The modified linear-quadratic model of Guerrero and Li can be derived from a mechanistic basis and exhibits linear-quadratic-linear behaviour.
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Animals↗
Biomedical subjects
Marco Carlone
Publications and source records attributed to Marco Carlone.
Radiobiological parameters suitable for modeling individual outcomes cannot be obtained by analyzing heterogeneous population data with homogeneous tumor control model: in regard to D'Souza et al. (Int J Radiat Oncol Biol Phys 2004;58:1540-1548).
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Brachytherapy↗
TCP isoeffect analysis using a heterogeneous distribution of radiosensitivity.
A formula for the alpha/beta ratio is derived using the heterogeneous (population averaged) tumor control model. This formula is nearly identical to the formula obtained using the homogeneous (individual) tumor control model, but the new formula includes extra terms showing that the alpha/beta ratio, the ratio of the mean value of a divided by the mean value of beta that would be observed in a patient population, explicitly depends on the survival level and heterogeneity. The magnitude of this correction is estimated for prostate cancer, and this appears to raise the mean value of the ratio estimate by about 20%. The method also allows investigation of confidence limits for alpha/beta based on a population distribution of radiosensitivity. For a widely heterogeneous population, the upper 95% confidence interval for the alpha/beta ratio can be as high as 7.3 Gy, even though the population mean is between 2.3 and 2.6 Gy.
Cell Survival↗
Comparison of alpha/beta estimates from homogeneous (individual) and heterogeneous (population) tumor control models for early stage prostate cancer.
Radiobiological parameter estimates for prostate cancer are obtained from both a homogeneous (individual) and heterogeneous (population) tumor control model based on Poisson statistics and the linear quadratic model of cell survival. Parameter estimates for both models are highly correlated: statistically equivalent fits are achievable using either (1) linear quadratic (LQ) parameters with low numbers of radioresistant tumor stem cells, or (2) LQ parameters with corresponding larger number of radiosensitive tumor stem cells. A theoretical framework is developed to explain this correlation. A Monte Carlo error analysis based on binomial statistics is used to estimate confidence intervals for all parameter estimates. It was found that both the homogeneous and heterogeneous models produce approximately equivalent estimates of radiobiological parameters, including the alpha/beta ratio. However, the 95% confidence interval for the alpha/beta ratio derived from the heterogeneous model are considerably larger than those derived from the homogeneous model, which indicate the homogeneous model overestimates the statistical significance of the alpha/beta estimate.
Cell Survival↗