Exploring breathing pattern irregularity with projection-based method

Accurate descriptions of organ motion due to breathing are highly desirable for radiation treatment planning. This paper proposes an index that quantifies the irregularity of a signal related to respiratory motion. The method works by finding the periodic band-limited signal that best fits the signal samples, and then computing the root mean squared (RMS) residual error. The fitted signal itself may be useful for treatment planning. Using clinical data describing amplitude-time relationships (RPM, Varian) from twelve patients, we correlated the proposed index against relevant metrics from various treatment planning schemes. Simulation results demonstrate a reasonable match with all treatment methods considered, suggesting that the proposed irregularity index is suitable for a variety of treatment methods. Compared to the modified cosine function, which was investigated previously for breathing pattern models, the proposed approach is more representative, flexible, and computationally efficient.