Deformation estimation and analysis for adaptive radiation therapy

Published

Journal Article

To accommodate the inter- and intra-fractional motion of internal organs in prostate cancer treatment, a large margin (5mm-25mm) has often to be considered during radiation therapy planning. Normally, the inter- fractional motion is more substantial than the intra-fractional counterpart. Therefore, the study of inter-fractional motion pattern is of special interest for adaptive radiation therapy. Existing methods on organ motion analysis mainly focus on the deviation of an organ's shape from its mean shape. The deviation information is helpful in choosing a statistically proper margin, hut is of limited use for plan adaptation. In this paper, we propose a new deformation analysis method that can be directly used for plan adaptation. First, deformation estimation is accomplished by a fast deformable registration method, which utilizes a contour based multi-grid strategy to register treatment: cone-beam CT (CBCT) images with planning CT images. Second, dominant deformation modes are extracted by a novel deformation analysis approach. To be specific, a cooperative principal component analysis (PCA) method is developed to analyze the deformation held in a. coarse-to-fine strategy. The deformation modes are initialized by applying PCA on the organs as a whole and refined by analyzing the individual organs subsequently. The experimental results; show that the organ motion can be well characterized by a lew dominant deformation modes. Based on the dominant modes, a corresponding set of dominant modal plans could be generated for further optimization. Ultimately, an adaptive plan for each treatment can be obtained on-line while the margin can be effectively reduced to minimize the unnecessary radiation dosage.

Full Text

Duke Authors

Cited Authors

  • Wang, B; Xuan, J; Wu, JQ; Zhang, S; Wang, Y

Published Date

  • May 19, 2008

Published In

Volume / Issue

  • 6914 /

International Standard Serial Number (ISSN)

  • 1605-7422

Digital Object Identifier (DOI)

  • 10.1117/12.773548

Citation Source

  • Scopus