Radiobiological parameters in a tumour control probability model for prostate cancer LDR brachytherapy

Area of Science:

• Radiation oncology
• Medical physics
• Cancer research

Background:

• Accurate radiobiological parameters are crucial for effective prostate cancer radiotherapy planning.
• Tumor control probability (TCP) models require validated parameters to predict treatment outcomes.
• Low-dose-rate (LDR) brachytherapy for prostate cancer offers a rich dataset for model validation.

Purpose of the Study:

• To recommend radiobiological parameters for prostate cancer treatment planning.
• To validate existing parameters and estimate new ones using clinical data.
• To assess parameter sensitivity within a TCP model.

Main Methods:

• Utilized clinical outcomes data from 849 prostate cancer patients treated with LDR brachytherapy.
• Applied maximum likelihood estimation for parameter validation and estimation.
• Incorporated a TCP model with radiosensitivity heterogeneity and non-uniform clonogen distribution.

Main Results:

• A previously published parameter set with 196,000 clonogens best described the patient cohort.
• Maximum likelihood estimation fitting of all parameters was not feasible.
• Parameter variations showed sensitivity, with log-normal distribution parameters for alpha (α) causing the largest changes in TCP.

Conclusions:

• Recommend using a previously published parameter set for future TCP model applications.
• Advocate for patient-specific, non-uniform clonogen density distributions, potentially from multiparametric imaging.
• Reducing parameter uncertainties enhances confidence in biological models for radiotherapy planning.