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Purpose The objective of this study was to investigate the influence of tumor motion on dose delivery in stereotactic body radiotherapy (SBRT) for lung cancer, using fixed field intensity- modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Methods and Materials For each of 10 patients with stage I/II non-small-cell pulmonary tumors, a respiration-correlated four-dimensional computed tomography (4DCT) study was carried out. The internal target volume was delineated on the maximum intensity projection CT, which was reconstructed from the 4DCT dataset. A 5-mm margin was used for generation of the planning target volume. VMAT and five-field IMRT plans were generated using Pinnacle 3 SmartArc and direct machine parameter optimization, respectively. All plans were generated for an Elekta Synergy linear accelerator using 6-MV photons. Simulation was performed to study the interplay between multileaf collimator (MLC) sequences and target movement during the delivery of VMAT and IMRT. For each plan, 4D dose was calculated using deformable image registration of the 4DCT images. Target volume coverage and doses to critical structures calculated using 4D methodology were compared with those calculated using 3D methodology. Results For all patients included in this study, the interplay effect was found to present limited impact (less than 1% of prescription) on the target dose distribution, especially for SBRT, in which fewer fractions (three fractions) are delivered. Dose to the gross tumor volume (GTV) was, on average, slightly decreased (1% of prescription) in the 4D calculation compared with the 3D calculation. The motion impact on target dose homogeneity was patient-dependent and relatively small. Conclusions Both VMAT and IMRT plans experienced negligible interplay effects between MLC sequence and tumor motion. For the most part, the 3D doses to the GTV and critical structures provided good approximations of the 4D dose calculations.

Purpose: Intensity modulated arc therapy (IMAT) is a radiation therapy delivery technique that combines the efficiency of arc based delivery with the dose painting capabilities of intensity modulated radiation therapy (IMRT). A key challenge in developing robust inverse planning solutions for IMAT is the need to account for the connectivity of the beam shapes as the gantry rotates from one beam angle to the next. To overcome this challenge, inverse planning solutions typically impose a leaf motion constraint that defines the maximum distance a multileaf collimator (MLC) leaf can travel between adjacent control points. The leaf motion constraint ensures the deliverability of the optimized plan, but it also impacts the plan quality, the delivery accuracy, and the delivery efficiency. In this work, the authors have studied leaf motion constraints in detail and have developed recommendations for optimizing the balance between plan quality and delivery efficiency. Methods: Two steps were used to generate optimized IMAT treatment plans. The first was the direct machine parameter optimization (DMPO) inverse planning module in the Pinnacle{sup 3} planning system. Then, a home-grown arc sequencer was applied to convert the optimized intensity maps into deliverable IMAT arcs. IMAT leaf motion constraints were imposed using limits ofmore » between 1 and 30 mm/deg. Dose distributions were calculated using the convolution/superposition algorithm in the Pinnacle{sup 3} planning system. The IMAT plan dose calculation accuracy was examined using a finer sampling calculation and the quality assurance verification. All plans were delivered on an Elekta Synergy with an 80-leaf MLC and were verified using an IBA MatriXX 2D ion chamber array inserted in a MultiCube solid water phantom. Results: The use of a more restrictive leaf motion constraint (less than 1-2 mm/deg) results in inferior plan quality. A less restrictive leaf motion constraint (greater than 5 mm/deg) results in improved plan quality but can lead to less accurate dose distribution as evidenced by increasing discrepancies between the planned and the delivered doses. For example, the results from our patient-specific quality assurance measurements demonstrated that the average gamma analysis passing rate decreased from 98% to 80% when the allowable leaf motion increased from 3 to 20 mm/deg. Larger leaf motion constraints also led to longer treatment delivery times (2 to 4 folds) due to the additional MLC leaf motion. Conclusions: Leaf motion constraints significantly impact IMAT plans in terms of plan quality, delivery accuracy, and delivery efficiency with the impact magnified for more complex cases. Our studies indicate that a leaf motion constraint of 2 to 3 mm/deg of gantry rotation can provide an optimal balance between plan quality, delivery accuracy, and efficiency.« less

