Sensitivity analysis of parameters in linear-quadratic radiobiologic modeling.

Area of Science:

• Radiation oncology
• Biophysical modeling
• Radiotherapy dose calculation

Background:

• Radiobiologic modeling is essential for optimizing radiotherapy treatment plans, particularly for dose escalation.
• The linear-quadratic (LQ) model is a cornerstone in predicting treatment outcomes based on dose and fractionation.
• Accurate modeling is vital for minimizing side effects and maximizing tumor control.

Purpose of the Study:

• To quantify the sensitivity of the LQ model's biologically equivalent dose (BED) calculations to variations in its individual parameters.
• To assess how parameter uncertainties affect dose estimations for tumor control, acute mucosal reactions, and late complications.
• To compare the robustness of LQ model calculations with equivalent uniform dose (EUD) under altered treatment conditions.

Main Methods:

• Calculated equivalent total doses (EQD2) using the LQ formula, incorporating overall treatment time.
• Systematically varied each of the five biologic parameters in the LQ formula by +/-10% and +/-20%.
• Quantified the resulting percentage change in EQD2 for tumor, acute, and late effects under conventional and stereotactic body radiotherapy (SBRT) schedules.

Main Results:

• For conventional schedules, a 1% parameter change caused 0.1%–0.45% variation in tumor/acute EQD, with overall time being most influential.
• Late effect EQD varied by 0.4%–0.6% per 1% parameter change, primarily driven by the alpha/beta ratio.
• SBRT schedules exhibited larger variations: 0.6%–0.9% for tumor and 1.6%–1.9% for late effects per 1% parameter change.

Conclusions:

• The LQ model demonstrates robustness similar to EUD due to inherent mathematical properties.
• Total dose, dose per fraction, and dose rate remain the primary drivers of radiobiologic effects.
• Understanding parameter sensitivity is key for reliable dose escalation and treatment plan optimization in radiotherapy.