Display options
Cite
Ghobadi K, Ghaffari H, Aleman D, et al. SU-D-211-03: An Automated Inverse Planning Optimization Approach for Single- Fraction and Fractionated Radiosurgery Using Gamma Knife Perfexion. Med Phys. 2012;39(6):3610doi: 10.1118/1.4734657.
Ghobadi, K., Ghaffari, H., Aleman, D., Ruschin, M., & Jaffray, D. (2012). SU-D-211-03: An Automated Inverse Planning Optimization Approach for Single- Fraction and Fractionated Radiosurgery Using Gamma Knife Perfexion. Medical physics, 39(6), 3610. https://doi.org/10.1118/1.4734657
Ghobadi, K, et al. "SU-D-211-03: An Automated Inverse Planning Optimization Approach for Single- Fraction and Fractionated Radiosurgery Using Gamma Knife Perfexion." Medical physics vol. 39,6 (2012): 3610. doi: https://doi.org/10.1118/1.4734657
Ghobadi K, Ghaffari H, Aleman D, Ruschin M, Jaffray D. SU-D-211-03: An Automated Inverse Planning Optimization Approach for Single- Fraction and Fractionated Radiosurgery Using Gamma Knife Perfexion. Med Phys. 2012 Jun;39(6):3610. doi: 10.1118/1.4734657. PMID: 28517428.
Copy Download .nbib Format: NLM
Share it on

Med Phys. 2012 Jun;39(6):3610. doi: 10.1118/1.4734657.

SU-D-211-03: An Automated Inverse Planning Optimization Approach for Single- Fraction and Fractionated Radiosurgery Using Gamma Knife Perfexion.

Medical physics

K Ghobadi, H Ghaffari, D Aleman, M Ruschin, D Jaffray

Affiliations

  1. University of Toronto, Toronto, Ontario, Canada.
  2. Odette Cancer Centre, Toronto, Canada.
  3. Princess Margaret Hospital, Toronto, Ontario, Canada.

PMID: 28517428 DOI: 10.1118/1.4734657

Abstract

PURPOSE: The purpose of this work is to develop an automated inverse planning approach to generate singe-fraction and fractionated stereotactic radiosurgery (SRS) treatment plans for Gamma Knife Perfexion.

METHODS: Our automated approach consists of two steps: 1) a grassfire-based algorithm to carefully determine the isocentre locations; 2) a penalty-based optimization to find the optimal shot shapes and their intensities to minimize the deviation of the delivered dose from the objective dose in all structures. For single-fraction SRS, a margin-less approach was taken: conformity of dose to the gross tumor volume (GTV) with a steep dose fall-off was prioritized. For fractionated radiosurgery, dose homogeneity was given a higher priority since planning target volumes (PTV) were applied to account for daily setup variation, and these PTVs could overlap with organs-at-risk (OARs). The two-step approach was tested on seven clinical cases with PTV sizes of 0.5cm̂3-56.5cm̂3. In the tested cases, the PTV had 0%-38% overlap with OARs.

RESULTS: For single-fraction SRS, the dose to 1mm̂3 brainstem was on average 0.24Gy (range: -2.4Gy to +2.0Gy) lower compared to manually-generated plans. Beam-on time varied with the number of isocentres, but on average was 33min longer than manually- generated plans. The optimization algorithm took 215min on average, while isocentre selection performed in <10s.For fractionated SRS, the average PTV coverage was V95=94.9% (range: 92.7%-97.6%) and the mean dose to 1 mm̂3 brainstem was 87.8% of the prescription dose (range: 35.4%- 108.8%). The mean beam-on time per fraction per dose-per-fraction was 4.8min/Gy (range: 0.9min/Gy-10.3min/Gy). We observed a tradeoff between conformity and OARs-sparing in both plans, and added sensitivity to isocentre locations in fractionated plans. In all the cases, GTV received the full prescription dose.

CONCLUSIONS: The results indicated that automated inverse planning yields improved conformity and OAR-sparing for single- fraction SRS and is capable of generating homogeneous fractionated SRS. This work is partially funded by Elekta Instrument, AB, Stockholm, Sweden.

© 2012 American Association of Physicists in Medicine.

Keywords: Cancer; Optimization; Radiosurgery

Publication Types