Marker-free motion correction in weight-bearing cone-beam CT of the knee joint

Abstract

Purpose: To allow for a purely image-based motion estimation and compensation in weight-bearing cone-beam computed tomography of the knee joint.

Methods: Weight-bearing imaging of the knee joint in a standing position poses additional requirements for the image reconstruction algorithm. In contrast to supine scans, patient motion needs to be estimated and compensated. The authors propose a method that is based on 2D/3D registration of left and right femur and tibia segmented from a prior, motion-free reconstruction acquired in supine position. Each segmented bone is first roughly aligned to the motion-corrupted reconstruction of a scan in standing or squatting position. Subsequently, a rigid 2D/3D registration is performed for each bone to each of K projection images, estimating 6 × 4 × K motion parameters. The motion of individual bones is combined into global motion fields using thin-plate-spline extrapolation. These can be incorporated into a motion-compensated reconstruction in the backprojection step. The authors performed visual and quantitative comparisons between a state-of-the-art marker-based (MB) method and two variants of the proposed method using gradient correlation (GC) and normalized gradient information (NGI) as similarity measure for the 2D/3D registration.

Results: The authors evaluated their method on four acquisitions under different squatting positions of the same patient. All methods showed substantial improvement in image quality compared to the uncorrected reconstructions. Compared to NGI and MB, the GC method showed increased streaking artifacts due to misregistrations in lateral projection images. NGI and MB showed comparable image quality at the bone regions. Because the markers are attached to the skin, the MB method performed better at the surface of the legs where the authors observed slight streaking of the NGI and GC methods. For a quantitative evaluation, the authors computed the universal quality index (UQI) for all bone regions with respect to the motion-free reconstruction. The authors quantitative evaluation over regions around the bones yielded a mean UQI of 18.4 for no correction, 53.3 and 56.1 for the proposed method using GC and NGI, respectively, and 53.7 for the MB reference approach. In contrast to the authors registration-based corrections, the MB reference method caused slight nonrigid deformations at bone outlines when compared to a motion-free reference scan.

Conclusions: The authors showed that their method based on the NGI similarity measure yields reconstruction quality close to the MB reference method. In contrast to the MB method, the proposed method does not require any preparation prior to the examination which will improve the clinical workflow and patient comfort. Further, the authors found that the MB method causes small, nonrigid deformations at the bone outline which indicates that markers may not accurately reflect the internal motion close to the knee joint. Therefore, the authors believe that the proposed method is a promising alternative to MB motion management.

FIG. 1.

Overview of the proposed motion compensation approach. The inputs are the femur and tibia volumes and the 2D projection images, both marked by a dashed frame.

FIG. 2.

Adjustment of 3D segmentation masks to reduce the noise level in DRRs. (a) Original masks, (b) adjusted masks for DRR generation.

FIG. 3.

Axial and coronal slices of the motion-free supine data. The green line corresponds to the regions used for the numerical evaluation in Sec. 3.B. The images show a clear reconstruction of the bones without any apparent motion artifacts. (a) Supine—axial, (b) supine—coronal. (See online version.)

FIG. 4.

Axial slices through the femur. From left to right: Reconstructions without motion correction (NoCorr), the proposed method using GC, the proposed method using NGI and the MB reference method. The rows correspond to the three different weight-bearing scans from 0^∘ flexion angle at the top to 60^∘ flexion angle at the bottom (W: 2025 HU, C: 145 HU). (a) NoCorr-0°, (b) GC-0°, (c) NGI-0°, (d) MB-0°, (e) NoCorr-35°, (f) GC-35°, (g) NGI-35°, (h) MB-35°, (i) NoCorr-60°, (j) GC-60°, (k) NGI-60°, and (l) MB-60°.

FIG. 5.

Axial slices through the tibia and fibula. From left to right: Reconstructions without motion correction (NoCorr), the proposed method using GC, the proposed method using NGI and the MB reference method. The rows correspond to the three different weight-bearing scans from 0^∘ flexion angle at the top to 60^∘ flexion angle at the bottom (W: 2025 HU, C: 145 HU). (a) NoCorr-0°, (b) GC-0°, (c) NGI-0°, (d) MB-0°, (e) NoCorr-35°, (f) GC-35°, (g) NGI-35°, (h) MB-35°, (i) NoCorr-60°, (j) GC-60°, (k) NGI-60°, and (l) MB-60°.

FIG. 6.

Difference of gradient magnitudes between DRR and acquired projections after registration. Top row: Projections used for extracting the reference coordinate system. Bottom row: Projections with large occlusions led to incorrect registration of the left tibia using the GC method. (a) GC-60°—Ref. projection, (b) NGI-60°—Ref. projection, (c) GC-60°—First projection, (d) NGI-60°—First projection.

FIG. 7.

Edge profiles along the outline of the right femur for NGI-0^∘, MB-0^∘, and the supine, motion-free reference (SUP). The depth axis points from the bone outward. The starting point and direction of the x-axis is indicated by arrows in (a). Compared to the NGI method the edge shifts upward for the MB method indicating a scaling effect. (a) Line profile measurement in an axial and coronal slice, (b) edge profiles along the right femur’s outline in an axial (top) and coronal (bottom) slice.

FIG. 8.

Relative bone motion during the 60^∘ scan estimated by the NGI approach. The motion parameters show the deviation to the average rigid transform over all four bones.