Beam Orientation Optimization for Intensity Modulated Radiation Therapy using Adaptive l1 Minimization

Beam orientation optimization (BOO) is a key component in the process of IMRT treatment planning. It determines to what degree one can achieve a good treatment plan quality in the subsequent plan optimization process. In this paper, we have developed a BOO algorithm via adaptive l_1 minimization. Specifically, we introduce a sparsity energy function term into our model which contains weighting factors for each beam angle adaptively adjusted during the optimization process. Such an energy term favors small number of beam angles. By optimizing a total energy function containing a dosimetric term and the sparsity term, we are able to identify the unimportant beam angles and gradually remove them without largely sacrificing the dosimetric objective. In one typical prostate case, the convergence property of our algorithm, as well as the how the beam angles are selected during the optimization process, is demonstrated. Fluence map optimization (FMO) is then performed based on the optimized beam angles. The resulted plan quality is presented and found to be better than that obtained from unoptimized (equiangular) beam orientations. We have further systematically validated our algorithm in the contexts of 5-9 coplanar beams for 5 prostate cases and 1 head and neck case. For each case, the final FMO objective function value is used to compare the optimized beam orientations and the equiangular ones. It is found that, our BOO algorithm can lead to beam configurations which attain lower FMO objective function values than corresponding equiangular cases, indicating the effectiveness of our BOO algorithm.Comment: 19 pages, 2 tables, and 5 figure

Multicriteria VMAT optimization

Purpose: To make the planning of volumetric modulated arc therapy (VMAT) faster and to explore the tradeoffs between planning objectives and delivery efficiency. Methods: A convex multicriteria dose optimization problem is solved for an angular grid of 180 equi-spaced beams. This allows the planner to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus organ at risk sparing. The selected plan is then made VMAT deliverable by a fluence map merging and sequencing algorithm, which combines neighboring fluence maps based on a similarity score and then delivers the merged maps together, simplifying delivery. Successive merges are made as long as the dose distribution quality is maintained. The complete algorithm is called VMERGE. Results: VMERGE is applied to three cases: a prostate, a pancreas, and a brain. In each case, the selected Pareto-optimal plan is matched almost exactly with the VMAT merging routine, resulting in a high quality plan delivered with a single arc in less than five minutes on average. VMERGE offers significant improvements over existing VMAT algorithms. The first is the multicriteria planning aspect, which greatly speeds up planning time and allows the user to select the plan which represents the most desirable compromise between target coverage and organ at risk sparing. The second is the user-chosen epsilon-optimality guarantee of the final VMAT plan. Finally, the user can explore the tradeoff between delivery time and plan quality, which is a fundamental aspect of VMAT that cannot be easily investigated with current commercial planning systems

Algorithm and performance of a clinical IMRT beam-angle optimization system

This paper describes the algorithm and examines the performance of an IMRT beam-angle optimization (BAO) system. In this algorithm successive sets of beam angles are selected from a set of predefined directions using a fast simulated annealing (FSA) algorithm. An IMRT beam-profile optimization is performed on each generated set of beams. The IMRT optimization is accelerated by using a fast dose calculation method that utilizes a precomputed dose kernel. A compact kernel is constructed for each of the predefined beams prior to starting the FSA algorithm. The IMRT optimizations during the BAO are then performed using these kernels in a fast dose calculation engine. This technique allows the IMRT optimization to be performed more than two orders of magnitude faster than a similar optimization that uses a convolution dose calculation engine.Comment: Final version that appeared in Phys. Med. Biol. 48 (2003) 3191-3212. Original EPS figures have been converted to PNG files due to size limi

Depth Modulation in Radiotherapy

Intensity Modulated Radiotherapy (IMRT) has been a major field of research over the last thirty years and is today the standard in radiotherapy treatment of cancer. The introduction of IMRT into the clinical environment has greatly improved the ability of the treatment team to conform the radiation dose to the tumour volume. Alongside improvements in image guidance, IMRT has led to a reduction in side effects for patients and opened up the possibilities of dose escalation and hypofractionation. IMRT is however by no means perfect. IMRT and derivatives such as Volumated Arc Therapy (VMAT) are limited by the exit dose from the X-ray beams and deliver a significant amount of radiation dose to normal tissues. The much publicised alternative to IMRT is proton therapy. Proton therapy beams deposit dose over a narrow range resulting in minimal exit dose. The future of radiotherapy certainly involves a significant contribution from proton therapy but the availability to patients is likely to remain limited for a long time to come. The research in this thesis considers the possibility of further improving IMRT by modulating radiotherapy beams along their direction of travel as well as across their intensity, i.e. the so called ‘Depth Modulation’ of the thesis title. Although there are numerous possible ways to achieve depth modulation, this work proposes a combination of X-ray beams with electron beams of different energies with both modalities delivered with a conventional medical linear accelerator. The research in this thesis is concerned with developing a proof of principle for this method. It is to some extent a theoretical study, however at each step the possibility of practical implementation has been considered with the view that the method is only a viable proposition if it can be effectively implemented into clinical practice. The technique proposed in this work is to use electron beams delivered through X-ray MLC with a standard patient set up. To reduce scatter and photon contamination it is proposed to remove the scattering foils from the beamline and to employ optimisation of the electron and photon components to compensate for any remaining penumbra broadening. The research has shown that improvements to dosimetry through removal of the scattering foil would allow delivery without reducing the source to surface distance, making a single isocentre synergistic delivery for both the electron and photon components practical. Electron dose segments have been calculated using Monte Carlo radiation transport and a procedure to optimise dose for the combined photon and electron IMRT technique has been developed. Through development of the optimisation procedure the characteristics of the mixed modality technique have been examined. A number of findings are demonstrated such as the benefit of gaps between electron segments, the benefits of optimising for energy in three dimensions and the dependence of the cost function minimum on the electron to photon ratio. Through clinical examples it has been shown that for tumours close to the surface the mixed modality technique has the potential to reduce the dose to normal tissues, particular in the low dose wash. Calculations of relative malignant induction probability demonstrate that this reduction in dose has the potential to reduce the incidence of secondary cancer induction. Possible treatment sites for application of the technique include breast, head and neck, brain and sarcomas

IMRT Beam Angle Optimization Using Non-descent Pattern Search Methods

https://thekeep.eiu.edu/commencement_spring2015/1304/thumbnail.jp