Optimization of Fluence Map for CyberKnife Raster Scanning Intensity Modulated Radiotherapy.


Journal

Anticancer research
ISSN: 1791-7530
Titre abrégé: Anticancer Res
Pays: Greece
ID NLM: 8102988

Informations de publication

Date de publication:
Apr 2023
Historique:
received: 20 12 2022
revised: 06 01 2023
accepted: 23 01 2023
medline: 29 3 2023
entrez: 28 3 2023
pubmed: 29 3 2023
Statut: ppublish

Résumé

Stereotactic body radiotherapy for prostate cancer using CyberKnife with circular cone requires a long treatment time. Raster scanning intensity modulated radiotherapy (RS-IMRT) has a potential of improving treatment efficacy, introducing shorter treatment time, better target dose uniformity, and lower organ at risk (OAR) dose. The purpose of the study was to develop a fluence optimization system for RS-IMRT. RS-IMRT plans were created for five prostate cancer patients treated with the Novalis system and parameters were compared to the Novalis treatment plans. From 80 nodes available for the CyberKnife, twelve nodes were arbitrarily selected. On the beam's eye view of each beam, a 100×100 matrix of optimization points was created at the target center plane. The beam fluence map was optimized using the attraction-repulsion model (ARM). The beam fluence maps were converted to the scanning sequence using the ARM and a final dose calculation was performed. For planning target volume (PTV), RS-IMRT plans showed higher dose covering 2% of the volume (D We developed a fluence optimization system for RS-IMRT that performs the entire RS-IMRT treatment planning process, including scanning sequence optimization and final dose calculation. The RS-IMRT was capable of generating clinically acceptable plans.

Sections du résumé

BACKGROUND/AIM OBJECTIVE
Stereotactic body radiotherapy for prostate cancer using CyberKnife with circular cone requires a long treatment time. Raster scanning intensity modulated radiotherapy (RS-IMRT) has a potential of improving treatment efficacy, introducing shorter treatment time, better target dose uniformity, and lower organ at risk (OAR) dose. The purpose of the study was to develop a fluence optimization system for RS-IMRT.
PATIENTS AND METHODS METHODS
RS-IMRT plans were created for five prostate cancer patients treated with the Novalis system and parameters were compared to the Novalis treatment plans. From 80 nodes available for the CyberKnife, twelve nodes were arbitrarily selected. On the beam's eye view of each beam, a 100×100 matrix of optimization points was created at the target center plane. The beam fluence map was optimized using the attraction-repulsion model (ARM). The beam fluence maps were converted to the scanning sequence using the ARM and a final dose calculation was performed.
RESULTS RESULTS
For planning target volume (PTV), RS-IMRT plans showed higher dose covering 2% of the volume (D
CONCLUSION CONCLUSIONS
We developed a fluence optimization system for RS-IMRT that performs the entire RS-IMRT treatment planning process, including scanning sequence optimization and final dose calculation. The RS-IMRT was capable of generating clinically acceptable plans.

Identifiants

pubmed: 36974800
pii: 43/4/1637
doi: 10.21873/anticanres.16314
doi:

Substances chimiques

Etoposide 6PLQ3CP4P3
Carmustine U68WG3173Y

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1637-1642

Informations de copyright

Copyright © 2023 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Auteurs

Yuichi Akino (Y)

Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Japan; akino@radonc.med.osaka-u.ac.jp.
Soseikai CyberKnife Center, Kyoto, Japan.
Miyakojima IGRT Clinic, Osaka, Japan.

Hiroya Shiomi (H)

Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Japan.
Soseikai CyberKnife Center, Kyoto, Japan.
Miyakojima IGRT Clinic, Osaka, Japan.

Nobuhisa Mabuchi (N)

Soseikai CyberKnife Center, Kyoto, Japan.

Norihisa Masai (N)

Department of Radiology, Kyoto Prefectural University Graduate School of Medical Science, Kyoto, Japan.

Ryoong-Jin Oh (RJ)

Miyakojima IGRT Clinic, Osaka, Japan.

Kazuhiko Ogawa (K)

Department of Radiation Oncology, Osaka University Graduate School of Medicine, Suita, Japan.

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Classifications MeSH