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Proceedings Paper

Deformation estimation and analysis for adaptive radiation therapy
Author(s): Bin Wang; Jianhua Xuan; Jackie Qingrong Wu; Su Zhang; Yue Wang
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Paper Abstract

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, but 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 field 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 few 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.

Paper Details

Date Published: 17 March 2008
PDF: 9 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 691436 (17 March 2008); doi: 10.1117/12.773548
Show Author Affiliations
Bin Wang, Virginia Polytechnic Institute and State Univ. (United States)
Jianhua Xuan, Virginia Polytechnic Institute and State Univ. (United States)
Jackie Qingrong Wu, Duke Univ. (United States)
Su Zhang, Shanghai Jiao Tong Univ. (China)
Yue Wang, Virginia Polytechnic Institute and State Univ. (United States)


Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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