Volumetric modulated arc therapy (VMAT) has the potential to reduce treatment times while producing comparable or improved dose distributions relative to fixed-field intensity-modulated radiation therapy. In order to take full advantage of the VMAT delivery technique, one must select a robust inverse planning tool. The purpose of this study was to evaluate the effectiveness and efficiency of VMAT planning techniques of three categories: anatomy-based, fluence-based and aperture-based inverse planning. We have compared these techniques in terms of the plan quality, planning efficiency and delivery efficiency. Fourteen patients were selected for this study including six head-and-neck (HN) cases, and two cases each of prostate, pancreas, lung and partial brain. For each case, three VMAT plans were created. The first VMAT plan was generated based on the anatomical geometry. In the Elekta ERGO++ treatment planning system (TPS), segments were generated based on the beam's eye view (BEV) of the target and the organs at risk. The segment shapes were then exported to Pinnacle TPS followed by segment weight optimization and final dose calculation. The second VMAT plan was generated by converting optimized fluence maps (calculated by the Pinnacle TPS) into deliverable arcs using an in-house arc sequencer. The third VMAT plan was generated using the Pinnacle SmartArc IMRT module which is an aperture-based optimization method. All VMAT plans were delivered using an Elekta Synergy linear accelerator and the plan comparisons were made in terms of plan quality and delivery efficiency. The results show that for cases of little or modest complexity such as prostate, pancreas, lung and brain, the anatomy-based approach provides similar target coverage and critical structure sparing, but less conformal dose distributions as compared to the other two approaches. For more complex HN cases, the anatomy-based approach is not able to provide clinically acceptable VMAT plans while highly conformal dose distributions were obtained using both aperture-based and fluence-based inverse planning techniques. The aperture-based approach provides improved dose conformity than the fluence-based technique in complex cases.

Purpose: Helical tomotherapy (HT) and volumetric modulated arc therapy (VMAT) are arc-based approaches to IMRT delivery. The objective of this study is to compare VMAT to both HT and fixed field IMRT in terms of plan quality, delivery efficiency, and accuracy. Methods: Eighteen cases including six prostate, six head-and-neck, and six lung cases were selected for this study. IMRT plans were developed using direct machine parameter optimization in the Pinnacle{sup 3} treatment planning system. HT plans were developed using a Hi-Art II planning station. VMAT plans were generated using both the Pinnacle{sup 3} SmartArc IMRT module and a home-grown arc sequencing algorithm. VMAT and HT plans were delivered using Elekta's PreciseBeam VMAT linac control system (Elekta AB, Stockholm, Sweden) and a TomoTherapy Hi-Art II system (TomoTherapy Inc., Madison, WI), respectively. Treatment plan quality assurance (QA) for VMAT was performed using the IBA MatriXX system while an ion chamber and films were used for HT plan QA. Results: The results demonstrate that both VMAT and HT are capable of providing more uniform target doses and improved normal tissue sparing as compared with fixed field IMRT. In terms of delivery efficiency, VMAT plan deliveries on average took 2.2 min for prostate andmore » lung cases and 4.6 min for head-and-neck cases. These values increased to 4.7 and 7.0 min for HT plans. Conclusions: Both VMAT and HT plans can be delivered accurately based on their own QA standards. Overall, VMAT was able to provide approximately a 40% reduction in treatment time while maintaining comparable plan quality to that of HT.« less

Purpose Intrafraction organ motion can produce dosimetric errors in radiotherapy. Commonly, the linear accelerator is gated using real-time breathing phase obtained by way of external sensors. However, the external anatomy does not always correlate well with the internal position. We examined a beam gating technique using signals from implanted wireless transponders that provided real-time feedback on the tumor location without an imaging dose to the patient. Methods and Materials An interface was developed between Calypso Medical's four-dimensional electromagnetic tracking system and a Varian Trilogy linear accelerator. A film phantom was mounted on a motion platform programmed with lung motion trajectories. Deliveries were performed when the beam was gated according to the signal from the wireless transponders. The dosimetric advantages of beam gating and the system latencies were quantified. Results Beam gating using on internal position monitoring provided up to a twofold increase in the dose gradients. The percentage of points failing to be within ±10 cGy of the planned dose (maximal dose, ∼200 cGy) was 3.4% for gating and 32.1% for no intervention in the presence of motion. The mean latencies between the transponder position and linear accelerator modulation were 75.0 ±12.7 ms for beam on and 65.1 ± 12.9 ms for beam off. Conclusion We have presented the results from a novel method for gating the linear accelerator using trackable wireless internal fiducial markers without the use of ionizing radiation for imaging. The latencies observed were suitable for gating using electromagnetic fiducial markers, which results in dosimetric improvements for irradiation in the presence of motion.

