An algorithm for fast beam angle selection in intensity modulated radiotherapy.

PURPOSE: This article aims to introduce a novel algorithm for fast beam angle selection in intensity modulated radiotherapy (IMRT). METHODS: The algorithm models the optimization problem as a beam angle ranking problem and chooses suitable beam angles according to their rank. A new parameter called "beam intensity profile perturbation score (BIPPS)" is used for ranking the beam angles. The BIPPS-based beam angle ranking implicitly accounts for the dose-volume effects of the involved structures. A simulated phantom case with obvious optimal beam angles is used to verify the validity of the presented technique. In addition, the efficiency of the algorithm was examined in three clinical cases (prostate, pancreas, and head and neck) in terms of DVH and dose distribution. In all cases, the judgment of the algorithm's efficiency was based on the comparison between plans with equidistant beams (equal-angle-plan) and plans with beams obtained using the algorithm (suitable-angle-plan). RESULTS: It is observed from the study that the beam angle ranking function over BIPPS instantly picks up a suitable set of beam angles for a specific case. It takes only about 15 min for choosing the suitable beam angles even for the most complicated cases. The DVHs and dose distributions confirm that the proposed algorithm can efficiently reduce the mean or maximum dose to OARs, while guaranteeing the target coverage and dose uniformity. On the average, about 17% reduction in the mean dose to critical organs, such as rectum, bladder, kidneys and parotids, is observed. Also, about 12% (averaged) reduction in the maximum dose to critical organs (spinal cord) is observed in the clinical cases presented in this study. CONCLUSIONS: This study demonstrates that the algorithm can be effectively applied to IMRT scenarios to get fast and case specific beam angle configurations.

A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: A performance evaluation study.

The study aims to introduce a hybrid optimization algorithm for anatomy-based intensity modulated radiotherapy (AB-IMRT). Our proposal is that by integrating an exact optimization algorithm with a heuristic optimization algorithm, the advantages of both the algorithms can be combined, which will lead to an efficient global optimizer solving the problem at a very fast rate. Our hybrid approach combines Gaussian elimination algorithm (exact optimizer) with fast simulated annealing algorithm (a heuristic global optimizer) for the optimization of beam weights in AB-IMRT. The algorithm has been implemented using MATLAB software. The optimization efficiency of the hybrid algorithm is clarified by (i) analysis of the numerical characteristics of the algorithm and (ii) analysis of the clinical capabilities of the algorithm. The numerical and clinical characteristics of the hybrid algorithm are compared with Gaussian elimination method (GEM) and fast simulated annealing (FSA). The numerical characteristics include convergence, consistency, number of iterations and overall optimization speed, which were analyzed for the respective cases of 8 patients. The clinical capabilities of the hybrid algorithm are demonstrated in cases of (a) prostate and (b) brain. The analyses reveal that (i) the convergence speed of the hybrid algorithm is approximately three times higher than that of FSA algorithm; (ii) the convergence (percentage reduction in the cost function) in hybrid algorithm is about 20% improved as compared to that in GEM algorithm; (iii) the hybrid algorithm is capable of producing relatively better treatment plans in terms of Conformity Index (CI) [~ 2% - 5% improvement] and Homogeneity Index (HI) [~ 4% - 10% improvement] as compared to GEM and FSA algorithms; (iv) the sparing of organs at risk in hybrid algorithm-based plans is better than that in GEM-based plans and comparable to that in FSA-based plans; and (v) the beam weights resulting from the hybrid algorithm are about 20% smoother than those obtained in GEM and FSA algorithms. In summary, the study demonstrates that hybrid algorithms can be effectively used for fast optimization of beam weights in AB-IMRT.

Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy.

This study aims to evaluate the performance of a new algorithm for optimization of beam weights in anatomy-based intensity modulated radiotherapy (IMRT). The algorithm uses a numerical technique called Gaussian-Elimination that derives the optimum beam weights in an exact or non-iterative way. The distinct feature of the algorithm is that it takes only fraction of a second to optimize the beam weights, irrespective of the complexity of the given case. The algorithm has been implemented using MATLAB with a Graphical User Interface (GUI) option for convenient specification of dose constraints and penalties to different structures. We have tested the numerical and clinical capabilities of the proposed algorithm in several patient cases in comparison with KonRad((R)) inverse planning system. The comparative analysis shows that the algorithm can generate anatomy-based IMRT plans with about 50% reduction in number of MUs and 60% reduction in number of apertures, while producing dose distribution comparable to that of beamlet-based IMRT plans. Hence, it is clearly evident from the study that the proposed algorithm can be effectively used for clinical applications.