Efficiency enhancements of a Monte Carlo beamlet based treatment planning process: implementation and parameter study.

Mueller, Silvan; Guyer, Gian; Volken, Werner; Frei, Daniel; Torelli, Nathan; Aebersold, Daniel M; Manser, Peter; Fix, Michael K (2023). Efficiency enhancements of a Monte Carlo beamlet based treatment planning process: implementation and parameter study. Physics in medicine and biology, 68(4) IOP Publishing 10.1088/1361-6560/acb480

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OBJECTIVE

The computational effort to perform beamlet calculation, plan optimization and final dose calculation of a treatment planning process (TPP) generating intensity modulated treatment plans is enormous, especially if Monte Carlo (MC) simulations are used for dose calculation. The goal of this work is to improve the computational efficiency of a fully MC based TPP for static and dynamic photon, electron and mixed photon-electron treatment techniques by implementing multiple methods and studying the influence of their parameters.

APPROACH

A framework is implemented calculating MC beamlets efficiently in parallel on each available CPU core. The user can specify the desired statistical uncertainty of the beamlets, a fractional sparse dose threshold to save beamlets in a sparse format and minimal distances to the PTV surface from which 2x2x2=8 (medium) or even 4x4x4=64 (large) voxels are merged. The compromise between final plan quality and computational efficiency of beamlet calculation and optimization is studied for several parameter values to find a reasonable trade-off. For this purpose, four clinical and one academic case are considered with different treatment techniques.

MAIN RESULTS

Setting the statistical uncertainty to 5% (photon beamlets) and 15% (electron beamlets), the fractional sparse dose threshold relative to the maximal beamlet dose to 0.1% and minimal distances for medium and large voxels to the PTV to 1 cm and 2 cm, respectively, does not lead to substantial degradation in final plan quality. Only OAR sparing is slightly degraded. Furthermore, computation times are reduced by about 58% (photon beamlets), 88% (electron beamlets) and 96% (optimization) compared to using 2.5% (photon beamlets) and 5% (electron beamlets) statistical uncertainty and no sparse format nor voxel merging.

SIGNIFICANCE

Several methods are implemented improving computational efficiency of beamlet calculation and plan optimization of a fully MC based TPP without substantial degradation in final plan quality.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Radiation Oncology
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Radiation Oncology > Medical Radiation Physics

UniBE Contributor:

Müller, Silvan Andreas, Guyer, Gian Mauro Carlo, Volken, Werner, Frei, Daniel, Aebersold, Daniel Matthias, Manser, Peter, Fix, Michael

Subjects:

500 Science > 530 Physics
600 Technology > 610 Medicine & health

ISSN:

1361-6560

Publisher:

IOP Publishing

Language:

English

Submitter:

Pubmed Import

Date Deposited:

23 Jan 2023 14:54

Last Modified:

14 Feb 2023 00:16

Publisher DOI:

10.1088/1361-6560/acb480

PubMed ID:

36655485

Uncontrolled Keywords:

Monte Carlo beamlet efficiency inverse planning treatment planning

BORIS DOI:

10.48350/177696

URI:

https://boris.unibe.ch/id/eprint/177696

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