A preliminary study on a multiresolution‐level inverse planning approach for Gamma Knife radiosurgery

Abstract

Purpose: With many plan variables to determine, manual forward planning for Gamma Knife (GK) radiosurgery is very challenging. Inverse planning eases GK planning by determining the variables via solving an optimization problem. However, due to the vast search space, most inverse planning algorithms, including the one provided in Leksell GammaPlan (LGP) treatment planning system, have to predetermine the isocenter locations using some geometric methods and then optimize the shot shapes and durations at these preselected isocenters. This sequential planning scheme does not necessarily lead to optimal isocenter locations and hence globally optimal plans. In this study, we proposed a multiresolution-level (MRL) inverse planning approach, attempting to approach this large-scale GK optimization problem via an iterative method. Methods: In our MRL approach, several rounds of optimizations were performed with a progressively increased resolution used for isocenter candidates. At each round, an optimization problem was solved to optimize the beam-on time for each collimator and sector at each isocenter candidate. The isocenters that obtained nonzero beam-on times at the previous round and their neighbors on a finer resolution were used as new isocenter candidates for the next round of optimization. After plan optimization, shot sequencing was performed to group the optimized sectors to deliverable composite shots. Results: We have tested our MRL approach on six GK cases previously treated in our institution. For the five cases that have a single target, with similar target coverage obtained, our MRL inverse planning approach achieved better plan quality compared to manual forward planning and LGP inverse planning, with higher selectivity (0.73 AE 0.07 vs 0.72 AE 0.08 and 0.62 AE 0.10), lower gradient index (2.71 AE 0.25 vs 2.78 AE 0.24 and 3.00 AE 0.29), lower brainstem D 0.1cc dose (6.10 AE 4.46 Gy vs 8.87 AE 4.82 Gy and 9.17 AE 3.80 Gy), and shorter total beam-on time (62.1 AE 22.9 min vs 83.6 AE 28.2 min and 70.7 AE 16.7 min). For the case that have six targets, compared with manual planning and LGP inverse planning, our MRL approach achieved higher selectivity (0.68 vs 0.57 and 0.47) and lower gradient index (3.77 vs 4.51 and 5.11). The beam-on time of our plan was slightly longer than manual planning and LGP inverse planning (206.4 min vs 204.7 min and 199.3 min). We have also performed sector duration optimization at the isocenters determined by manual planning or the LGP inverse planning, and the resulting plan qualities were found to be inferior to our MRL approach for all the six cases. Conclusions: This preliminary study has demonstrated the efficacy and feasibility of our MRL inverse planning approach for GK radiosurgery.

Systematic evaluation and plan quality assessment of the Leksell® gamma knife® lightning dose optimizer

“…The latter limitation was addressed by the introduction of the gradient index 16 to limit dose outside the target volume, which was added in the LGP v10.0, released in 2010. Although this resulted in a significant improvement over the previous optimizer, manual planning still outperformed inversely optimized plans, especially in plans with multiple target [15]. Inverse optimization tool v11.0.1 was used in combination with manual planning for the lesions optimized using MFP in this study.…”

IntuitivePlan inverse planning performance evaluation for Gamma Knife radiosurgery of AVMs

“…This version of the inverse planning software could potentially streamline the clinical workflow, particularly when applied to planning large, rounded targets in non‐eloquent areas 3 . However, for complex targets, manual planning is usually preferred, particularly by expert planners 9 .…”

Evaluating the impact of prescription isodose line on plan quality using Gamma Knife inverse planning

“…This was very difficult to achieve in Paddick's study, because manual planning was the only choice in GammaPlan with versions earlier than 10; hence, it was not feasible to generate numerous FP plans with consistent planning quality. IP has been developed and reported by multiple groups 3 , 4 , 5 , 6 , 7 , 8 , 9 but not available until LGP version 10.0 was released in 2010. Under the IP feature, the target coverage, CI, GI, and treatment time could be optimized concurrently based on predefined planning settings.…”