Large deformation three-dimensional image registration in image-guided radiation therapy.
In this paper, we present and validate a framework, based on deformable image registration, for automatic processing of serial three-dimensional CT images used in image-guided radiation therapy. A major assumption in deformable image registration has been that, if two images are being registered, every point of one image corresponds appropriately to some point in the other. For intra-treatment images of the prostate, however, this assumption is violated by the variable presence of bowel gas. The framework presented here explicitly extends previous deformable image registration algorithms to accommodate such regions in the image for which no correspondence exists. We show how to use our registration technique as a tool for organ segmentation, and present a statistical analysis of this segmentation method, validating it by comparison with multiple human raters. We also show how the deformable registration technique can be used to determine the dosimetric effect of a given plan in the presence of non-rigid tissue motion. In addition to dose accumulation, we describe a method for estimating the biological effects of tissue motion using a linear-quadratic model. This work is described in the context of a prostate treatment protocol, but it is of general applicability.
Foskey
Mark
M
Department of Radiation Oncology, University of North Carolina, USA. mark_foskey@unc.edu
Davis
Brad
B
Goyal
Lav
L
Chang
Sha
S
Chaney
Ed
E
Strehl
Nathalie
N
Tomei
Sandrine
S
Rosenman
Julian
J
Joshi
Sarang
S
D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D008297:Male; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011859:Radiography; D011880:Radiotherapy Planning, Computer-Assisted; D012007:Rectum / Q000000981:diagnostic imaging / Q000528:radiation effects