Purpose: To assess efficacy and quality of life (QOL) outcomes associated with gamma-knife radiosurgery (GK-RS) in treating atypical trigeminal neuralgia (ATN) compared with classic trigeminal neuralgia (CTN). Methods and Materials: Between September 1996 and September 2004, 35 cases of ATN were treated with GK-RS. Patients were categorized into two groups: Group I comprised patients presenting with ATN (57%); Group II consisted of patients presenting with CTN then progressing to ATN (43%). Median prescription dose 75 Gy (range, 70–80 Gy) was delivered to trigeminal nerve root entry zone. Treatment efficacy and QOL improvements were assessed with a standardized questionnaire. Results: With median follow-up of 29 months (range, 3–74 months), 72% reported excellent/good outcomes, with mean time to relief of 5.8 weeks (range, 0–24 weeks) and mean duration of relief of 62 weeks (range, 1–163 weeks). This rate of pain relief is similar to rate achieved in our previously reported experience treating CTN with GK-RS ( p = 0.36). There was a trend toward longer time to relief ( p = 0.059), and shorter duration of relief ( p = 0.067) in patients with ATN. There was no difference in rate of, time to, or duration of pain relief between Groups I and II. Of the patients with ATN, 88% discontinued or decreased the use of pain medications. Among the patients with sustained pain relief, QOL improved an average of 85%. Conclusion: This is the largest reported GK-RS experience for the treatment of ATN. Patients with ATN can achieve rates of pain relief similar to those in patients with CTN. Further follow-up is necessary to assess adequately the durability of response.

An optimization framework for three-dimensional conformal radiation therapy is presented. In conformal therapy, beams of radiation are applied to a patient from different directions, where the aperture through which the beam is delivered from each direction is chosen to match the shape of the tumor, as viewed from that direction. Wedge filters may be used to produce a gradient in beam intensity across the aperture. Given a set of equispaced beam angles, a mixed-integer linear program can be solved to determine the most effective angles to be used in a treatment plan, the weight (exposure time) to be used for each beam, and the type and orientation of wedges to be used. Practical solution techniques for this problem are described; they include strengthening of the formulation and solution of smaller approximate problems obtained by a reduced parametrization of the treatment region. In addition, techniques for controlling the dose-volume histogram implicitly for various parts of the treatment region using hot- and cold-spot control parameters are presented. Computational results are given that show the effectiveness of the proposed approach on practical data sets.

Intensity modulated arc therapy (IMAT) is an intensity modulated radiation therapy delivery technique originally proposed as an alternative to tomotherapy. IMAT uses a series of overlapping arcs to deliver optimized intensity patterns from each beam direction. The full potential of IMAT has gone largely unrealized due in part to a lack of robust and commercially available inverse planning tools. To address this, we have implemented an IMAT arc-sequencing algorithm that translates optimized intensity maps into deliverable IMAT plans. The sequencing algorithm uses simulated annealing to simultaneously optimize the aperture shapes and weights throughout each arc. The sequencer enforces the delivery constraints while minimizing the discrepancies between the optimized and sequenced intensity maps. The performance of the algorithm has been tested for ten patient cases (3 prostate, 3 brain, 2 head-and-neck, 1 lung, and 1 pancreas). Seven coplanar IMAT plans were created using an average of 4.6 arcs and 685 monitor units. Additionally, three noncoplanar plans were created using an average of 16 arcs and 498 monitor units. The results demonstrate that the arc sequencer can provide efficient and highly conformal IMAT plans. An average sequencing time of approximately 20 min was observed.

