A Pareto‐based beam orientation optimization method for spot scanning intensity‐modulated proton therapy. Issue 5 (13th March 2020)

• Record Type: Journal Article
• Authors: Kamal Sayed, Hisham; Herman, M. G.; Beltran, C. J.
• Other Names: El Naqa Issam guestEditor.; Das Shiva K. guestEditor.
• Is Part Of: Medical physics. Volume 47:Issue 5(2020)
• Page Start: 2049
• Page End: 2060
• Publication Date: 2020-03-13
• Subjects: GPU -- multicriteria optimization -- proton therapy; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.14096
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: To provide a proof of principle of a Pareto‐based method to automatically generate optimal intensity‐modulated proton therapy (IMPT) plans for various noncoplanar beam orientations. Methods: A novel multicriteria beam orientation optimization (MCBOO) method was developed to generate Pareto database of optimal plans. The MCBOO method automatically explores the beam orientations and the scalarization parameters of the IMPT plans simultaneously. The MCBOO method is based on multicriteria bilevel optimization (i.e., hierarchical optimization with two nested levels, named the upper and lower level optimization). In MCBOO, the upper level optimization explores the noncoplanar beam orientation space, while the lower level explores the scalarization parameters for a given beam orientation. Differential evolution method was used in both levels, and the Pareto optimal plans were aggregated from the bilevel optimizations to construct the Pareto database. The MCBOO method was implemented on a multinode multi‐GPU cluster, and it was tested on three brain tumor patient cases. The Pareto database of the three patients was generated for a set of DVH‐based objectives. A statistical analysis was performed between a selected set of MCBOO plans and the manual plan (plan with manually selected beam orientation based on the clinical experience and optimized with the same single plan iterative optimizer used in the MCBOO). The selected set of MCBOO plans consisted of plans that matched the performance of the manual plan [i.e., MCBOO plans that have the same target coverage (within 2%) as the manual plan or better and achieved the same dose (within 2%) or lower to all of the organs at risks (OARs) but one OAR]. Additionally, a dosimetric comparison between of one of the selected MCBOO plans vs the manual plan was conducted. Results: The multicriteria beam orientation optimization algorithm automatically generated Pareto plans for the three noncoplanar brain tumor cases. The MCBOO plans provided an alternative objective trade‐offs to the manual plan. The selected MCBOO plans showed a reduction in dose to multiple organs at risk vs the manual plan with a maximum value which ranged between 10.8 and 12.9 Gy for the three patients. The trade‐off of the OAR dose reduction resulted in higher dose to no more than one OAR for each of the selected MCBOO plans vs the manual plan. The maximum dose increase in the MCBOO plans over the manual plan ranged from 7.8 to 11.8 Gy. Conclusions: A novel multicriteria beam orientation optimization method was developed and tested on three IMPT patient cases. The method automatically generates Pareto plans database by exploring the noncoplanar beam orientations. The method was able to identify beam orientations with Pareto optimal plans that are comparable to the manually created plans with varying objective trade‐offs. Abstract :