In silico trial of simulation-free hippocampal-avoidance whole brain adaptive radiotherapy

Alex T. Price, Kylie H. Kang, Francisco J. Reynoso, Eric Laugeman, Christopher D. Abraham, Jiayi Huang, Jessica Hilliard, Nels C. Knutson, Lauren E. Henke

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Background and Purpose: Hippocampal-avoidance whole brain radiotherapy (HA-WBRT) can be a time-consuming process compared to conventional whole brain techniques, thus potentially limiting widespread utilization. Therefore, we evaluated the in silico clinical feasibility, via dose-volume metrics and timing, by leveraging a computed tomography (CT)-based commercial adaptive radiotherapy (ART) platform and workflow in order to create and deliver patient-specific, simulation-free HA-WBRT. Materials and methods: Ten patients previously treated for central nervous system cancers with cone-beam computed tomography (CBCT) imaging were included in this study. The CBCT was the adaptive image-of-the-day to simulate first fraction on-board imaging. Initial contours defined on the MRI were rigidly matched to the CBCT. Online ART was used to create treatment plans at first fraction. Dose-volume metrics of these simulation-free plans were compared to standard-workflow HA-WBRT plans on each patient CT simulation dataset. Timing data for the adaptive planning sessions were recorded. Results: For all ten patients, simulation-free HA-WBRT plans were successfully created utilizing the online ART workflow and met all constraints. The median hippocampi D100% was 7.8 Gy (6.6–8.8 Gy) in the adaptive plan vs 8.1 Gy (7.7–8.4 Gy) in the standard workflow plan. All plans required adaptation at first fraction due to both a failing hippocampal constraint (6/10 adaptive fractions) and sub-optimal target coverage (6/10 adaptive fractions). Median time for the adaptive session was 45.2 min (34.0–53.8 min). Conclusions: Simulation-free HA-WBRT, with commercially available systems, was clinically feasible via plan-quality metrics and timing, in silico.

Original languageEnglish
Article number100491
JournalPhysics and Imaging in Radiation Oncology
StatePublished - Oct 2023


  • Adaptive RT
  • Diagnostic planning
  • Simulation-free


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