Improving IMRT-plan quality with MLC leaf position refinement post plan optimization

Enhanced optimization of volumetric modulated arc therapy plans using Monte Carlo generated beamlets

PURPOSE

A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed-computing framework.

METHODS

DICOM files for clinical VMAT plans files are exported from the TPS and used to generate input files for the EGSnrc MC toolkit. Beamlet doses are calculated using the MC routines, each corresponding to a single multileaf collimator leaf from a single control point traveling 0.5 cm in or out of the field. A typical VMAT plan requires 5000 to 10 000 beamlets, which may be calculated overnight. This results in a ternary-valued objective function, which may use the same clinical objectives as the original VMAT plan. A simple greedy search algorithm is applied to minimize this function and determine the optimal set of ternary variables. The resulting modified control point parameters are imported into the TPS to calculate the final, deliverable dose, and to compare the EO plan with the original. EO was evaluated retrospectively on seven VMAT plans (two adult brain, one pediatric brain, two head and neck, and two prostate). Additionally, the use of stricter objectives was investigated for two of the cases: the left cochlea planning organ at risk (OAR) volume objective for the pediatric brain case, and the rectum objective for a prostate case.

RESULTS

EO produced improved objective scores (by 6% to 60%) and dose-volume histograms (DVH) for the brain plans and the head and neck plans. For each of these plans, the target dose minimum and homogeneity were preserved, while one or more of the OAR DVH's was reduced. Although EO also reduced the objective scores for the prostate plans (by 46% and 79%), their absolute score and DVH improvements were not substantial. The stricter objective on the pediatric brain case resulted in lower dose to the OAR without compromising the target dose. However, the rectum dose in the prostate case could not be improved without reducing dose homogeneity to the planning target volume, suggesting that VMAT prostate cases may already be highly optimized by the TPS.

CONCLUSION

We have developed a novel approach to improving the dose distribution of VMAT plans, which relies on MC calculations to provide small modifications to the control points. This method may be particularly useful for complex treatments in which a certain OAR is of concern and it is difficult for the treatment planner to obtain an acceptable solution with the TPS. Further development will reduce the beamlet computation time and result in more sophisticated EO treatment planning methods.

Improvement of VMAT plan quality for head and neck cancer with high resolution fluences generated by couch shift between arcs

PURPOSE

To investigate the changes in quality of the volumetric modulated arc therapy (VMAT) plans with couch-shift between arcs by half of a multi-leaf collimator (MLC) leaf width.

METHODS

A total of 22 patients with head-and-neck cancer were retrospectively selected. Since the smallest MLC leaf width was 5 mm in this study, the couch was shifted by 2.5 mm in the longitudinal-direction between arcs to increase the resolution of fluence map. A total of three types of VMAT plans were generated for each patient; the three types of plans were a two-full-arc plan without couch-shift (NS plan), a two-half-arc-pair plan with couch-shift (HAS plan), and a two-full-arc pair plan with couch-shift (FAS plan). Changes in the dose-volumetric parameters were investigated.

RESULTS

The FAS plan showed the best plan quality for the target volumes and organs at risk compared to the NS and HAS plans. However, the magnitudes of differences among the three types of plans were minimal, and every plan was clinically acceptable. The average integral doses of the NS, HAS, and FAS plans were 160,549 ± 37,600 Gy-cc, 147,828 ± 33,343 Gy-cc, and 156,030 ± 36,263 Gy-cc, respectively. The average monitor unit of the NS, HAS, and FAS plans were 717 ± 120 MU, 648 ± 100 MU, and 763 ± 158 MU, respectively.

CONCLUSIONS

The HAS plan was better than the others in terms of normal tissue sparing and plan efficiency. By shifting the couch by half of the MLC leaf width in the longitudinal direction between arcs, the VMAT plan quality could be improved.

Direct aperture optimization using an inverse form of back-projection

Direct aperture optimization (DAO) has been used to produce high dosimetric quality intensity-modulated radiotherapy (IMRT) treatment plans with fast treatment delivery by directly modeling the multileaf collimator segment shapes and weights. To improve plan quality and reduce treatment time for our in-house treatment planning system, we implemented a new DAO approach without using a global objective function (GFO). An index concept is introduced as an inverse form of back-projection used in the CT multiplicative algebraic reconstruction technique (MART). The index, introduced for IMRT optimization in this work, is analogous to the multiplicand in MART. The index is defined as the ratio of the optima over the current. It is assigned to each voxel and beamlet to optimize the fluence map. The indices for beamlets and segments are used to optimize multileaf collimator (MLC) segment shapes and segment weights, respectively. Preliminary data show that without sacrificing dosimetric quality, the implementation of the DAO reduced average IMRT treatment time from 13 min to 8 min for the prostate, and from 15 min to 9 min for the head and neck using our in-house treatment planning system PlanUNC. The DAO approach has also shown promise in optimizing rotational IMRT with burst mode in a head and neck test case.