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Assessment of PTV margin adequacy for single isocenter multiple brain metastases using genetic algorithms
José Alejandro Rojas-López1,2, Carlos Daniel Venencia3, Miguel Ángel Chesta1
1Facultad de Matemática, Astronomía, Física y Computación, Universidad Nacional de Córdoba, X5000HUA, Av. Medina Allende, Córdoba, Argentina.
Biomedical Physics & Engineering Express
|June 13, 2023
Summary
Optimized margins in single isocenter multiple brain metastases radiosurgery (SIMM-SRS) reduce healthy brain dose by accounting for setup errors. A genetic algorithm (GA) approach automatically adjusts margins, improving safety without compromising target coverage.
Area of Science:
- Medical Physics
- Radiation Oncology
- Computational Biology
Background:
- Single isocenter multiple brain metastases radiosurgery (SIMM-SRS) is a complex technique requiring precise margin definition.
- Setup errors in linac-based radiosurgery can impact dose coverage and healthy tissue exposure.
- Optimizing margins is crucial for balancing treatment efficacy and safety.
Purpose of the Study:
- To evaluate the effect of optimized margins on dose coverage and healthy tissue dose in SIMM-SRS.
- To assess the impact of setup errors (rotations/translations) on SIMM-SRS plans using a genetic algorithm (GA).
- To determine if GA-driven margin optimization can improve safety in SIMM-SRS.
Main Methods:
- Analysis of quality indices including Paddick conformity index (PCI), gradient index (GI), and dose metrics (Dmax, Dmean, V12) for 32 SIMM-SRS plans (256 lesions).
- Utilized a GA with Python packages to calculate maximum shifts from induced setup errors (0.2°/0.2 mm and 0.5°/0.5 mm) in 6 degrees of freedom.
- Compared quality indices of original plans with GA-optimized margin plans under different error scenarios.
Main Results:
- Optimized margins maintained dose coverage (Dmax, Dmean) compared to original plans (p > 0.072).
- For 0.5°/0.5 mm errors, PCI and GI decreased, while healthy brain V12 increased significantly.
- For 0.2°/0.2 mm errors, PCI and GI worsened, but healthy brain V12 improved.
Conclusions:
- GA facilitates automatic, individualized margin determination, avoiding user dependency.
- This computational approach accounts for SRS uncertainties, enabling 'smart' margin reduction to protect healthy brain tissue.
- Clinically acceptable target volume coverage is maintained in most cases with optimized margins.
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