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IMRT optimization including random and systematic geometric errors based on the expectation of TCP and NTCP
Marnix G Witte1, Joris van der Geer, Christoph Schneider
1Department of Radiation Oncology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
Medical Physics
|October 12, 2007
Summary
A new probabilistic planning method for prostate cancer radiotherapy improves treatment by balancing tumor control and reducing rectal toxicity. This approach accounts for uncertainties, offering better outcomes than conventional techniques.
Area of Science:
- Radiation Oncology
- Medical Physics
- Computational Biology
Background:
- Accurate radiotherapy planning requires accounting for geometrical uncertainties.
- Traditional methods often rely on predefined margins, which may not be optimal.
- Biological objectives like tumor control and normal tissue complication probabilities are crucial for treatment efficacy.
Purpose of the Study:
- To develop and evaluate a probabilistic planning method using biological cost functions (tumor control probability [TCP] and normal tissue complication probability [NTCP]) without predefined margins.
- To integrate geometrical uncertainties into inverse planning for improved treatment robustness.
- To compare this probabilistic approach against conventional planning strategies for prostate cancer patients.
Main Methods:
- Developed a probabilistic planning method incorporating TCP and NTCP objective functions.
- Modeled random errors by dose blurring and systematic errors by structure shifting.
- Generated treatment plans for 19 prostate patients using four strategies: conformal, simultaneous integrated boost, margin-based biological optimization, and probabilistic optimization.
- Evaluated plans using Monte Carlo simulations of treatment histories with geometrical uncertainties.
Main Results:
- Probabilistic optimization significantly reduced rectal wall dose while increasing clinical target volume dose.
- Achieved a 50% reduction in expected rectal toxicity compared to the boost technique, without compromising local control.
- Outperformed conformal and margin-based biological techniques in terms of toxicity and control rate variability.
- Probabilistic technique showed higher sensitivity to geometrical error distribution variations.
Conclusions:
- Probabilistic optimization using TCP and NTCP is a feasible and effective method for prostate cancer radiotherapy.
- This approach yields robust treatment plans with an improved balance between local tumor control and rectal toxicity.
- The method offers a significant advantage over conventional planning techniques by directly addressing uncertainties and biological outcomes.
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