Intensity modulated proton therapy plan generation in under ten seconds.

Matter, Michael; Nenoff, Lena; Meier, Gabriel; Weber, Damien C.; Lomax, Antony J; Albertini, Francesca (2019). Intensity modulated proton therapy plan generation in under ten seconds. (In Press). Acta oncologica, pp. 1-5. Taylor & Francis 10.1080/0284186X.2019.1630753

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Treatment planning for intensity modulated proton therapy (IMPT) can be significantly improved by reducing the time for plan calculation, facilitating efficient sampling of the large solution space characteristic of IMPT treatments. Additionally, fast plan generation is a key for online adaptive treatments, where the adapted plan needs to be ideally available in a few seconds. However, plan generation is a computationally demanding task and, although dose restoration methods for adaptive therapy have been proposed, computation times remain problematic. IMPT plan generation times were reduced by the development of dedicated graphical processing unit (GPU) kernels for our in-house, clinically validated, dose and optimization algorithms. The kernels were implemented into a coherent system, which performed all steps required for a complete treatment plan generation. Using a single GPU, our fast implementation was able to generate a complete new treatment plan in 5-10 sec for typical IMPT cases, and in under 25 sec for plans to very large volumes such as for cranio-spinal axis irradiations. Although these times did not include the manual input of optimization parameters or a final clinical dose calculation, they included all required computational steps, including reading of CT and beam data. In addition, no compromise was made on plan quality. Target coverage and homogeneity for four patient plans improved (by up to 6%) or remained the same (changes <1%). No worsening of dose-volume parameters of the relevant organs at risk by more than 0.5% was observed. Fast plan generation with a clinically validated dose calculation and optimizer is a promising approach for daily adaptive proton therapy, as well as for automated or highly interactive planning.

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

UniBE Contributor:

Weber, Damien Charles

Subjects:

600 Technology > 610 Medicine & health

ISSN:

1651-226X

Publisher:

Taylor & Francis

Language:

English

Submitter:

Beatrice Scheidegger

Date Deposited:

08 Aug 2019 09:04

Last Modified:

08 Aug 2019 09:13

Publisher DOI:

10.1080/0284186X.2019.1630753

PubMed ID:

31271095

BORIS DOI:

10.7892/boris.131835

URI:

https://boris.unibe.ch/id/eprint/131835

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