Quantification of proton dose calculation accuracy in the lung

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Accurate dose calculation is critical for effective proton therapy, especially in lung cancer where tissue heterogeneity poses challenges.
• Clinical proton treatment planning systems (TPS) may have limitations in accurately modeling dose distributions in lung tissue.
• Monte Carlo (MC) simulations offer a more detailed approach to dose calculation but require validation for clinical use.

Purpose of the Study:

• To evaluate the accuracy of a clinical proton treatment planning system (TPS) against Monte Carlo (MC) based dose calculations using phantom and patient data.
• To assess the clinical impact of TPS versus MC dose calculations for lung tumors treated with proton therapy.
• To quantify the differences in dose to the target volume and organs at risk, as well as range uncertainties.

Main Methods:

• Dose measurements were performed using an ion chamber array in a lung phantom to determine dose and distal fall-off.
• Results from phantom measurements were compared with calculations from the TPS and MC simulations.
• MC dose distributions were simulated for 19 patients (54 fields) with lung tumors and compared to TPS calculations.

Main Results:

• MC calculations demonstrated superior accuracy in lung tissue, reproducing measurements within ±2% and showing a 1.6% average dose difference compared to TPS's 5.6%.
• MC simulations predicted a mean target dose 3.4% lower than TPS, with significant differences in small fields, and higher doses to normal lung (V5, V10) due to wider penumbra.
• MC reduced range uncertainty by approximately half compared to TPS (3.9 mm vs. 7 mm average difference), with potential for significant impact on critical structures distal to the target.

Conclusions:

• Integrating MC dose calculation into clinical practice can improve proton therapy for lung cancer by preventing systematic overestimation of target dose and underestimation of normal lung dose.
• MC's improved accuracy in range prediction allows for confident reduction of range margins, potentially leading to decreased toxicity for all patients.
• These findings support the clinical adoption of MC techniques to enhance the quality and safety of proton therapy for lung malignancies.