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. 2021 Jul;22(7):245-254.
doi: 10.1002/acm2.13316. Epub 2021 Jun 20.

Reducing variability among treatment machines using knowledge-based planning for head and neck, pancreatic, and rectal cancer

Hideaki Hirashima  1 , Mitsuhiro Nakamura  1   2 , Nobutaka Mukumoto  1 , Ryo Ashida  1 , Kota Fujii  1 , Kiyonao Nakamura  1 , Aya Nakajima  1 , Katsuyuki Sakanaka  1 , Michio Yoshimura  1 , Takashi Mizowaki  1
Affiliations

Reducing variability among treatment machines using knowledge-based planning for head and neck, pancreatic, and rectal cancer

Hideaki Hirashima et al. J Appl Clin Med Phys. 2021 Jul.

Abstract

Purpose: This study aimed to assess dosimetric indices of RapidPlan model-based plans for different energies (6, 8, 10, and 15 MV; 6- and 10-MV flattening filter-free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual-layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans.

Methods: RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and neck, pancreatic, and rectal cancer, respectively. RapidPlan models of head and neck, pancreatic, and rectal cancer were created for TrueBeam STx (High Definition 120) with 6 MV, TrueBeam STx with 10-MV flattening filter-free, and Clinac iX (Millennium 120) with 15 MV, respectively. The models were used to create volumetric-modulated arc therapy plans for a 10-patient test dataset using all energy and MLC types at all disease sites. The Holm test was used to compare multiple dosimetric indices in different treatment machines and energy types.

Results: The dosimetric indices for planning target volume and organs at risk in RapidPlan model-based plans were comparable to those in the clinical plan. Furthermore, no dose difference was observed among the RapidPlan models. The variability among RapidPlan models was consistent regardless of the treatment machines, MLC types, and energy.

Conclusions: Dosimetric indices of RapidPlan model-based plans appear to be comparable to the ones based on clinical plans regardless of energies, MLC types, and disease sites. The results suggest that the RapidPlan model can generate treatment plans independent of the type of treatment machine.

Keywords: different treatment machine; disease site; energy; knowledge-based planning; multileaf collimator type.

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Figures

Fig. 1
Fig. 1
Overall scheme of this study.
Fig. 2
Fig. 2
Dose distribution of both clinical plan and RapidPlan model‐based plan (e.g., Halcyon) in head and neck cancer, pancreatic cancer, and rectal cancer.
Fig. 3
Fig. 3
Average predicted dose‐volume histograms in the treatment of (a) head and neck cancer, (b) pancreatic cancer, and (c) rectal cancer.
See this image and copyright information in PMC

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