Dosimetric comparison of inverse and forward planning for Gamma Knife stereotactic radiosurgery of brain metastases

Med Dosim. 2020;45(4):317-320. doi: 10.1016/j.meddos.2020.03.002. Epub 2020 Jun 7.

Abstract

The Leksell GammaPlan (LGP) with an inverse planning (IP) tool has been upgraded to version 11.1 since its launch in 2010. We evaluated its IP planning performance by re-planning 16 targets that had been planned using forward planning (FP). The FP and IP plans were compared. A planning guideline for IP process was developed aiming for an unbiased comparison. Sixteen brain metastases (BMs) without nearby critical structures were included in the study (size > 1 cm for all targets). All prior FP were re-planned in the LGP using IP and maintaining the same beam-on time and coverage. The dose to all the targets was scaled to 20 Gy in a single fraction at 50% isodose line (IDL) for FP and IP comparison purpose. The coverage and beam-on time were nearly the same for both the FP and IP plans. For all the IP plans, the mean selectivity was 0.85 ± 0.04 (vs 0.83 ± 0.04 in FP plans, p = 0.02), the mean GI was 2.92 ± 0.21 (vs 3.18 ± 0.60 in FP plans, p = 0.047), the mean V12Gy was 8.18 ± 8.57 cc (vs 9.09 ± 9.08 cc in FP plans, p = 0.001), the mean V8Gy was 14.63 ± 15.14 cc (vs 16.34 ± 16.17 cc in FP plans, p = 0.001), and the mean V5Gy was 29.01 ± 28.77 cc (vs 32.77 ± 31.41 cc in FP plans, p = 0.001). The number of shots was higher in IP plans (means of 16.69 ± 8.11 vs 10.81 ± 6.87 in FP plans, p = 0.001). We retrospectively re-planned 16 FP plans using the IP tool while meeting the quality limiting factors for the FP plans. The dosimetry parameters from the IP plans outperformed the treated FP plans and the IP tool should be preferred for tumors with size > 1 cm.

Keywords: Forward planning; Gamma Knife; Inverse planning; Selectivity and gradient index.

MeSH terms

  • Brain Neoplasms* / radiotherapy
  • Brain Neoplasms* / surgery
  • Humans
  • Radiometry
  • Radiosurgery*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted
  • Retrospective Studies