A wide variety of optimization problems and techniques are used in radiation treatment planning. The problems typically involve large amounts of data, derived from simulations of patient anatomy and the properties of the delivery device. We investigate a three phase approach for their solution based on sampling of the underlying data that determines optimal beam angles, wedge orientations and delivery intensities in patient examples. Phase I uses multiple coarse samplings of the data and linear programming to adapt the sampling and determine a collection of promising angles to use. Phase II solves the adapted sample problems as mixed integer programs using only the promising angles. Phase III refines the sampling further, and fixes most of the discrete decision variables to reduce computation times. Particular emphasis will be given to general principles that are applicable to large classes of treatment planning problems. Specific examples show enormous increase in speed of planning, without detriment to the solution quality.

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases were selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle{sup 3} treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequencedmore » intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.« less

We have studied the degree to which beamlet step-size impacts the quality of intensity modulated radiation therapy (IMRT) treatment plans. Treatment planning for IMRT begins with the application of a grid that divides each beam's-eye-view of the target into a number of smaller beamlets (pencil beams) of radiation. The total dose is computed as a weighted sum of the dose delivered by the individual beamlets. The width of each beamlet is set to match the width of the corresponding leaf of the multileaf collimator (MLC). The length of each beamlet (beamlet step-size) is parallel to the direction of leaf travel. The beamlet step-size represents the minimum stepping distance of the leaves of the MLC and is typically predetermined by the treatment planning system. This selection imposes an artificial constraint because the leaves of the MLC and the jaws can both move continuously. Removing the constraint can potentially improve the IMRT plan quality. In this study, the optimized results were achieved using an aperture-based inverse planning technique called direct aperture optimization (DAO). We have tested the relationship between pencil beam step-size and plan quality using the American College of Radiology's IMRT test case. For this case, a series of IMRT treatment plans were produced using beamlet step-sizes of 1, 2, 5, and 10 mm. Continuous improvements were seen with each reduction in beamlet step size. The maximum dose to the planning target volume (PTV) was reduced from 134.7% to 121.5% and the mean dose to the organ at risk (OAR) was reduced from 38.5% to 28.2% as the beamlet step-size was reduced from 10 to 1 mm. The smaller pencil beam sizes also led to steeper dose gradients at the junction between the target and the critical structure with gradients of 6.0, 7.6, 8.7, and 9.1 dose%/mm achieved for beamlet step sizes of 10, 5, 2, and 1 mm, respectively.

Intensity-modulated arc therapy (IMAT) is a radiation therapy delivery technique that combines gantry rotation with dynamic multi-leaf collimation (MLC). With IMAT, the benefits of rotational IMRT can be realized using a conventional linear accelerator and a conventional MLC. Thus far, the advantages of IMAT have gone largely unrealized due to the lack of robust automated planning tools capable of producing efficient IMAT treatment plans. This work describes an inverse treatment planning algorithm, called 'direct aperture optimization' (DAO) that can be used to generate inverse treatment plans for IMAT. In contrast to traditional inverse planning techniques where the relative weights of a series of pencil beams are optimized, DAO optimizes the leaf positions and weights of the apertures in the plan. This technique allows any delivery constraints to be enforced during the optimization, eliminating the need for a leaf-sequencing step. It is this feature that enables DAO to easily create inverse plans for IMAT. To illustrate the feasibility of DAO applied to IMAT, several cases are presented, including a cylindrical phantom, a head and neck patient and a prostate patient.

The Gamma Knife is a highly specialized treatment unit that provides an advanced stereotactic approach to the treatment of tumors, vascular malformations, and pain disorders within the head. Inside a shielded treatment unit, multiple beams of radiation are focussed into an approximately spherical volume, generating a high dose shot of radiation. The treatment planning process attempts to cover the tumor with sufficient dosage without overdosing normal tissue or surrounding sensitive structures. An optimization problem is formulated that determines where to center the shots, for how long to expose each shot on the target, and what size focussing helmets should be used. We outline a new approach that models the dose distribution nonlinearly, and uses a smoothing approach to treat discrete problem choices. The resulting nonlinear program is not convex and several heuristic approaches are used to improve solution time and quality. The overall approach is fast and reliable; we give several results obtained from use in a clinical setting.

