In this study, a measurement protocol is presented that improves the precision of dose measurements using a flat-bed document scanner in conjunction with two new GafChromic film models, HS and Prototype A EBT exposed to 6 MV photon beams. We established two sources of uncertainties in dose measurements, governed by measurement and calibration curve fit parameters contributions. We have quantitatively assessed the influence of different steps in the protocol on the overall dose measurement uncertainty. Applying the protocol described in this paper on the Agfa Arcus II flat-bed document scanner, the overall one-sigma dose measurement uncertainty for an uniform field amounts to 2% or less for doses above around 0.4 Gy in the case of the EBT (Prototype A), and for doses above 5 Gy in the case of the HS model GafChromic film using a region of interest 2 X 2 mm2 in size.

Percentage depth dose (PDD) distributions and beam profiles of very small diameter (1.5-5 mm) megavoltage radiosurgical beams calculated with Monte Carlo (MC) technique critically depend on the diameter of the circular focal spot used in the simulation: The smaller is the field diameter, the larger is the effect. Thus, in simulations of radiosurgical fields that have diameters of the order of the focal spot size, an accurate focal spot geometry should be used. We used a simplified moving slit technique in conjunction with a diode detector for evaluation of the focal spot size and shape of a megavoltage 6 MV linac as well as for determination of the equivalent focal spot diameter of the linac for use in MC simulations. The measured total diode signal contains three components: A direct focal spot signal, a background signal, and an extra-focal radiation signal. A single profile scan of the focal spot signal is Gaussian like in shape, and its full width at half maximum is used to define the focal spot dimension for this scan. The focal spot of our 6 MV linac is approximated with a Gaussian circle, and when the geometry of the effective focal spot circle is used in MC simulations, the agreement between MC-calculated and measured PDD distributions as well as beam profiles is good even for radiosurgical fields as small as 1.5 mm in diameter. Our results also confirm that matching the penumbral areas of accurately measured large-field beam profiles to the same areas of the MC-calculated beam profiles reliably leads to a realistic effective focal spot size for use in MC simulations of very small diameter beams.

In the current state-of-the art of clinical inverse planning, the design of clinically acceptable IMRT plans is predominantly based on the optimization of physical rather than biological objective functions. A major impetus for this trend is the unproven predictive power of radiobiological models, which is largely due to the scarcity of data sets for an accurate evaluation of the model parameters. On the other hand, these models do capture the currently known dose-volume effects in tissue dose-response, which should be accounted for in the process of optimization. In order to incorporate radiobiological information in clinical treatment planning optimization, we propose a hybrid physico-biological approach to inverse treatment planning based on the application of a continuous penalty function method to the constrained minimization of a biological objective. The objective is defined as the weighted sum of normal tissue complication probabilities evaluated with the Lyman normal-tissue complication probability model. Physical constraints specify the admissible minimum and maximum target dose. The continuous penalty function method is then used to find an approximate solution of the resulting large-scale constrained minimization problem. Plans generated by our approach are compared to ones produced by a commercial planning system incorporating physical optimization. The comparisons show clinically negligible differences, with the advantage that the hybrid technique does not require specifications of any dose-volume constraints to the normal tissues. This indicates that the proposed hybrid physico-biological method can be used for the generation of clinically acceptable plans.

A method that allows a straightforward implementation of dose-volume constraints in gradient algorithms for inverse treatment planning is presented. The method is consistent with the penalty function approach, which requires the formulation of an objective function with penalty terms proportional to the magnitudes of constraint violations. Dose constraints with respect to minimum and maximum target dose levels are incorporated in quadratic, dose-penalty terms. Analogously, quadratic volume-penalty terms in the objective function reflect the violation of dose-volume constraints imposing limits on the fractions of healthy organ volumes that can be irradiated above specified dose levels. It has been demonstrated that within the framework of this formulation neither modified objective functions nor finite difference gradient calculations are necessary for the incorporation of gradient minimization algorithms. As an example, a simple steepest descent algorithm is presented along with its application to illustrate prostate and lung cases.