A dosimetric comparison of stereotactic body radiation therapy techniques for lung cancer: robotic versus conventional linac-based systems.

Abstract:

:The aim of this study is to compare the dosimetric characteristics of robotic and conventional linac-based SBRT techniques for lung cancer, and to provide planning guidance for each modality. Eight patients who received linac-based SBRT were retrospectively included in this study. A dose of 60 Gy given in three fractions was prescribed to each target. The Synchrony Respiratory Tracking System and a 4D dose calculation methodology were used for CyberKnife and linac-based SBRT, respectively, to minimize respiratory impact on dose calculation. Identical image and contour sets were used for both modalities. While both modalities can provide satisfactory target dose coverage, the dose to GTV was more heterogeneous for CyberKnife than for linac planning/delivery in all cases. The dose to 1000 cc lung was well below institutional constraints for both modalities. In the high dose region, the lung dose depended on tumor size, and was similar between both modalities. In the low dose region, however, the quality of CyberKnife plans was dependent on tumor location. With anteriorly-located tumors, the CyberKnife may deliver less dose to normal lung than linac techniques. Conversely, for posteriorly-located tumors, CyberKnife delivery may result in higher doses to normal lung. In all cases studied, more monitor units were required for CyberKnife delivery for given prescription. Both conventional linacs and CyberKnife provide acceptable target dose coverage while sparing normal tissues. The results of this study provide a general guideline for patient and treatment modality selection based on dosimetric, tumor and normal tissue sparing considerations.

journal_name

J Appl Clin Med Phys

authors

Ding C,Chang CH,Haslam J,Timmerman R,Solberg T

doi

10.1120/jacmp.v11i3.3223

subject

Has Abstract

pub_date

2010-06-29 00:00:00

pages

3223

issue

3

issn

1526-9914

journal_volume

11

pub_type

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