Prostate implant evaluation using tumour control probability--the effect of input parameters.

Area of Science:

• Medical Physics
• Oncology
• Radiotherapy

Background:

• Permanent prostate implants are a radiotherapy technique for localized prostate cancer.
• Accurate dosimetry and understanding treatment parameter effects are crucial for optimizing tumor control probability (TCP).
• Prostate cancer models often simplify tissue heterogeneity and cellular response to radiation.

Purpose of the Study:

• To evaluate the impact of treatment parameter variations on a prostate implant model.
• To assess the uncertainty in calculated tumor control probability (TCP) values.
• To determine the model's ability to identify sub-sections at risk of local recurrence.

Main Methods:

• A 12-sub-section prostate model incorporating cell density based on cancer foci probability.
• Analysis of wasted dose due to dose rate below adequate levels for repopulation.
• Evaluation of TCP uncertainty across different dose distributions and parameter variations (radiosensitivity, repopulation rates, alpha distribution).

Main Results:

• Wasted dose varied by 2-16% across radiosensitivity and repopulation rates.
• Uncertainty in TCP was generally <12% for good quality implants but higher for poor quality implants.
• Heterogeneous alpha distribution and Gaussian cutoff values significantly impacted calculated TCP.

Conclusions:

• The model can identify sub-sections at risk of local recurrence despite parameter uncertainties.
• Calculated TCP values are best considered in a relative, not absolute, sense due to inherent model parameter variability.
• Understanding parameter effects is vital for refining permanent prostate implant treatment planning.