Journal article
Development and in silico validation of an online adaptive workflow for proton therapy with an in-room synchrocyclotron and CT-on-rails
International journal of radiation oncology, biology, physics
07/29/2026
DOI: 10.1016/j.ijrobp.2026.07.032
PMID: 42526650
Abstract
Development and validation of an online adaptive proton therapy workflow for clinical use.
A script-based online adaptive proton therapy workflow was developed in a graphics processing unit (GPU)-accelerated treatment planning system (TPS) to automate plan adaptation using traditional CT images acquired on an in-room CT-on-rails. Monte Carlo (MC) -based secondary dose calculation and log file analysis of machine parameters were integrated into the workflow to provide quality assurance (QA) pre- and post- plan delivery for the adapted treatment plan. In silico retrospective testing was performed with ten previously treated pelvic patients for validation of the workflow, a total of 50 fractions were included in this study. The fidelity of adapted dose distributions, time required for the in-silico workflow, and QA results were recorded and analyzed.
The median (inter-quartile range, IQR) time required for this workflow was 61.9 (12.2) minutes, demonstrating technical feasibility for online adaptation. Of the 50 evaluated fractions, 15 (30%) showed clinically meaningful improvements in sparing of highest-priority organ-at-risk (OAR) using the adaptive plans (PA), and 8 (16%) showed improved target coverage relative to the scheduled plan. Both MC-based secondary dose checks and log file–based machine QA were within institutional tolerance criteria, confirming the dosimetric accuracy and delivery fidelity of the workflow.
A fully integrated, QA-embedded online adaptive proton therapy workflow using in-room CT-on-rails imaging was developed and validated in silico on a clinical proton beamline. The workflow demonstrated clinically acceptable treatment times and reliable dosimetric accuracy and provided measurable benefits in OAR sparing and target coverage for a substantial subset of fractions. These results support the readiness of this workflow for clinical use.
Details
- Title: Subtitle
- Development and in silico validation of an online adaptive workflow for proton therapy with an in-room synchrocyclotron and CT-on-rails
- Creators
- Hailei Zhang - Washington University in St. LouisWeiren Liu - Washington University in St. LouisAllen Mo - Washington University in St. LouisThomas R. Mazur - Washington University in St. LouisEric Laugeman - Washington University in St. LouisRobbie Beckert - Washington University in St. LouisYao Hao - Washington University in St. LouisNels Knutson - Washington University in St. LouisHyun Kim - Washington University in St. LouisStephanie Perkins - Washington University in St. LouisTianyu Zhao - University of South Florida
- Resource Type
- Journal article
- Publication Details
- International journal of radiation oncology, biology, physics
- DOI
- 10.1016/j.ijrobp.2026.07.032
- PMID
- 42526650
- NLM abbreviation
- Int J Radiat Oncol Biol Phys
- ISSN
- 0360-3016
- eISSN
- 1879-355X
- Publisher
- Elsevier Inc
- Language
- English
- Electronic publication date
- 07/29/2026
- Academic Unit
- Radiation Oncology
- Record Identifier
- 9985222822202771
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