Abstract
Purpose: To clarify the effects of respiratory condition on dose calculation for stereotactic radiotherapy of small lung tumors. Methods and materials: Computed tomography (CT) data were obtained for nine tumors (diameter, 2.1-3.6 cm; mean, 2.7 cm) during the stable state, deep expiration, and deep inspiration breath-hold states. Rotational Irradiation with 3 non-coplanar arcs (Rotational Irradiation) and static irradiation with 18 non-coplanar ports (Static Irradiation) using 6-MV photons were evaluated using Fast Fourier Transform (FFT) convolution and Multigrid (MG) superposition algorithms. Dose-volume histograms (DVHs), mean path-length (PL) and mean effective path-length (EPL) were calculated. Results: Although the PL was larger for the inspiration state than for the stable state and the expiration state, the EPL was 0.4-0.5 cm smaller in the inspiration state than in the expiration state (p = 0.01 for Rotational Irradiation; p = 0.03 for Static Irradiation). The isocenter dose obtained by the FFT convolution algorithm was 7-12% higher than that obtained with the MG superposition algorithm. A leftward shift of the DVH obtained by MG superposition was noted for the inspiration state compared with the expiration state. Conclusions: The choice of the proper algorithm is important to accounting for changes in respiration state. Differences in isocenter dose were not large among the respiratory states analyzed. EPL was a little shorter for inspiration than for expiration, although there were larger and reverse trends in path length. A leftward shift of the DVH obtained for the inspiration state when MG superposition was used.
Original language | English |
---|---|
Pages (from-to) | 204-211 |
Number of pages | 8 |
Journal | Physica Medica |
Volume | 24 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2008 Dec |
Keywords
- Electron density
- Lung tumor
- Path-length
- Stereotactic radiotherapy
ASJC Scopus subject areas
- Biophysics
- Radiology Nuclear Medicine and imaging
- Physics and Astronomy(all)