A margin model to account for respiration-induced tumour motion and its variability

被引:29
作者
Coolens, Catherine [1 ]
Webb, Steve [1 ]
Shirato, H. [2 ]
Nishioka, K. [2 ]
Evans, Phil M. [1 ]
机构
[1] Inst Canc Res, Joint Dept Phys, Sutton SM2 5PT, Surrey, England
[2] Hokkaido Univ, Grad Sch Med, Dept Radiol, Sapporo, Hokkaido, Japan
关键词
D O I
10.1088/0031-9155/53/16/007
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
In order to reduce the sensitivity of radiotherapy treatments to organ motion, compensation methods are being investigated such as gating of treatment delivery, tracking of tumour position, 4D scanning and planning of the treatment, etc. An outstanding problem that would occur with all these methods is the assumption that breathing motion is reproducible throughout the planning and delivery process of treatment. This is obviously not a realistic assumption and is one that will introduce errors. A dynamic internal margin model (DIM) is presented that is designed to follow the tumour trajectory and account for the variability in respiratory motion. The model statistically describes the variation of the breathing cycle over time, i. e. the uncertainty in motion amplitude and phase reproducibility, in a polar coordinate system from which margins can be derived. This allows accounting for an additional gating window parameter for gated treatment delivery as well as minimizing the area of normal tissue irradiated. The model was illustrated with abdominal motion for a patient with liver cancer and tested with internal 3D lung tumour trajectories. The results confirm that the respiratory phases around exhale are most reproducible and have the smallest variation in motion amplitude and phase (approximately 2 mm). More importantly, the margin area covering normal tissue is significantly reduced by using trajectory- specific margins (as opposed to conventional margins) as the angular component is by far the largest contributor to the margin area. The statistical approach to margin calculation, in addition, offers the possibility for advanced online verification and updating of breathing variation as more data become available.
引用
收藏
页码:4317 / 4330
页数:14
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