A genetic algorithm approach to the inverse problem of treatment planning for intensity-modulated radiotherapy

A genetic algorithm optimization approach for designing treatment plans in intensity-modulated radiotherapy is proposed. The approach determines the beam intensities of the pencil-beam dose model such that the optimized dose distribution closely matches the prescribed dose distribution. The approach indirectly inverts the ill-conditioned dose-projection matrix, which can be very large and extremely sparse. The beam intensities are treated as chromosomes that are encoded as binary strings. The approach was used to design treatment plans for two deceptive clinical test cases. In both case, cancerous tissues in the planning target region received at least 98% of the prescribed dose level while dose levels delivered to the organs at risk were well within safe limits, with a maximum exposure of 2.5 and 52.5% of the prescribed tolerance level for the brain and prostrate cancer cases, respectively. Dose levels delivered to the healthy tissues were small with a mean exposure of 22.8 and 23.5% of the prescribed tolerance level.