We outline a new approach for radiosurgery treatment planning, based on solving a series of optimization problems. We consider a specific treatment planning problem for a specialized device known as the gamma knife, which provides an advanced stereotactic approach to the treatment of tumors, vascular malformations, and pain disorders within the head. The sequence of optimization problems involves nonlinear and mixed integer programs whose solution is required in a given planning time (typically less than 30 minutes). This paper outlines several modeling decisions that result in more efficient and robust solutions. Furthermore, it outlines a new approach for determining starting points for the nonlinear programs, based on a skeletonization of the target volume. Treatment plans generated for real patient data show the efficiency of the approach.

An inverse treatment planning system for Gamma Knife radiosurgery has been developed using nonlinear programming techniques. The system optimizes the shot sizes, locations, and weights for Gamma Knife treatments. In the patient's prescription, the user can specify both the maximum number of shots of radiation and a minimum isodose line that must surround the entire treatment volume. After satisfying all of the constraints included in the prescription, the system maximizes the conformity of the dose distribution. This automated approach to treatment planning has been applied retrospectively to a series of patient cases, and each optimized plan has been compared to the corresponding manual plan produced by an experienced user. The results demonstrate that this tool can often improve the tumor dose homogeneity while using fewer shots than were included in the original plan. Therefore, inverse treatment planning should improve both the quality and the efficiency of Gamma Knife treatments.

Essential for the calculation of photon fluence distributions for intensity modulated radiotherapy (IMRT) is the use of a suitable objective function. The objective function should reflect the clinical aims of tumor control and low side effect probability. Individual radiobiological parameters for patient organs are not yet available with sufficient accuracy. Some of the major drawbacks of some current optimization methods include an inability to converge to a solution for arbitrary input parameters, and/or a need for intensive user input in order to guide the optimization. In this work, a constrained optimization method was implemented and tested. It is closely related to the demanded clinical aims, avoiding the drawbacks mentioned above. In a prototype treatment planning system for IMRT, tumor control was guaranteed by setting a lower boundary for target dose. The aim of low complication is fulfilled by minimizing the dose to organs at risk. If only one type of tissue is involved, there is no absolute need for radiobiological parameters. For different organs, threshold dose, relative seriality of the organs or an upper dose limit could be set. All parameters, however, were optional, and could be omitted. Dose-volume constraints were not used, avoiding the possibility of local minima in the objective function. The approach was benchmarked through the simulation of both a head and neck and a lung case. A cylinder phantom with precalculated dose distributions of individual pencil beams was used. The dose to regions at risk could be significantly reduced using at least seven ports of beam incidence. Increasing the number of ports beyond seven produced only minor further gain. The relative seriality of organs was modeled through the use of an added exponent to the dose. This approach however increased calculation time significantly. The alternative of setting an upper limit is much faster and allows direct control of the maximum dose. Constrained optimization guarantees high tumor control probability, it is computationally more efficient than adding penalty terms to the objective function, and the input parameters are dose limits known in clinical practice.

Convolution/superposition software has been used to produce a library of photon pencil beam dose matrices. This library of pencil beams is designed to serve as a tool for both education and investigation in the field of radiotherapy optimization. The elegance of this pencil beam model stems from its cylindrical symmetry. Because of the symmetry, the dose distribution for a pencil beam from any arbitrary angle can be determined through a simple rotation of a pre-computed dose matrix. Rapid dose calculations can thus be performed while maintaining the accuracy of a convolution/superposition based dose computation. The pencil beam data sets have been made publicly available. It is hoped that the data sets will facilitate a comparison of a variety of optimization and delivery approaches. This paper will present a number of studies designed to demonstrate the usefulness of the pencil beam data sets. These studies include an examination of the extent to which a treatment plan can be improved through either an increase in the number of beam angles and/or a decrease in the collimator size. A few insights into the significance of heterogeneity corrections for treatment planning for intensity modulated radiotherapy will also be presented.

