A nanodosimetry-based linear-quadratic model of cell survival for mixed-LET radiations

Determination of the Effective Local Lethal Function for the NanOx Model

NanOx is a biophysical model recently developed in the context of hadrontherapy to predict the cell survival probability from ionizing radiation. It postulates that this may be factorized into two independent terms describing the cell response to two classes of biological events that occur in the sequence of an irradiation: the local lethal events that occur at nanometric scale and can by themselves induce cell death, and the non-local lethal events that lead to cell death by an effect of accumulation and/or interaction at a larger scale. Here we address how local lethal events are modeled in terms of the inactivation of undifferentiated nanometric targets via an "effective local lethal function F", which characterizes the response of each cell line to the spectra of "restricted specific energy". F is initially determined as a linear combination of basis functions. Then, a parametric expression is used to reproduce the function's main features, a threshold and a saturation, while at the same time reducing the number of free parameters. This strategy was applied to three cell lines in response to ions of different type and energy, which allows for benchmarking of the α(LET) curves predicted with both effective local lethal functions against the experimental data.

Characterisation of a setup for mixed beam exposures of cells to 241Am alpha particles and X-rays

Exposure of humans to mixed fields of high- and low-linear energy transfer (LET) radiation occurs in many situations-for example, in urban areas with high levels of indoor radon as well as background gamma radiation, during airplane flights or certain forms of radiation therapy. From the perspective of health risk associated with exposure to mixed fields, it is important to understand the interactions between different radiation types. In most cellular investigations on mixed beams, two types of irradiations have been applied sequentially. Simultaneous irradiation is the desirable scenario but requires a dedicated irradiation facility. The authors have constructed a facility where cells can be simultaneously exposed to (241)Am alpha particles and 190-kV X-rays at 37°C. This study presents the technical details and the dosimetry of the setup, as well as validates the performance of the setup for clonogenic survival in AA8 Chinese hamster ovary cells. No significant synergistic effect was observed. The relative biological effectiveness of the alpha particles was 2.56 for 37 % and 1.90 for 10 % clonogenic survival.

A mathematical framework for separating the direct and bystander components of cellular radiation response

A mathematical model for fractional tumor cell survival was developed incorporating components of cell killing due to direct radiation interactions and bystander signals resulting from non-local dose deposition.

MATERIAL AND METHODS

Three possible mechanisms for signal production were tested by fitting predictions to available experimental results for tumor cells (non-small cell lung cancer NCI-H460 and melanoma MM576) exposed to gradient x-ray fields. The parameter fitting allowed estimation of the contribution of bystander signaling to cell death (20-50% for all models). Separation of the two components of cell killing allowed determination of the α and β parameters of the linear-quadratic model both with and without the presence of bystander signaling.

RESULTS AND DISCUSSION

For both cell lines, cell death from bystander signaling and direct radiation interactions were comparable. For NCI-H460 cells, the values for α and β were 0.18 Gy⁻¹ and 0.10 Gy⁻² respectively when direct and bystander effects were combined, and 0.053 Gy⁻¹ and 0.061 Gy⁻² respectively when the signaling component was removed. For MM576, the corresponding respective values were 0.09 Gy⁻¹ and 0.011 Gy⁻² for the combined response, and 0.014 Gy⁻¹ and 0.002 Gy⁻² for the isolated direct radiation response. The bystander component in cell death was found to be significant and should not be ignored. Further experimental evidence is required to determine how these results translate to the in vivo situation where tumor control probability (TCP) models that currently assume cellular independence may need to be revised.

Cellular apoptosis by nanosecond, high-intensity electric pulses: model evaluation of the pulsing threshold and extrinsic pathway

A simple, bistable rate-equation based model is used to predict trends of cellular apoptosis following electric pulsing. The caspase-8 extrinsic pathway with inherent delays in its activation, cytochrome c release, and an internal feedback mechanism between caspase-3 and cleavage of Bid are incorporated. Results obtained were roughly in keeping with the experimental cell-survival data and include an electrical pulse-number threshold followed by a near-exponential fall-off. The extrinsic caspase-8 mechanism is predicted to be more sensitive than the mitochondrial intrinsic pathway for electric pulse induced cell apoptosis. Also, delays of about an hour are predicted for detectable molecular concentration increases following electrical pulsing. Finally, our results suggest that multi-needle electrode systems with adjustable field orientations would likely enhance apoptosis in the context of pulsed voltage-induced inactivation of tumor cells.

Biological optimization of tumor radiosurgery

In tumor radiosurgery, a high dose of radiation is delivered in a single session. The question then naturally arises of selecting an irradiation strategy of high biological efficiency. In this study, the authors propose a mathematical framework to investigate the biological effects of heterogeneity and rate of dose delivery in radiosurgery. The authors simulate a target composed by proliferating and hypoxic tumor cells as well as by normal tissue. Treatment outcome is evaluated by a functional of the dose distribution that counts the LQ-surviving fractions of each cell type. Prescriptions on intensity, homogeneity, and duration of radiation delivery are incorporated as constraints. Biological optimization is performed by means of calculus of variation techniques. For a fixed dose, increasing heterogeneity considerably improved the biological performance. The dose peaks progressively concentrated in the hypoxic and proliferating areas, while damage to normal tissue was reduced. The duration of delivery, optimized in the range of 1-30 min and for various tumor/normal characteristic DNA repair time ratios, coincided with the maximum allowed value. It resulted in a poor therapeutic gain, which was positively correlated with the tumor/normal characteristic DNA repair time ratio. The mathematical framework described in this work allows one to design the dose distribution and dose rate of biologically based plans for tumor radiosurgery. It may be thus integrated into the available simulation softwares to assist in treatment planning.

Experimental validation of the new nanodosimetry-based cell survival model for mixed neutron and gamma-ray irradiation

The new nanodosimetry-based linear-quadratic (LQ) formula has been reviewed for mixed-LET irradiation. V-79 Chinese hamster cells have been irradiated with a mixed-LET field of fission neutrons and gamma rays at the University of Maryland Training Reactor (MUTR). The results show that the experimental survival curve agrees well with that predicted by the new nanodosimetry-based LQ model. The experimental study described in this note, therefore, serves as a validation for the new model to be used for mixed-LET radiotherapies, e.g. 252Cf brachytherapy.

Nanodosimetry in a clinical neutron therapy beam using the variance-covariance method and Monte Carlo simulations

Nanodosimetric single-event distributions or their mean values may contribute to a better understanding of how radiation induced biological damages are produced. They may also provide means for radiation quality characterization in therapy beams. Experimental nanodosimetry is however technically challenging and Monte Carlo simulations are valuable as a complementary tool for such investigations. The dose-mean lineal energy was determined in a therapeutic p(65)+Be neutron beam and in a (60)Co gamma beam using low-pressure gas detectors and the variance-covariance method. The neutron beam was simulated using the condensed history Monte Carlo codes MCNPX and SHIELD-HIT. The dose-mean lineal energy was calculated using the simulated dose and fluence spectra together with published data from track-structure simulations. A comparison between simulated and measured results revealed some systematic differences and different dependencies on the simulated object size. The results show that both experimental and theoretical approaches are needed for an accurate dosimetry in the nanometer region. In line with previously reported results, the dose-mean lineal energy determined at 10 nm was shown to be related to clinical RBE values in the neutron beam and in a simulated 175 MeV proton beam as well.