Objective assessment of deformable image registration in radiotherapy: a multi-institution study.
The looming potential of deformable alignment tools to play an integral role in adaptive radiotherapy suggests a need for objective assessment of these complex algorithms. Previous studies in this area are based on the ability of alignment to reproduce analytically generated deformations applied to sample image data, or use of contours or bifurcations as ground truth for evaluation of alignment accuracy. In this study, a deformable phantom was embedded with 48 small plastic markers, placed in regions varying from high contrast to roughly uniform regional intensity, and small to large regional discontinuities in movement. CT volumes of this phantom were acquired at different deformation states. After manual localization of marker coordinates, images were edited to remove the markers. The resulting image volumes were sent to five collaborating institutions, each of which has developed previously published deformable alignment tools routinely in use. Alignments were done, and applied to the list of reference coordinates at the inhale state. The transformed coordinates were compared to the actual marker locations at exhale. A total of eight alignment techniques were tested from the six institutions. All algorithms performed generally well, as compared to previous publications. Average errors in predicted location ranged from 1.5 to 3.9 mm, depending on technique. No algorithm was uniformly accurate across all regions of the phantom, with maximum errors ranging from 5.1 to 15.4 mm. Larger errors were seen in regions near significant shape changes, as well as areas with uniform contrast but large local motion discontinuity. Although reasonable accuracy was achieved overall, the variation of error in different regions suggests caution in globally accepting the results from deformable alignment.
Kashani
Rojano
R
Department of Radiation Oncology, University of Michigan, Ann Arbor Michigan 48109-0010, USA. rkashani@umich.edu
Hub
Martina
M
Balter
James M
JM
Kessler
Marc L
ML
Dong
Lei
L
Zhang
Lifei
L
Xing
Lei
L
Xie
Yaoqin
Y
Hawkes
David
D
Schnabel
Julia A
JA
McClelland
Jamie
J
Joshi
Sarang
S
Chen
Quan
Q
Lu
Weiguo
W
D000465:Algorithms; D001331:Automation; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D011878:Radiotherapy / Q000379:methods*; D011879:Radiotherapy Dosage; D015203:Reproducibility of Results; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*