (15, 20, 30 Gy or even larger). The question of whether the linear-quadratic (LQ) model is appropriate to describe radiation response for such large fraction doses has been raised and has not been answered definitively. It has been proposed that mechanism-based models, such as the lethal-potentially lethal (LPL) model, could be more appropriate for such large fraction/acute doses. However, such models are not well characterized with clinical data and they are generally not easy to use. The purpose of this work is to modify the LQ model to more accurately describe radiation response for high fraction/acute doses. A new parameter is introduced in the modified LQ (MLQ) model. The new parameter introduced is characterized based both on in vitro cell survival data of several human tumour cell lines and in vivo animal iso-effect curves. The MLQ model produces a better fit to the iso-effect data than the LQ model. For a high single dose irradiation, the prediction of the MLQ is consistent with that from the LPL model. Unlike the LPL model, the MLQ model retains the simplicity of the LQ model and uses the well-characterized alpha and beta parameters. This work indicates that the standard LQ model can lead to erroneous results when used to calculate iso-effects with large fraction doses, such as those used for ESR. We present a solution to this problem.

The authors have implemented and validated a deformable image registration method to register planning CT images to weekly CBCT images in head-and-neck cancer cases. The accuracy of the TRE values suggests that they can be used as a promising tool for automatic target delineation on CBCT.

Parallel in vitro and in vivo studies provide insight into the relationship between clinical response and intrinsic cellular radiosensitivity and may aid in the development of predictive assays. Compilations of radiosensitivity parameters from in vitro experiments can also be used to examine the potential effectiveness of alternative or new treatment plan designs until enough clinical data become available to directly estimate the requisite radiosensitivity parameters. In this work, survival data for six prostate cancer cell lines (ten datasets total) have been extracted from the literature and re-analysed using the linear-quadratic (LQ) survival model. The paired bootstrap technique for regression is used to compute 95% confidence intervals for the estimated radiosensitivity parameters. LQ radiosensitivity parameters derived from the in vitro data are then compared to radiosensitivity parameters derived from clinical data for prostate cancer. Estimates of alpha range from 0.09 to 0.35 Gy(-1) (all cell lines), and the alpha/beta ratio ranges from 1.09 to 6.29 Gy (all cell lines). Point estimates of the repair half-time (PPC-1, TSU-Pr1, PC-3 and DU-145 cell lines) range from 5.7 to 8.9 h (95% confidence interval from 0.26 h to 10.7 h). Differences in the radiosensitivity parameters determined from the data reported by different laboratories are as large as or larger than the differences in radiosensitivity parameters observed among the various prostate cell lines. The reported studies demonstrate that even seemingly small corrections for dose rate effects, such as those expected in high dose rate (HDR) experiments, can sometimes have a significant impact on estimates of alpha and alpha/beta. By neglecting dose rate effects in the analysis of HDR experiments, estimates of the alpha/beta, ratio may be too high by factors as large as 1.3 to 6.2. The half-time for repair derived from the in vitro experiments appears significantly larger (slower repair rate) than estimates derived from the clinical data. However, the prostate radiosensitivity parameters alpha and alpha/beta may be approximately the same in vitro and in vivo. Most of the in vitro data are consistent with an alpha/beta ratio for prostate cancer less than 3 or 4 Gy.

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