Four-dimensional image-based treatment planning: Target volume segmentation and dose calculation in the presence of respiratory motion

Abstract

Purpose: To describe approaches to four-dimensional (4D) treatment planning, including acquisition of 4D-CT scans, target delineation of spatio-temporal image data sets, 4D dose calculations, and their analysis.

Methods and materials: The study included patients with thoracic and hepatocellular tumors. Specialized tools were developed to facilitate visualization, segmentation, and analysis of 4D-CT data: maximum intensity volume to define the extent of lung tumor motion, a 4D browser to examine and dynamically assess the 4D data sets, dose calculations, including respiratory motion, and deformable registration to combine the dose distributions at different points.

Results: Four-dimensional CT was used to visualize and quantitatively assess respiratory target motion. The gross target volume contours derived from light breathing scans showed significant differences compared with those extracted from 4D-CT. Evaluation of deformable registration using difference images of original and deformed anatomic maps suggested the algorithm is functionally useful. Thus, calculation of effective dose distributions, including respiratory motion, was implemented.

Conclusion: Tools and methods to use 4D-CT data for treatment planning in the presence of respiratory motion have been developed and applied to several case studies. The process of 4D-CT-based treatment planning has been implemented, and technical barriers for its routine use have been identified.