Geometrical tracking accuracy and appropriate PTV margins for robotic radiosurgery of liver lesions by SBRT

Abstract

Purpose: To assess the geometrical accuracy and estimate adequate PTV margins for liver treatments using the Synchrony respiratory tracking system.

Material and methods: Treatment log files are analyzed for 72 liver patients to assess tracking accuracy. The tracking error is calculated as the quadratic sum of the correlation, the predictor and the beam positioning errors. Treatment target rotations and rigid body errors reported by the system are also evaluated. The impact of uncorrected rotations is assessed by rotating the planned dose distribution and reassessing target coverage. Total PTV margins are estimated by summing in quadrature tracking errors and rigid body errors. Relationships are explored between tracking errors, model linearity and motion amplitudes of internal and external markers.

Results: Margins of 3, 2, 2 mm in SUP-INF, LT-RT and ANT-POST directions, respectively, are sufficient to account for tracking and beam positioning errors for 95% of patients. If rigid body error is also considered, margins increase to 4 mm isotropic. Rotations could not be corrected for 92% of patients due to imperfect fiducial implantation and limitations in the magnitude of corrections that the system can apply. Uncorrected rotations would lead to average estimated dose reductions of 2.7% ± 5.8% of the prescribed dose for D99 of GTVs (5 mm PTV expansion) in which the target was well covered in the original plan (28 of 31 GTVs). 80% of tracking models exhibit near linear correlation between internal and external marker motions with small tracking errors (<2.2 mm).

Conclusions: Isotropic PTV margins considering tracking errors and target rigid body errors could be used for liver SBRT treatments if rotational corrections can be calculated accurately so that systematic rotational offsets can be avoided. The linearity of the internal and external breathing motions might be useful for other types of treatment modalities for liver cancer.

Acknowledgments

The authors kindly thank Lisa Goggin and Fabienne Hirigoyenberry from Accuray Inc. for helpful discussions. Dr. Graham Cook and the clinical CyberKnife team at the Ottawa Hospital Cancer Centre are also acknowledged for support and technical help in this project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Ontario Consortium for Adaptive Interventions Radiation Oncology [number ORF-RE File #: RE-04-026]; and by a research grant from Accuray Inc., CA.