In the field of radiation therapy, much of the research is aimed at developing new and innovative techniques for treating cancer patients with radiation. In recent years, new treatment machines have been developed that provide a much greater degree of computer control than was available with the machines of previous generations. One innovation has been the development of an approach called "tomotherapy.'' Tomotherapy can be defined as computer-controlled rotational radiotherapy delivered using an intensity-modulated fan beam of radiation. The successful implementation of the new delivery techniques requires the development of a suitable approach for optimizing each patient's treatment plan. One of the challenges is to quantify optimality in radiation therapy. We have tested a variety of objective functions and constraints in pursuit of a formulation that performs well for a wide variety of disease sites. An additional challenge stems from the sizable amount of data and the large number of variables that are involved in each optimization. This paper presents several approaches to optimizing treatment plans in radiation therapy, and the advantages and disadvantages of a number of formulations are explored.

The U.S. Coast Guard has been developing a 47′ high-speed, heavy weather motor lifeboat, the 47 MLB, to replace the aging 44′ motor lifeboats. The 47 MLB is designed to be self-righting and operate in up to 20′ breaking waves. The prototype 47 MLB has been in service for four years, and five pre-production boats have been built by Textron Marine Systems in New Orleans, La. If the pre-production boats prove to be successful, plans call for 100 boats to be built in the production run. One of the primary goals in developing a new motor lifeboat was to make major improvements with regard to crew safety, comfort, and efficiency. These human engineering requirements have affected almost every stage of the design, and have been the subject of considerable engineering effort. Throughout the development, a logical human engineering program has been followed. This program will continue through the pre-production evaluation and into the production craft development.

Intensity modulated arc therapy (IMAT) is a radiation therapy delivery technique that combines the efficiency of arc based delivery with the dose painting capabilities of intensity modulated radiation therapy (IMRT). A key challenge in developing robust inverse planning solutions for IMAT is the need to account for the connectivity of the beam shapes as the gantry rotates from one beam angle to the next. To overcome this challenge, inverse planning solutions typically impose a leaf motion constraint that defines the maximum distance a multileaf collimator (MLC) leaf can travel between adjacent control points. The leaf motion constraint ensures the deliverability of the optimized plan, but it also impacts the plan quality, the delivery accuracy, and the delivery efficiency. In this work, the authors have studied leaf motion constraints in detail and have developed recommendations for optimizing the balance between plan quality and delivery efficiency.Two steps were used to generate optimized IMAT treatment plans. The first was the direct machine parameter optimization (DMPO) inverse planning module in the Pinnacle(3) planning system. Then, a home-grown arc sequencer was applied to convert the optimized intensity maps into deliverable IMAT arcs. IMAT leaf motion constraints were imposed using limits of between 1 and 30 mm∕deg. Dose distributions were calculated using the convolution∕superposition algorithm in the Pinnacle(3) planning system. The IMAT plan dose calculation accuracy was examined using a finer sampling calculation and the quality assurance verification. All plans were delivered on an Elekta Synergy with an 80-leaf MLC and were verified using an IBA MatriXX 2D ion chamber array inserted in a MultiCube solid water phantom.The use of a more restrictive leaf motion constraint (less than 1-2 mm∕deg) results in inferior plan quality. A less restrictive leaf motion constraint (greater than 5 mm∕deg) results in improved plan quality but can lead to less accurate dose distribution as evidenced by increasing discrepancies between the planned and the delivered doses. For example, the results from our patient-specific quality assurance measurements demonstrated that the average gamma analysis passing rate decreased from 98% to 80% when the allowable leaf motion increased from 3 to 20 mm∕deg. Larger leaf motion constraints also led to longer treatment delivery times (2 to 4 folds) due to the additional MLC leaf motion.Leaf motion constraints significantly impact IMAT plans in terms of plan quality, delivery accuracy, and delivery efficiency with the impact magnified for more complex cases. Our studies indicate that a leaf motion constraint of 2 to 3 mm∕deg of gantry rotation can provide an optimal balance between plan quality, delivery accuracy, and efficiency.

