Normal Tissue Risk Estimation Using Biological Knowledge-Based Fuzzy Logic in Volumetric Modulated Arc Therapy of...

Area of Science:

• Radiation Oncology
• Medical Physics
• Computational Biology

Background:

• Volumetric Modulated Arc Therapy (VMAT) is standard for prostate cancer radiotherapy.
• Daily uncertainties (setup errors, organ motion) can compromise VMAT effectiveness.
• Prostate and rectal volume changes during treatment necessitate adaptive strategies.

Purpose of the Study:

• To develop and evaluate a novel two-level fuzzy logic method for estimating rectal toxicity.
• To incorporate prostate and rectal motion, and setup uncertainties into toxicity estimation.
• To ensure target dose distribution is not compromised while assessing organ-at-risk (OAR) toxicity.

Main Methods:

• A two-level Mamdani-type fuzzy logic framework was employed.
• Level 1: Determined biological acceptable target margins using tumor control and normal tissue complication probability (NTCP) based on prostate motion.
• Level 2: Assessed rectal toxicity using weekly cone-beam CT (CBCT) data to analyze rectal volume variations and corresponding NTCP.

Main Results:

• Fuzzy planning target volume (PTV) margins were comparable or slightly larger (up to 0.5 mm) than conventional margins.
• The method demonstrated good agreement with conventional margin formulations under 0-5 mm standard deviation (SD) displacement errors.
• The final risk factor for rectal toxicity was qualitatively assessed as clinically acceptable, even with significant displacement errors.

Conclusions:

• The proposed two-level fuzzy logic approach effectively estimates OAR toxicity (rectum) without compromising tumor dose distribution.
• This method accounts for prostate and rectal deformation, even with displacement errors up to 5 mm SD.
• The simple and fast method allows real-time OAR risk assessment and potential treatment margin adjustments based on individual factors.