Anatomy-based Dose Optimization Research Articles

TU-D-BRB-03: Enforcing Maximum Dwell Times in High Dose Rate Brachytherapy Highlights the Tradeoff between Small Dwell Time Gradients and Dose Coverage

Purpose Applicator-based dose optimization (forward planning) emphasizes dwell time homogeneity to avoid regions of exceptionally high dose concentration. Anatomy-based dose optimization (inverse planning) relaxes this constraint in order to obtain a dose distribution that is more conformal the anatomy. We developed a version of inverse planning constrained by maximum dwell times. The relationship between dwell time homogeneity and the dose delivered to cancerous and healthy organs is examined. Methods and Materials A software method was implemented within the IPSA inverse planning algorithm to allow for (1) imposition of a user-defined global maximum dwell time at any given dwell position and (2) homogeneity of dwell times within any given catheter. In-silico studies were performed on six previously-treated-patient image datasets using the contours and catheter digitization of the clinically-used plan. Two each of tandem-and-ring gynecological, tandem-and-ovoid gynecological, and prostate were examined. The plan used for treatment served as the control and had no restriction on dwell times. New plans were optimized by imposing either a global (Study 1) or catheter-specific maximum dwell times (Study 2) for different time limits. Dosimetric indices were compared with the control plans. Results Clinically acceptable plans were achievable with modest restriction of the dwell times, but severe restriction lead to unacceptable plans. Across all studies, restriction of dwell times correlated with an increase of the final objective function value. A higher objective function means less adherence of the optimization to the dosimetric requirements imposed on the optimization by the user. Conclusion Imposing restrictions on a global maximum dwell and intra-catheter dwell time homogeneity necessarily results in a worsening of the dosimetric optimization objective function. However, less severe restrictions can allow for some tailoring of the dose distribution to avoid intra-catheter dwell time heterogeneity with only a small decrease in target coverage. Research sponsored in part by Nucletron.

A hybrid evolutionary algorithm for multi-objective anatomy-based dose optimization in high-dose-rate brachytherapy

Multiple objectives must be considered in anatomy-based dose optimization for high-dose-rate brachytherapy and a large number of parameters must be optimized to satisfy often competing objectives. For objectives expressed solely in terms of dose variances, deterministic gradient-based algorithms can be applied and a weighted sum approach is able to produce a representative set of non-dominated solutions. As the number of objectives increases, or non-convex objectives are used, local minima can be present and deterministic or stochastic algorithms such as simulated annealing either cannot be used or are not efficient. In this case we employ a modified hybrid version of the multi-objective optimization algorithm NSGA-II. This, in combination with the deterministic optimization algorithm, produces a representative sample of the Pareto set. This algorithm can be used with any kind of objectives, including non-convex, and does not require artificial importance factors. A representation of the trade-off surface can be obtained with more than 1000 non-dominated solutions in 2–5 min. An analysis of the solutions provides information on the possibilities available using these objectives. Simple decision making tools allow the selection of a solution that provides a best fit for the clinical goals. We show an example with a prostate implant and compare results obtained by variance and dose-volume histogram (DVH) based objectives.

Inverse planning anatomy-based dose optimization for HDR-brachytherapy of the prostate using fast simulated annealing algorithm and dedicated objective function.

An anatomy-based dose optimization algorithm is developed to automatically and rapidly produce a highly conformal dose coverage of the target volume while minimizing urethra, bladder, and rectal doses in the delivery of an high dose-rate (HDR) brachytherapy boost for the treatment of prostate cancer. The dwell times are optimized using an inverse planning simulated annealing algorithm (IPSA) governed entirely from the anatomy extracted from a CT and by a dedicated objective function (cost function) reflecting clinical prescription and constraints. With this inverse planning approach, the focus is on the physician's prescription and constraint instead of on the technical limitations. Consequently, the physician's control on the treatment is improved. The capacity of this algorithm to represent the physician's prescription is presented for a clinical prostate case. The computation time (CPU) for IPSA optimization is less than 1 min (41 s for 142915 iterations) for a typical clinical case, allowing fast and practical dose optimization. The achievement of highly conformal dose coverage to the target volume opens the possibility to deliver a higher dose to the prostate without inducing overdosage of urethra and normal tissues surrounding the prostate. Moreover, using the same concept, it will be possible to deliver a boost dose to a delimited tumor volume within the prostate. Finally, this method can be easily extended to other anatomical sites.