Adaptive intensity modulated radiation therapy planning optimization with changing tumor geometry and fraction size limits

Abstract

The modern approach of delivering radiation treatments through intensity modulated radiotherapy (IMRT) requires a computationally complex planning process. Intensities must be chosen for the many small unit grids into which the beams are divided to produce a desired distribution of dose at points throughout the body. To achieve desired aims, attention must be paid to both the cumulative doses and the doses delivered in each separate treatment session. The time horizon for the treatment allows for periodic re-imaging of the tumor geometry and for adapting the treatment plan accordingly. We present a promising iterative optimization approach that re-optimizes and updates the treatment plan periodically by incorporating the latest tumor geometry information. Two realistic lung cases simulating practice, based on anonymized archive datasets, are used to test the effectiveness of our adaptive planning approach. The computed plans both satisfy cumulative and per-session dose constraints while improving the objective (average tumor dose).