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This paper reports an inverse arc-modulated radiation therapy planning technique based on linear models. It is implemented with a two-step procedure. First, fluence maps for 36 fixed-gantry beams are generated using a linear model-based intensity-modulated radiation therapy (IMRT) optimization algorithm. The 2D fluence maps are decomposed into 1D fluence profiles according to each leaf pair position. Second, a mixed integer linear model is used to construct the leaf motions of an arc delivery that reproduce the 1D fluence profile previously derived from the static gantry IMRT optimization. The multi-leaf collimator (MLC) sequence takes into account the starting and ending leaf positions in between the neighbouring apertures, such that the MLC segments of the entire treatment plan are deliverable in a continuous arc. Since both steps in the algorithm use linear models, implementation is simple and straightforward. Details of the algorithm are presented, and its conceptual correctness is verified with clinical cases representing prostate and head-and-neck treatments.

This study compares three online image guidance techniques (IGRT) for prostate IMRT treatment: bony-anatomy matching, soft-tissue matching, and online replanning. Six prostate IMRT patients were studied. Five daily CBCT scans from the first week were acquired for each patient to provide representative "snapshots" of anatomical variations during the course of treatment. Initial IMRT plans were designed for each patient with seven coplanar 15 MV beams on a Eclipse treatment planning system. Two plans were created, one with a PTV margin of 10 mm and another with a 5 mm PTV margin. Based on these plans, the delivered dose distributions to each CBCT anatomy was evaluated to compare bony-anatomy matching, soft-tissue matching, and online replanning. Matching based on bony anatomy was evaluated using the 10 mm PTV margin ("bone10"). Soft-tissue matching was evaluated using both the 10 mm ("soft10") and 5 mm ("soft5") PTV margins. Online reoptimization was evaluated using the 5 mm PTV margin ("adapt"). The replanning process utilized the original dose distribution as the basis and linear goal programming techniques for reoptimization. The reoptimized plans were finished in less than 2 min for all cases. Using each IGRT technique, the delivered dose distribution was evaluated on all 30 CBCT scans (6 patients x 5 CBCT/patient). The mean minimum dose (in percentage of prescription dose) to the CTV over five treatment fractions were in the ranges of 99%-100% (SD = 0.1%-0.8%), 65%-98% (SD = 0.4%-19.5%), 87%-99% (SD = 0.7%-23.3%), and 95%-99% (SD = 0.4%-10.4%) for the adapt, bone10, soft5, and soft10 techniques, respectively. Compared to patient position correction techniques, the online reoptimization technique also showed improvement in OAR sparing when organ motion/deformations were large. For bladder, the adapt technique had the best (minimum) D90, D50, and D30 values for 24, 17, and 15 fractions out of 30 total fractions, while it also had the best D90, D50, and D30 values for the rectum for 25, 16, and 19 fractions, respectively. For cases where the adapt plans did not score the best for OAR sparing, the gains of the OAR sparing in the repositioning-based plans were accompanied by an underdosage in the target volume. To further evaluate the fast online replanning technique, a gold-standard plan ("new" plan) was generated for each CBCT anatomy on the Eclipse treatment planning system. The OAR sparing from the online replanning technique was compared to the new plan. The differences in D90, D50, and D30 of the OARs between the adapt and the new plans were less than 5% in 3 patients and were between 5% and 10% for the remaining three. In summary, all IGRT techniques could be sufficient to correct simple geometrical variations. However, when a high degree of deformation or differential organ position displacement occurs, the online reoptimization technique is feasible with less than 2 min optimization time and provides improvements in both CTV coverage and OAR sparing over the position correction techniques. For these cases, the reoptimization technique can be a highly valuable online IGRT tool to correct daily treatment uncertainties, especially when hypofractionation scheme is applied and daily correction, rather than averaging over many fractions, is required to match the original plan.

Stereotactic body radiation therapy (SBRT), which delivers a much higher fractional dose than conventional treatment in only a few fractions, is an effective treatment for liver metastases. For patients who are treated under free-breathing conditions, however, respiration-induced tumor motion in the liver is a concern. Limited clinical information is available related to the impact of tumor motion and treatment technique on the dosimetric consequences. This study evaluated the dosimetric deviations between planned and delivered SBRT dose in the presence of tumor motion for three delivery techniques: three-dimensional conformal static beams (3DCRT), dynamic conformal arc (DARC), and intensity-modulated radiation therapy (IMRT). Five cases treated with SBRT for liver metastases were included in the study, with tumor motions ranging from 0.5 to 1.75 cm. For each case, three different treatment plans were developed using 3DCRT, DARC, and IMRT. The gantry/multileaf collimator (MLC) motion in the DARC plans and the MLC motion in the IMRT plans were synchronized to the patient's respiratory motion. Retrospectively sorted four-dimensional computed tomography image sets were used to determine patient-organ motion and to calculate the dose delivered during each respiratory phase. Deformable registration, using thin-plate-spline models, was performed to encode the tumor motion and deformation and to register the dose-per-phase to the reference phase images. The different dose distributions resulting from the different delivery techniques and motion ranges were compared to assess the effect of organ motion on dose delivery. Voxel dose variations occurred mostly in the high gradient regions, typically between the target volume and normal tissues, with a maximum variation up to 20%. The greatest CTV variation of all the plans was seen in the IMRT technique with the largest motion range (D99: -8.9%, D95: -8.3%, and D90: -6.3%). The greatest variation for all 3DCRT plans was less than 2% for D95. Dose variations for DARC fell between the 3DCRT and IMRT techniques. The dose volume histogram variations for normal organs were negligible. Therefore, the IMRT technique may be a preferable treatment choice in cases where the target volume and critical organs are in close proximity, or when normal organ protection is a high priority, provided that motion effect for the target volume can be managed.

For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment.

The challenges of real-time Gamma Knife inverse planning are the large number of variables involved and the unknown search space a priori. With limited collimator sizes, shots have to be heavily overlapped to form a smooth prescription isodose line that conforms to the irregular target shape. Such overlaps greatly influence the total number of shots per plan, making pre-determination of the total number of shots impractical. However, this total number of shots usually defines the search space, a pre-requisite for most of the optimization methods. Since each shot only covers part of the target, a collection of shots in different locations and various collimator sizes selected makes up the global dose distribution that conforms to the target. Hence, planning or placing these shots is a combinatorial optimization process that is computationally expensive by nature. We have previously developed a theory of shot placement and optimization based on skeletonization. The real-time inverse planning process, reported in this paper, is an expansion and the clinical implementation of this theory. The complete planning process consists of two steps. The first step is to determine an optimal number of shots including locations and sizes and to assign initial collimator size to each of the shots. The second step is to fine-tune the weights using a linear-programming technique. The objective function is to minimize the total dose to the target boundary (i.e., maximize the dose conformity). Results of an ellipsoid test target and ten clinical cases are presented. The clinical cases are also compared with physician's manual plans. The target coverage is more than 99% for manual plans and 97% for all the inverse plans. The RTOG PITV conformity indices for the manual plans are between 1.16 and 3.46, compared to 1.36 to 2.4 for the inverse plans. All the inverse plans are generated in less than 2 min, making real-time inverse planning a reality.