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Andrew W Beavis

Publications and source records attributed to Andrew W Beavis.

2 recordsLinked to original sources
PubMed2002

Influence of dose calculation model on treatment plan evaluation in conformal radiotherapy: a three-case study.

In modern conformal radiotherapy (CRT), we attempt to increase its therapeutic ratio, thus improving the survival chances and/or quality of life for patients. It is common to acknowledge that poor local tumor control or increased normal tissue complications may arise from inaccurate targeting of the tumor, failure to conform the high-dose distribution to the target volume, and inaccurately delivered radiation doses. A further cause for concern is the influence that errors or inaccuracies in the dose calculation may have on the management of radiation therapy. Such errors arise from inherent limitations in the calculation algorithm used, which are more significant in some anatomical sites than others. Furthermore, an estimate of the therapeutic ratio is given by the ratio of tumor control probability (TCP) and normal tissue complication probability (NTCP). The effectiveness of these predictive indicators also depends on the accuracy of the calculated dose distributions in the target and surrounding normal structures. In this work, we compared CRT dose distributions of plans for the treatment of prostate, head-and-neck, and lung tumors using the measurement-based Clarkson and model-based Superposition dose calculation algorithms. Dose-volume histograms (DVHs) for the planning target volume (PTV) and sensitive structures, as well as NTCP and TCP, were compared. Dose distributions, observed in the lung and head-and-neck plans, vary significantly with respect to dose conformity as a function of algorithm used. Differences in the calculated maximum dose of up to 14% were observed in the PTV and sensitive structures for the lung and head-and-neck Clarkson-based plans, respectively, compared to the Superposition-based plans. Furthermore, a difference in the biological outcomes of up to 14% in the NTCP and 4% in the TCP was noticed. The CRT plans show the importance of accurate modeling of the effect of tissue inhomogeneities on dose distributions in the target and critical structures for lung and head-and-neck treatments.

Algorithms↗
PubMed2002

Beyond bixels: generalizing the optimization parameters for intensity modulated radiation therapy.

Intensity modulated radiation therapy (IMRT) treatment planning systems optimize fluence distributions by subdividing the fluence distribution into rectangular bixels. The algorithms typically optimize the fluence intensity directly, often leading to fluence distributions with sharp discontinuities. These discontinuities may yield difficulties in delivery of the fluence distribution, leading to inaccurate dose delivery. We have developed a method for decoupling the bixel intensities from the optimization parameters; either by introducing optimization control points from which the bixel intensities are interpolated or by parametrizing the fluence distribution using basis functions. In either case, the number of optimization search parameters is reduced from the direct bixel optimization method. To illustrate the concept, the technique is applied to two-dimensional idealized head and neck treatment plans. The interpolation algorithms investigated were nearest-neighbor, linear and cubic spline, and radial basis functions serve as the basis function test. The interpolation and basis function optimization techniques were compared against the direct bixel calculation. The number of optimization parameters were significantly reduced relative to the bixel optimization, and this was evident in the reduction of computation time of as much as 58% from the full bixel optimization. The dose distributions obtained using the reduced optimization parameter sets were very similar to the full bixel optimization when examined by dose distributions, statistics, and dose-volume histograms. To evaluate the sensitivity of the fluence calculations to spatial misalignment caused either by delivery errors or patient motion, the doses were recomputed with a 1 mm shift in each beam and compared to the unshifted distributions. Except for the nearest-neighbor algorithm, the reduced optimization parameter dose distributions were generally less sensitive to spatial shifts than the bixel optimization. These results indicate that significant reductions in optimization parameter sets can be accomplished with a negligible reduction in dose distribution quality. The decreased parameters can result in a reduced optimization time, or can be used to allow an improved and consequently more computation-intensive dose calculation for more accurate dose calculations during the optimization process. The basis functions may be generalized to model the accelerator motion for direct computation of the accelerator motion sequence, removing the need for developing an independent leaf sequence step.

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