Intensity-modulated arc therapy (IMAT) is a rotational approach to radiation therapy delivered on a conventional linear accelerator using a conventional multileaf collimator. There are 2 key advantages of IMAT. First, the rotational nature of the delivery provides great flexibility in shaping each dose distribution. As a result, IMAT can provide dosimetric advantages relative to fixed-field intensity-modulated radiation therapy (IMRT). The second advantage is the highly efficient nature of the delivery. For centers with an active IMRT program, the clinical implementation of IMAT should be relatively straightforward. For clinical implementation of IMAT, it is important to fully characterize the accuracy of the dose model used, and the performance of the quality assurance equipment.

Intensity-modulated arc therapy (IMAT) is a rotational IMRT technique. It uses a set of overlapping or nonoverlapping arcs to create a prescribed dose distribution. Despite its numerous advantages, IMAT has not gained widespread clinical applications. This is mainly due to the lack of an effective IMAT leaf-sequencing algorithm that can convert the optimized intensity patterns for all beam directions into IMAT treatment arcs. To address this problem, we have developed an IMAT leaf-sequencing algorithm and software using graph algorithms in computer science. The input to our leaf-sequencing software includes (1) a set of (continuous) intensity patterns optimized by a treatment planning system at a sequence of equally spaced beam angles (typically 10 degrees apart), (2) a maximum leaf motion constraint, and (3) the number of desired arcs, k. The output is a set of treatment arcs that best approximates the set of optimized intensity patterns at all beam angles with guaranteed smooth delivery without violating the maximum leaf motion constraint. The new algorithm consists of the following key steps. First, the optimized intensity patterns are segmented into intensity profiles that are aligned with individual MLC leaf pairs. Then each intensity profile is segmented into k MLC leaf openings using a k-link shortest path algorithm. The leaf openings for all beam angles are subsequently connected together to form 1D IMAT arcs under the maximum leaf motion constraint using a shortest path algorithm. Finally, the 1D IMAT arcs are combined to form IMAT treatment arcs of MLC apertures. The performance of the implemented leaf-sequencing software has been tested for four treatment sites (prostate, breast, head and neck, and lung). In all cases, our leaf-sequencing algorithm produces efficient and highly conformal IMAT plans that rival their counterpart, the tomotherapy plans, and significantly improve the IMRT plans. Algorithm execution times ranging from a few seconds to 2 min are observed on a laptop computer equipped with a 2.0 GHz Pentium M processor.

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases were selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle3 treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequenced intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.

Purpose: For treatment planning, clinicians typically compensate for respiratory motion by applying treatment margins that ensure the clinical target volume (CTV) always remains in the treatment field. We have investigated a more sophisticated approach where the pattern of organ motion is directly incorporated into both the dose calculation process and the optimization of IMRT treatment plans, and we have evaluated the degree to which plan quality can be improved by accounting for intra‐fraction organ motion during IMRT optimization. Method and Materials: In this study, we employed a convolution/superposition based dose calculation that incorporates organ motion. For each photon history, the isocenter is randomly sampled from a probability distribution defined by the respiration‐induced anatomical displacement. The resulting blurred pencil beam dose distributions have been incorporated into our IMRT plan optimizations. Comparisons were made between plans optimized using a motion‐based dose calculation and those optimized using a static dose calculation. Tests were performed for both a concave target in a phantom and a lungcancer patient. Results: For the phantom case, the mean dose to the adjacent organ‐at‐risk was reduced from 67.3% to 48.4% of the prescribed dose when motion was included in the optimization. For the lung patient, the volume of the right lung receiving greater than 80% of the prescribed dose was reduced from 14.1% to 7.2% when organ motion was included in the optimization. Conclusion: The motion‐based optimization accounts for the fact that the CTV will not be at all locations with equal probability and is thus more sophisticated than the application of patient specific margins. Consequently, significant additional sparing of critical structures can be achieved by incorporating intra‐fraction organ motion into IMRT optimization. Additionally, the agreement between the predicted and delivered doses is improved because the impact of organ motion has been accounted for in the dose calculation.