C-arm orbits for metal artifact avoidance (MAA) in cone-beam CT

Abstract

Metal artifacts present a challenge to cone-beam CT (CBCT) image-guided surgery, obscuring visualization of metal instruments and adjacent anatomy—often in the very region of interest pertinent to the imaging/surgical tasks. We present a method to reduce the influence of metal artifacts by prospectively defining an image acquisition protocol—viz., the C-arm source-detector orbit—that mitigates metal-induced biases in the projection data. The metal artifact avoidance (MAA) method is compatible with simple mobile C-arms, does not require exact prior information on the patient or metal implants, and is consistent with 3D filtered backprojection (FBP), more advanced (e.g. polyenergetic) model-based image reconstruction (MBIR), and metal artifact reduction (MAR) post-processing methods. The MAA method consists of: (i) coarse localization of metal objects in the field-of-view (FOV) via two or more low-dose scout projection views and segmentation (e.g. a simple U-Net) in coarse backprojection; (ii) model-based prediction of metal-induced x-ray spectral shift for all source-detector vertices accessible by the imaging system (e.g. gantry rotation and tilt angles); and (iii) identification of a circular or non-circular orbit that reduces the variation in spectral shift. The method was developed, tested, and evaluated in a series of studies presenting increasing levels of complexity and realism, including digital simulations, phantom experiment, and cadaver experiment in the context of image-guided spine surgery (pedicle screw implants). The MAA method accurately predicted tilted circular and non-circular orbits that reduced the magnitude of metal artifacts in CBCT reconstructions. Realistic distributions of metal instrumentation were successfully localized (0.71 median Dice coefficient) from 2–6 low-dose scout views even in complex anatomical scenes. The MAA-predicted tilted circular orbits reduced root-mean-square error (RMSE) in 3D image reconstructions by 46%–70% and ‘blooming’ artifacts (apparent width of the screw shaft) by 20–45%. Non-circular orbits defined by MAA achieved a further ∼46% reduction in RMSE compared to the best (tilted) circular orbit. The MAA method presents a practical means to predict C-arm orbits that minimize spectral bias from metal instrumentation. Resulting orbits—either simple tilted circular orbits or more complex non-circular orbits that can be executed with a motorized multi-axis C-arm—exhibited substantial reduction of metal artifacts in raw CBCT reconstructions by virtue of higher fidelity projection data, which are in turn compatible with subsequent MAR post-processing and/or polyenergetic MBIR to further reduce artifacts.

Accuracy Assessment of Percutaneous Pedicle Screw Placement Using Cone Beam Computed Tomography with Metal Artifact Reduction

“…Elliptic scanning elicited fewer metal artifacts compared to isocentric scanning. Wu et al [15] compared MAR with different C-arm trajectories in reducing blooming artifacts on CBCT reconstructions and demonstrated that non-circular orbits reduced metal artifacts by 46% compared to circular orbits. Thies et al [16] introduced a MAR technique that uses non-circular C-arm orbits with intraoperative adjustments of X-ray source trajectory to optimize the image reconstruction quality.…”

“…This method can also be extended by known-component image reconstruction [13,14]. Another technique uses optimized C-arm orbits in order to avoid collinearity between the X-ray source and screws [15,16]. Figures 1 and 2 demonstrate ARSN images for the baseline technology without MAR (NoMAR) in comparison to images using MAR, which is based on the interpolation of projection data neighboring the metal shadow around the pedicle screw [10].…”

Theory, method, and test tools for determination of 3D MTF characteristics in cone‐beam CT

“…1, denotes the 2D projection image domain and the 3D image reconstruction. While the diagram depicts a single x‐ray source and FPD in a circular orbit about the axis with fixed source‐axis‐distance (SAD) and source‐detector distance (SDD), the methods described herein are pertinent to MTF measurement for CBCT systems with alternative geometries (e.g., multi‐source arrangements 39 and noncircular orbits 40,41 ). A point is alternatively described by spherical coordinates: , the distance from the center of reconstruction (); , the rotation angle about the axis; and , the tilt angle above or below the central axial plane.…”

Simulation-Driven Training of Vision Transformers Enabling Metal Segmentation in X-Ray Images

“…To reduce the impact of metal artifacts, many algorithms have been developed, such as metal artifact avoidance (MAA) and metal artifact reduction (MAR) method. MAA tends to optimize scan geometry based on limited projections to minimizes metal-induced biases in the projection data [2]. MAR focuses on the removal of artifacts [3].…”

“…MAR focuses on the removal of artifacts [3]. Both methods rely on accurate segmentation of metals [2][3][4][5][6][7][8][9][10][11] which is performed either directly on projections or on reconstructed volume. Most of the commercially available MAR algorithms are based on the volume based metal segmentation [3].…”