A convolution-based calibration procedure has been developed to use an amorphous silicon flat-panel electronic portal imaging device (EPID) for accurate dosimetric verification of intensity-modulated radiotherapy (IMRT) treatments. Raw EPID images were deconvolved to accurate, high-resolution 2-D distributions of primary fluence using a scatter kernel composed of two elements: a Monte Carlo generated kernel describing dose deposition in the EPID phosphor, and an empirically derived kernel describing optical photon spreading. Relative fluence profiles measured with the EPID are in very good agreement with those measured with a diamond detector, and exhibit excellent spatial resolution required for IMRT verification. For dosimetric verification, the EPID-measured primary fluences are convolved with a Monte Carlo kernel describing dose deposition in a solid water phantom, and cross-calibrated with ion chamber measurements. Dose distributions measured using the EPID agree to within 2.1% with those measured with film for open fields of 2 x 2 cm2 and 10 x 10 cm2. Predictions of the EPID phantom scattering factors (SPE) based on our scatter kernels are within 1% of the SPE measured for open field sizes of up to 16 x 16 cm2. Pretreatment verifications of step-and-shoot IMRT treatments using the EPID are in good agreement with those performed with film, with a mean percent difference of 0.2 +/- 1.0% for three IMRT treatments (24 fields).

A three-dimensional (3D) intensity-modulated radiotherapy (IMRT) pretreatment verification procedure has been developed based on the measurement of two-dimensional (2D) primary fluence profiles using an amorphous silicon flat-panel electronic portal imaging device (EPID). As described in our previous work, fluence profiles are extracted from EPID images by deconvolution with kernels that represent signal spread in the EPID due to radiation and optical scattering. The deconvolution kernels are derived using Monte Carlo simulations of dose deposition in the EPID and empirical fitting methods, for both 6 and 15 MV photon energies. In our new 3D verification technique, 2D fluence modulation profiles for each IMRT field in a treatment are used as input to a treatment planning system (TPS), which then generates 3D doses. Verification is accomplished by comparing this new EPID-based 3D dose distribution to the planned dose distribution calculated by the TPS. Thermoluminescent dosimeter (TLD) point dose measurements for an IMRT treatment of an anthropomorphic phantom were in good agreement with the EPID-based 3D doses; in contrast, the planned dose under-predicts the TLD measurement in a high-gradient region by approximately 16%. Similarly, large discrepancies between EPID-based and TPS doses were also evident in dose profiles of small fields incident on a water phantom. These results suggest that our 3D EPID-based method is effective in quantifying relevant uncertainties in the dose calculations of our TPS for IMRT treatments. For three clinical head and neck cancer IMRT treatment plans, our TPS was found to underestimate the mean EPID-based doses in the critical structures of the spinal cord and the parotids by approximately 4 Gy (11%-14%). According to radiobiological modeling calculations that were performed, such underestimates can potentially lead to clinically significant underpredictions of normal tissue complication rates.

Radiotherapy treatment plan evaluation relies on an implicit estimation of the tumor control probability (TCP) and normal tissue complication probability (NTCP) arising from a given dose distribution. A potential application of radiobiological modeling to radiotherapy is the ranking of treatment plans via a more explicit determination of TCP and NTCP values. Although the limited predictive capabilities of current radiobiological models prevent their use as a primary evaluative tool, radiobiological modeling predictions may still be a valuable complement to clinical experience. A convenient computational module has been developed for estimating the TCP and the NTCP arising from a dose distribution calculated by a treatment planning system, and characterized by differential (frequency) dose‐volume histograms (DDVHs). The radiobiological models included in the module are sigmoidal dose response and Critical Volume NTCP models, a Poisson TCP model, and a TCP model incorporating radiobiological parameters describing linear‐quadratic cell kill and repopulation. A number of sets of parameter values for the different models have been gathered in databases. The estimated parameters characterize the radiation response of several different normal tissues and tumor types. The system also allows input and storage of parameters by the user, which is particularly useful because of the rapidly increasing number of parameter estimates available in the literature. Potential applications of the system include the following: comparing radiobiological predictions of outcome for different treatment plans or types of treatment; comparing the number of observed outcomes for a cohort of patient DVHs to the predicted number of outcomes based on different models/parameter sets; and testing of the sensitivity of model predictions to uncertainties in the parameter values. The module thus helps to amalgamate and make more accessible current radiobiological modeling knowledge, and may serve as a useful aid in the prospective and retrospective analysis of radiotherapy treatment plans.PACS number: 87.53.Tf

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