A kinetic repair-misrepair-fixation (RMF) model is developed to better link double-strand break (DSB) induction to reproductive cell death. Formulas linking linear-quadratic (LQ) model radiosensitivity parameters to DSB induction and repair explicitly account for the contribution to cell killing of unrejoinable DSBs, misrepaired and fixed DSBs, and exchanges formed through intra- and intertrack DSB interactions. Information from Monte Carlo simulations is used to determine the initial yields and complexity of DSBs formed by low- and high-LET radiations. Our analysis of published survival data for human kidney cells suggests that intratrack DSB interactions are negligible for low-LET radiations but increase rapidly with increasing LET. The analysis suggests that no class of DSB is intrinsically unrejoinable or that DSB reparability is not strictly determined by the number of lesions forming the DSB. For radiations with LET >110 keV/mum, the model predicts that the relative cell killing efficiency, per unit absorbed dose, should continue to increase, whereas data from published experiments indicate a reduced cell killing efficiency. This observation suggests that the Monte Carlo simulation overestimates the DSB yield beyond 110 keV/microm or that other biological phenomena not included in the model, such as proximity effects, are important. For 200-250 kVp X rays ( approximately 1.9 keV/microm), only about 1% of the one-track killing is attributed to intratrack binary misrepair interactions. The analysis indicates that the remaining 99% of the lethal damage is due to other types of one-track damage, including possible unrepairable, misrepaired and fixed damage. Compared to the analysis of the X-ray results, 48% of the one-track lethal damage caused by 5.1 MeV alpha particles (approximately 88 keV/microm) is due to intratrack DSB interactions while the remainder is due to other forms of one-track damage.

Treatment planning tools that use biologically related models for plan optimization and/or evaluation are being introduced for clinical use. A variety of dose-response models and quantities along with a series of organ-specific model parameters are included in these tools. However, due to various limitations, such as the limitations of models and available model parameters, the incomplete understanding of dose responses, and the inadequate clinical data, the use of biologically based treatment planning system (BBTPS) represents a paradigm shift and can be potentially dangerous. There will be a steep learning curve for most planners. The purpose of this task group is to address some of these relevant issues before the use of BBTPS becomes widely spread. In this report, the authors (1) discuss strategies, limitations, conditions, and cautions for using biologically based models and parameters in clinical treatment planning; (2) demonstrate the practical use of the three most commonly used commercially available BBTPS and potential dosimetric differences between biologically model based and dose-volume based treatment plan optimization and evaluation; (3) identify the desirable features and future directions in developing BBTPS; and (4) provide general guidelines and methodology for the acceptance testing, commissioning, and routine quality assurance (QA) of BBTPS.

Ionizing radiation produces both singly and multiply damaged DNA sites. Multiply damaged sites (MDS) have been implicated in radiation-induced cell killing and mutagenesis. The spatial distribution of elementary damages (strand breaks and base damages) that constitute MDS is of special interest, since the complexity of MDS has an impact on damage repair. A fast and easy-to-implement algorithm to simulate the local clustering of elementary damages produced by ionizing radiation is proposed. This algorithm captures the major trends in the DNA damage spectrum predicted using detailed track- structure simulations. An attractive feature of the proposed algorithm is that only four adjustable parameters need to be identified to simulate the formation of DNA damage. A convenient recipe to determine the parameters used in the fast Monte Carlo damage simulation algorithm is provided for selected low- and high-LET radiations. The good agreement among the damage yields predicted by the fast and detailed damage formation algorithms suggests that the small-scale spatial distribution of damage sites is determined primarily by independent and purely stochastic events and processes.

The passage of ionizing radiation through living organisms initiates physical and chemical processes that create clusters of damaged nucleotides within one or two turns of the DNA. These clusters are widely considered an important initiating event for the induction of other biological endpoints, including cell killing and neoplastic transformation. Monte Carlo simulations of the DNA damage formation process are a useful adjunct to experiments because they provide additional information about the spatial configuration of damage within a cluster. In this paper, the fast Monte Carlo damage simulation (MCDS) algorithm is re-parameterized so that yields of double-strand breaks, single-strand breaks and sites of multiple base damage can be simulated for electrons, protons and alpha particles with kinetic energies on the order of GeV. The MCDS algorithm provides a useful, quasi-phenomenological scheme to interpolate damage yields from computationally expensive, but more detailed, track-structure simulations. The predicted characteristics of various classes of damage produced by electrons, protons and alpha particles, such as average number of lesions per DNA damage cluster and cluster length in base pairs, are presented. A study examining the effects on damage complexity of an extrinsic free radical scavenger, dimethyl sulfoxide, is also presented. The reported studies provide new information that will aid efforts to characterize the relative biological effectiveness of high-energy protons and other light ions, which are sometimes used in particle therapy for the treatment of cancer.

The poor treatment prognosis for tumors with high levels of hypoxia is usually attributed to the decreased sensitivity of hypoxic cells to ionizing radiation. Mechanistic considerations suggest that linear quadratic (LQ) survival model radiosensitivity parameters for hypoxic (H) and aerobic (A) cells are related by alphaH = alphaA/oxygen enhancement ratio (OER) and (alpha/beta)H=OER(alpha/beta)A. The OER parameter may be interpreted as the ratio of the dose to the hypoxic cells to the dose to the aerobic cells required to produce the same number of DSBs per cell. The validity of these expressions is tested against survival data for mammalian cells irradiated in vitro with low- and high-LET radiation. Estimates of hypoxic and aerobic radiosensitivity parameters are derived from independent and simultaneous least-squares fits to the survival data. An external bootstrap procedure is used to test whether independent fits to the survival data give significantly better predictions than simultaneous fits to the aerobic and hypoxic data. For low-LET radiation, estimates of the OER derived from the in vitro data are between 2.3 and 3.3 for extreme levels of hypoxia. The estimated range for the OER is similar to the oxygen enhancement ratios reported in the literature for the initial yield of DSBs. The half-time for sublethal damage repair was found to be independent of oxygen concentration. Analysis of patient survival data for cervix cancer suggests an average OER less than or equal to 1.5, which corresponds to a pO2 of 5 mm Hg (0.66%) in the in vitro experiments. Because the OER derived from the cervix cancer data is averaged over cells at all oxygen levels, cells irradiated in vivo under extreme levels of hypoxia (<0.5 mm Hg) may have an OER substantially higher than 1.5. The reported analyses of in vitro data, as well as mechanistic considerations, provide strong support for the expressions relating hypoxic and aerobic radiosensitivity parameters. The formulas are also useful for the analysis of clinical data because the number of radiosensitivity parameters that need to be determined is reduced from four to three without a substantial decrease in the ability of the LQ to accurately predict the surviving faction. The relationships among radiosensitivity parameters imply that the dose to the hypoxic subvolume of the tumor needs to be escalated by a factor of the OER to achieve the same level of tumor control as in well oxygenated tumor regions.