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Comparison of Elekta VMAT with helical tomotherapy and fixed field IMRT: plan quality, delivery efficiency and accuracy.

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 Pinnacle3 treatment planning system. HT plans were developed using a Hi-Art II planning station. VMAT plans were generated using both the Pinnacle3 SmartArc IMRT module and a home-grown arc sequencing algorithm. VMAT and HT plans were delivered using Elektas 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 and 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.

An arc-sequencing algorithm for intensity modulated arc therapy.

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.

Dosimetric Impact of Breathing Motion in Lung Stereotactic Body Radiotherapy Treatment Using Image-Modulated Radiotherapy and Volumetric Modulated Arc Therapy

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.

Leaf-sequencing for intensity-modulated arc therapy using graph algorithms

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 generalized inverse planning tool for volumetric-modulated arc therapy.

The recent development in linear accelerator control systems, named volumetric-modulated arc therapy (VMAT), has generated significant interest in arc-based intensity-modulated radiation therapy (IMRT). The VMAT delivery technique features simultaneous changes in dose rate, gantry angle and gantry rotation speed as well as multi-leaf collimator (MLC) leaf positions while radiation is on. In this paper, we describe a generalized VMAT planning tool that is designed to take full advantage of the capabilities of the new linac control systems. The algorithm incorporates all of the MLC delivery constraints such as restrictions on MLC leaf interdigitation and the MLC leaf velocity constraints. A key feature of the algorithm is that it is able to plan for both single- and multiple-arc deliveries. Compared to conventional step-and-shoot IMRT plans, our VMAT plans created using this tool can achieve similar or better plan quality with less MU and better delivery efficiency. The accuracy of the obtained VMAT plans is also demonstrated through plan verifications performed on an Elekta Synergy linear accelerator equipped with a conventional MLC of 1 cm leaf width using a PreciseBeam VMAT linac control system.

Continuous intensity map optimization (CIMO): A novel approach to leaf sequencing in step and shoot IMRT

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 Pinnacles convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacles 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.

Impact of leaf motion constraints on IMAT plan quality, deliver accuracy, and efficiency

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(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. 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.

New Developments in Intensity Modulated Radiation Therapy

As intensity modulated radiation therapy (IMRT) becomes routine clinical practice, its advantages and limitations are better understood. With these new understandings, some new developments have emerged in an effort to alleviate the limitations of the current IMRT practice. This article describes a few of these efforts made at the University of Maryland, including: i) improving IMRT efficiency with direct aperture optimization; ii) broadening the scope of optimization to include the mode of delivery and beam angles; and iii) new planning methods for intensity modulated arc therapy (IMAT).

Comparison of anatomy-based, fluence-based and aperture-based treatment planning approaches for VMAT

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 beams 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.

Stochastic versus deterministic kernel-based superposition approaches for dose calculation of intensity-modulated arcs

Dose calculations for radiation arc therapy are traditionally performed by approximating continuous delivery arcs with multiple static beams. For 3D conformal arc treatments, the shape and weight variation per degree is usually small enough to allow arcs to be approximated by static beams separated by 5 degrees -10 degrees . But with intensity-modulated arc therapy (IMAT), the variation in shape and dose per degree can be large enough to require a finer angular spacing. With the increase in the number of beams, a deterministic dose calculation method, such as collapsed-cone convolution/superposition, will require proportionally longer computational times, which may not be practical clinically. We propose to use a homegrown Monte Carlo kernel-superposition technique (MCKS) to compute doses for rotational delivery. The IMAT plans were generated with 36 static beams, which were subsequently interpolated into finer angular intervals for dose calculation to mimic the continuous arc delivery. Since MCKS uses random sampling of photons, the dose computation time only increased insignificantly for the interpolated-static-beam plans that may involve up to 720 beams. Ten past IMRT cases were selected for this study. Each case took approximately 15-30 min to compute on a single CPU running Mac OS X using the MCKS method. The need for a finer beam spacing is dictated by how fast the beam weights and aperture shapes change between the adjacent static planning beam angles. MCKS, however, obviates the concern by allowing hundreds of beams to be calculated in practically the same time as for a few beams. For more than 43 beams, MCKS usually takes less CPU time than the collapsed-cone algorithm used by the Pinnacle(3) planning system.