An active optical flow model for dose prediction in spinal sbrt plans

Published

Journal Article

© Springer International Publishing Switzerland 2015. Accurate dose predication is critical to spinal stereotactic body radiation therapy (SBRT). It enables radiation oncologists and planners to design treatment plans that maximally protect spinal cord while effectively controlling surrounding tumors. Spinal cord dose distribution is primarily affected by the shapes of tumor boundaries near the organ. In this work, we estimate such boundary effects and predict dose distribution by exploring an active optical flow model (AOFM). To establish AOFM, we collect a sequence of dose sub-images and tumor contours near spinal cords from a database of clinically accepted spine SBRT plans. The data are classified into five groups according to the tumor location in relation to the spinal cords. In each group, we randomly choose a dose sub-image as the reference and register all other dose images to the reference using an optical flowmethod. AOFM is then constructed by importing optical flow vectors and dose values into the principal component analysis. To develop the predictivemodel for a group, we also build active shape model (ASM) of tumor contours near the spinal cords. The correlation between ASM and AOFM is estimated via the multiple regression model. When predicting dose distribution of a new case, the group was first determined based on the case’stumor contour. Then the corresponding model for the group is used to map from the ASM space to the AOFM space. Finally, the parameters in the AOFM space are used to estimate dose distribution. This method was validated on 30 SBRT plans. Analysis of dose-volume histograms revealed that at the important 2%volume mark, the dose difference between prediction and clinical plan is less than 4%. These results suggest that theAOFM-based approach is a promising tool for predicting accurate spinal cord dose in clinical practice.

Full Text

Duke Authors

Cited Authors

  • Liu, J; Jackie Wu, Q; Yin, FF; Kirkpatrick, JP; Cabrera, A; Ge, Y

Published Date

  • January 1, 2015

Published In

Volume / Issue

  • 20 /

Start / End Page

  • 27 - 35

Electronic International Standard Serial Number (EISSN)

  • 2212-9413

International Standard Serial Number (ISSN)

  • 2212-9391

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-14148-0_3

Citation Source

  • Scopus