Abstract

Image-guided therapy (IGT) involves acquisition and processing of biomedical images to actively guide medical interventions. The proliferation of IGT technologies has been particularly significant in image-guided radiotherapy (IGRT), as a way to increase the tumor targeting accuracy. When IGRT is applied to moving tumors, image guidance becomes challenging, as motion leads to increased uncertainty. Different strategies may be applied to mitigate the effects of motion: each technique is related to a different technological effort and complexity in treatment planning and delivery. The objective comparison of different motion mitigation strategies can be achieved by quantifying the residual uncertainties in tumor targeting, to be detected by means of IGRT technologies. Such quantification requires an extension of targeting error theory to a 4D space, where the 3D tumor trajectory as a function of time measured (4D Targeting Error, 4DTE). Accurate 4DTE analysis can be represented by a motion probability density function, describing the statistical fluctuations of tumor trajectory. We illustrate the application of 4DTE analysis through examples, including weekly variations in tumor trajectory as detected by 4DCT, respiratory gating via external surrogates and real-time tumor tracking.

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