An algorithm for metal streaking artifact reduction in cone beam CT

M. Bazalova

1,2

, G. Landry

1

, L. Beaulieu

3

, F. Verhaegen

1,4

1-McGill University, Montreal, Canada, 2-Stanford University, Stanford, CA, Centre Hospitalier Univ de Quebec, Quebec, QC, Canada, 4-Maastro, Maastricht, The Netherlands

Introduction

A number of patients undergoing HDR brachytherapy in our institution are imaged with cone beam computed tomography (CBCT). CBCT helps identify patient anatomy and the position of the catheter or vaginal cylinder in which the radiation source is inserted and the tumor treated.

Image quality in CBCT can suffer from severe artifacts if metals, such as vaginal cylinders or hip prostheses, are present in the patient body. Metal artifacts in CT have been studied extensively, however, research in CBCT imaging is sparse. This abstract presents a correction algorithm for CBCT metal artifacts based on sinogram interpolation methods used in CT.

Materials and Methods

CBCT images of a 15 cm diameter water phantom with three 2 cm diameter steel cylinders and two teflon inserts and a 30 cm diameter solid water phantom with tissue equivalent inserts and with or without two large steel cylinders mimicking hip prostheses were scanned on a CBCT scanner (Simulix, Nucletron). CBCT images of a GYN patient with metallic vaginal cylinder were also used in this study. The correction technique was designed to reduce metal artifacts caused by the steel cylinders and by the central rod of the vaginal cylinder. It can be easily modified for broader applications.

a) b) c) In the next step, the interpolated projections were reconstructed using an x-ray imaging simulation program (ImaSim) developed at our institute. The distances source-to-isocenter, detector-to-isocenter, and the data overlap for the half fan geometry were taken into account. CBCT images were filtered and backprojected with the Feldkamp algorithm. To reduce calculation speed and noise, projection data were downsampled by a factor of two before the backprojection. The reconstruction of a single 886 ×886 pixel slice takes approximately 35 minutes on a 3 GHz processor. The deleted metals were superimposed on the reconstructed images based on the interpolated projections which produced the final artifact corrected image with the metals.

Results

The small water phantom CBCT images suffered from severe artifacts, as demonstrated with 3D volume rendering in fig 2a and with an axial slice in fig 2b. Our reconstruction algorithm produced images with less, however still significant, streaking artifacts that closely resemble CT metal artifacts (fig 2c). The correction algorithm introduced in this paper significantly diminished the metal streaking artifacts (fig 2d). The teflon cylinders can be identified more easily than in the original CBCT images.

f) g) a) b) The patient study was the most challenging test for our correction method.

The identification of metal traces based on identification of metal traces in the artifact corrupted images worked very well, as demonstrated in fig 4a and 4b. Fig 4c represents the interpolated projection and the vaginal cylinder rod is made invisible.

a) b) c)

Figure 4: Original patient projection (a), masked projection (b) and interpolated projection (c).

Due to the vaginal cylinder geometry, the interpolation is hardly noticeable. Fig. 5a and 5b show an original and artifact corrected slice, respectively. The reduction of streaking artifacts in the vicinity of the cylinder is evident. The coronal slices at the position of the vaginal cylinder (fig 5c and 5d ) also demonstrate the effectiveness of the artifact correction algorithm. Note that the streaks caused by the metal rings are not corrected for since this was not the aim of our method. Only the projections corresponding to the central rod were interpolated. To correct for the rings, a different threshold for identification of metal voxels in the a) b) image domain has to be chosen.

a) b)

c) d) Figure 1: Small water phantom: original CBCT projection (a), projection with deleted metal traces (b), interpolated projection (c).

The Nucletron CBCT scanner operates with a 120 kV x-ray tube rotating at a distance of 100 cm from the isocenter and the x-rays are detected by an amorphous silicon flat panel with 1024 ×1024 pixels of 0.4×0.4 mm2.

The detector-to-isocenter distance is 52 cm.

CBCT images are reconstructed from approximately 500 views. The scanner can operate in half fan or full fan modes requiring two different reconstruction techniques.

The artifact correction algorithm is described here. First, the metal traces in the projection data were identified. In the case of the small water phantom, the metal traces could be segmented directly in the projection space due to the simple geometry (fig 1a-b). However, a more sophisticated approach had to be taken in the large phantom and the patient studies. Metals were first segmented in the original reconstructed images using a fixed threshold, which worked well in the studied cases.

Metal traces of these voxels in the projection space were found by projection of the voxels from the source onto the flat panel and the corresponding detector signal was deleted. This was done for each x-ray tube position. Consequently, the deleted data were filled in using interpolation of the neighboring data in the direction perpendicular to the scanner rotation axis (fig 1c). This direction of interpolation is the optimal direction for correction of artifacts caused by long objects parallel to the SI direction, such as vaginal cylinders, tungsten shielding or hip prostheses.

Figure 2: 3D volume rendering of the small phantom based on CBCT scanner reconstructed images (a). An axial slice reconstructed by the CBCT scanner (b), using our reconstruction algorithm (b) and the original projections and CBCT image reconstructed using the modified interpolated projections (d).

The CBCT images of the large phantom are presented in fig 3. Fig 3a shows streaking artifacts around the steel cylinders, however, the artifacts between the steel cylinders are less pronounced than in the small phantom. Nevertheless, the corrected image in fig. 3b reduces the artifacts in the vicinity of the steel cylinders and the image quality is similar to the CBCT image taken without the steel inserts.

a) b) c) Figure 3: Original CBCT image (a), artifact corrected CBCT image (b) of the large phantom with steel cylinders and CBCT image of the large phantom without steel. All images reconstructed by our algorithm with no scatter correction.

c)

c) d)

d)

Figure 5: Axial original (a) and corrected (b) slice. Coronal original (c) and corrected (c) slice. The arrows indicate artifact suppression.

Conclusions

The artifact correction algorithm introduced in this study significantly improves image quality and enables to define phantom geometry and patient anatomy in the regions obscured by the artifacts. The ultimate test of the method will be correction of artifacts for a patient with bilateral hip prostheses. This study has the potential to be translated into the clinic.

The interpolated projections can be uploaded to the CBCT reconstruction PC and corrected CBCT images can be reconstructed directly on the scanner computer. Further investigation into the resulting image quality is warranted.