Dose perturbations by two carbon fiber treatment couches and the ability of a commercial treatment planning system to predict these effects.

PURPOSE

To measure the effect of the treatment couch on dose distributions and to investigate the ability of a modern planning system to accurately model these effects.

METHODS

This work measured the dose perturbation at depth and in the dose buildup region when one of two treatment couches, CIVCO (formerly MED-TEC) or Medical Intelligence, was placed between a photon beam source (6, 10, and 18 MV) and the phantom. Beam attenuation was measured in the center of a cylindrical acrylic phantom with a Farmer type ion chamber at multiple gantry angles. Dose buildup was measured in Solid Water with plane parallel ion chambers (NACP-02 and PTW Markus) with the beam normal to both the phantom and couch surfaces. The effective point of measurement method as described [M. R. McEwen et al. "The effective point of measurement of ionization chambers and the build-up anomaly in MV x-ray beams," Med. Phys. 35(3), 950-958 (2008)] was employed to calculate dose in the buildup region. Both experiments were modeled in XiO. Images of the treatment couches were merged with images of the phantoms such that they were included as part of the "patient" image. Dose distributions calculated with superposition and fast superposition algorithms were compared to measurement.

RESULTS

The two treatment couches have different radiological signatures and dissimilar water equivalent thicknesses (4.2 vs 6.3 mm.) Maximum attenuation was 7%. Both couches caused significant loss of skin sparing, the worst case showing an increase in surface dose from 17% (no couch) to 88% (with couch). The TPS accurately predicted the surface dose (+/-3%) and the attenuation at depth when the phantom was in contact with the couch. For the open beam the TPS was less successful in the buildup region.

CONCLUSIONS

The treatment couch is not radio-transparent. Its presence between the patient and beam source significantly alters dose in the patient. For the most part, a modern treatment planning system can adequately predict the altered dose distribution.