Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012 May 7;57(9):2539-54.
doi: 10.1088/0031-9155/57/9/2539. Epub 2012 Apr 11.

Evaluation of deformable image registration and a motion model in CT images with limited features

Affiliations

Evaluation of deformable image registration and a motion model in CT images with limited features

F Liu et al. Phys Med Biol. .

Abstract

Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

PubMed Disclaimer

Figures

Figure 1
Figure 1
NCAT phantom. Red-blue overlay of coronal images at end expiration and end inspiration motion states a) before and b) after deformable image registration. Arrows show motion-induced differences in the lung and in the chest wall before DIR.
Figure 2
Figure 2
(a) Physical deformable abdominal phantom. (b) Overlay of coronal view CT images of phantom in an uncompressed (blue enhanced) and compressed (red enhanced, piston position 30 cm) state. Arrows indicate the markers in the two images. (c) Overlay of uncompressed and compressed phantom images after deformable image registration (compressed state deformed to match uncompressed). Red line segments indicate the magnitude and direction of displacement at the point of the green dots.
Figure 3
Figure 3
Discrepancy between NCAT-phantom (ground truth) and DIR-predicted displacements, in AP (middle row) and SI (bottom row) directions. Positive discrepancy denotes that NCAT displacement is larger. Top row: corresponding axial CT slices. Spherical tumor is visible in the right lung. Symbols “L” and “S” denote liver and spleen.
Figure 4
Figure 4
Discrepancy (DIR predicted–actual displacement) vs actual displacements of implanted radiopaque markers in physical deformable phantom, in the (a) anterior–posterior, and (b) superior–inferior directions. In (a), positive displacement is in anterior direction; in (b), negative displacement is in inferior direction.
Figure 5
Figure 5
Example of a bile duct used as a landmark in patient #1. a) EE–EI overlay of a coronal section before registration and the surrounding VOI indicated with a rectangle; left arrow indicates a discontinuity in displacement between ribs and liver; b) EE–EI overlay after rigid registration; c) EE–EI overlay after deformable registration. The liver is aligned well but the ribs are not (left arrow), which is due to the discontinuity in displacement not fully accounted for by the DIR.
Figure 6
Figure 6
EE-EI landmark displacement (light gray bars) in liver in 7 patients, in (a) AP and (b) SI directions, using rigid registration in a small VOI around the landmarks as ground truth. Dark gray bars show discrepancy between DIR-predicted and rigid registration displacements; medium gray bars show discrepancy between model-predicted and rigid registration displacements.
Figure 7
Figure 7
Discrepancy in EE-EI displacements between motion model and NCAT ground truth in AP (upper row) and SI (lower row) directions.
Figure 8
Figure 8
Discrepancy (Motion Model predicted–actual displacement) vs actual displacements of implanted radiopaque markers in physical deformable phantom, in the (a) anterior–posterior, and (b) superior–inferior directions.
Figure 9
Figure 9
EE-EI displacement (light gray bars), discrepancy between the DIR-predicted and actual observed displacements (medium gray) and discrepancy between model-predicted and actual displacements (dark gray) of 5 markers (a through e, each subplot stands for one marker) vs. piston position (10, 20, 30, 35 and 15 mm) in the physical deformable phantom.
Figure 10
Figure 10
Landmark motion trajectories in the SI(z)–AP(y) plane in patients 1, 3 and 6, measured over 10 RCCT images. 0% phase (as measured by the external respiratory motion monitor) corresponds to end inspiration. Displacements are relative to 50% phase image. Red indicates the rigid registration results, blue indicates DIR results and green indicates model prediction results.

References

    1. Keall P. 4-dimensional computed tomography imaging and treatment planning. Semin Radiat Oncol. 2004;14:81–90. - PubMed
    1. Dieterich S, Cleary K, D’Souza W, Murphy MJ, Wong KH, Keall P. Locating and targeting moving tumors with radiation beams. Med Phys. 2008;35 (12):5684– 5694. - PubMed
    1. Yan D, Jaffray DA, Wong JW. A model to accumulate fractionated dose in a deforming organ. Int J Radiat Oncol Biol Phys. 1999;44:665–675. - PubMed
    1. Wu C, Jeraj R, Olivera GH, Mackie TR. Re-optimization in adaptive radiotherapy. Phys Med Biol. 2002;47:3181–3195. - PubMed
    1. Birkner M, Yan D, Alber M, et al. Adapting inverse planning to patient and organ geometrical variation: algorithm and implementation. Med Phys. 2003;30:2822–2831. - PubMed

Publication types