ABSTRACT
PURPOSE: Inclusion of highly non-coplanar treatment angles increases radiations dose conformality and critical organ sparing. However, implementation of this treatment strategy has been hampered by inaccurate solution space modeling, limited automated beam selection methods, the lack of efficient beam sequencing program and integrated collision prevention. The aim is to develop a 4pi radiotherapy paradigm that takes full advantage of modern computer-controlled robotic C-arm linear accelerators. METHODS: The beam geometry solution space was modeled by 3D surface scanning of the couch, gantry and patient. In order to utilize the entire solution space and optimize MLC resolution, variable source-to-tumor distances were introduced. Conformai radiation doses were computed using convolution/superposition from uniformly distributed solid angles. Beam orientation optimization was performed using a column generation and pricing approach, which was also used to optimize beam fluence intensity modulation. A level set method was then employed to automatically sequence beams so the treatment time and couch motion can be minimized while avoiding collision on the path. RESULTS: The machine and patient surface was accurately measured and a cocoon shaped solution space was created with an integrated gap buffer of 4 cm. 14 conformai beams were typically selected to maximize target dose coverage and minimize critical organ doses. Compared with manual non-coplanar and coplanar volumetric modulated arc therapy plans, an average 20% improvement was observed in high dose spillage, defined as the 50% isodose volume divided by the target volume, in a wide range of clinical cases including brain, lung, liver and partial breast cancer. CONCLUSIONS: We have established a framework that overcomes major technical difficulties associated with automated planning and delivery of highly non-coplanar treatment on the widely available C-arm linacs. Compared with coplanar volumetric modulated arc therapy plans, 4pi plans improve nearly all aspects of the dosimetry while remain highly deliverable.
ABSTRACT
PURPOSE: To efficiently select high-quality coplanar or non-coplanar beam orientations for IMRT treatments while formally and explicitly incorporating the effect of the selected beam orientations on the quality of the dose distribution obtained by the treatment plan optimization model. METHODS: Beam orientation models consider a discrete set of potential coplanar and/or non-coplanar beam locations around the patient. A new greedy algorithm is proposed to solve a model that integrates beam orientation optimization (BOO) and fluence map optimization (FMO). The algorithm iteratively adds beams to a FMO model. In each iteration, an attractiveness measure is associated with each remaining candidate beam orientation. This attractiveness measure is based explicitly on an optimal dose distribution that allows only the currently selected set of beams to be used. Several alternate attractiveness measures are considered which use either first-order information or both first and second-order information. Performance of the algorithm was assessed on a clinical lung cancer case. RESULTS: The developed beam selection algorithm was applied to a lung cancer case using either coplanar beams or both coplanar and non-coplanar beams. In the coplanar case, beam orientations were found that produce a superior dose distribution to that using an equal number of equi-spaced beams. In the non-coplanar case it was found that fewer beams were needed to produce a dose distribution of comparable quality to that found in the coplanar case. CONCLUSIONS: The developed solution approach showcases the potential benefits of integrating different steps in the treatment plan optimization process. By integrating the BOO and FMO models, treatment plan quality was explicitly incorporated into the beam selection process. BOO can be automated and implemented efficiently, which eliminates the guesswork involved in manually adjusting beam orientations in IMRT treatment planning.