Biologically optimized helium ion plans: calculation approach and its in vitro validation.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Clinical application of helium ion beams requires accurate treatment planning that accounts for biological effects.
• Raster-scanned helium ion beams produce a complex radiation field including primary ions and secondary fragments.

Purpose of the Study:

• To develop and validate a novel calculation approach for predicting the biological effect of helium ion beams.
• To integrate data-driven biological models into a Monte Carlo treatment planning tool for experimental verification.

Main Methods:

• A novel Monte Carlo treatment planning (MCTP) tool was developed, incorporating data-driven biological models.
• A spread-out Bragg peak (SOBP) in water was optimized and delivered at the Heidelberg Ion Beam Therapy Center (HIT).
• Predictions of cell survival and relative biological effectiveness (RBE) were compared against experimental clonogenic survival data.

Main Results:

• The novel MCTP approach demonstrated a mean absolute survival variation of 5.3% ± 0.9% compared to experimental data.
• Comparisons with the local effect model (LEM) and repair-misrepair-fixation (RMF) model showed good agreement (4.5% ± 0.8% and 5.8% ± 1.1%, respectively).
• The approach accurately estimated biological effects for a clinically relevant scenario.

Conclusions:

• The developed data-driven biological modeling approach integrated into MCTP is feasible for accurate biological effect estimation in helium ion radiotherapy.
• This method provides a foundation for the clinical application of helium ion beams at facilities like HIT.
• Further studies can leverage this approach for optimizing treatment plans and improving patient outcomes.