Purpose To characterize the radiation dose and three‐dimensional (3D) imaging performance of a recently developed mobile, isocentric C‐arm equipped with a flat‐panel detector (FPD) for intraoperative cone‐beam computed tomography (CBCT) (Cios Spin 3D, Siemens Healthineers) and to identify potential improvements in 3D imaging protocols for pertinent imaging tasks. Methods The C‐arm features a 30 × 30 cm2 FPD and isocentric gantry with computer‐controlled motorization of rotation (0–195°), angulation (±220°), and height (0–45 cm). Geometric calibration was assessed in terms of 9 degrees of freedom of the x‐ray source and detector in CBCT scans, and the reproducibility of geometric calibration was evaluated. Standard and custom scan protocols were evaluated, with variation in the number of projections (100–400) and mAs per view (0.05–1.65 mAs). Image reconstruction was based on 3D filtered backprojection using “smooth,” “normal,” and “sharp” reconstruction filters as well as a custom, two‐dimensional 2D isotropic filter. Imaging performance was evaluated in terms of uniformity, gray value correspondence with Hounsfield units (HU), contrast, noise (noise‐power spectrum, NPS), spatial resolution (modulation transfer function, MTF), and noise‐equivalent quanta (NEQ). Performance tradeoffs among protocols were visualized in anthropomorphic phantoms for various anatomical sites and imaging tasks. Results Geometric calibration showed a high degree of reproducibility despite ~19 mm gantry flex over a nominal semicircular orbit. The dose for a CBCT scan varied from ~0.8–4.7 mGy for head protocols to ~6–38 mGy for body protocols. The MTF was consistent with sub‐mm spatial resolution, with f10 (frequency at which MTF = 10%) equal to 0.64 mm−1, 1.0 mm−1, and 1.5 mm−1 for smooth, standard, and sharp filters respectively. Implementation of a custom 2D isotropic filter improved CNR ~ 50–60% for both head and body protocols and provided more isotropic resolution and noise characteristics. The NPS and NEQ quantified the 3D noise performance and provided a guide to protocol selection, confirmed in images of anthropomorphic phantoms. Alternative scan protocols were identified according to body site and task — for example, lower‐dose body protocols (<3 mGy) sufficient for visualization of bone structures. Conclusion The studies provided objective assessment of the dose and 3D imaging performance of a new C‐arm, offering an important basis for clinical deployment and a benchmark for quality assurance. Modifications to standard 3D imaging protocols were identified that may improve performance or reduce radiation dose for pertinent imaging tasks.
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.
An algorithm for automatic spinal pedicle screw planning is reported and evaluated in simulation and first clinical studies. A statistical atlas of the lumbar spine (N = 40 members) was constructed for active shape model (ASM) registration of target vertebrae to an unsegmented patient CT. The atlas was augmented to include ‘reference’ trajectories through the pedicles as defined by a spinal neurosurgeon. Following ASM registration, the trajectories are transformed to the patient CT and accumulated to define a patient-specific screw trajectory, diameter, and length. The algorithm was evaluated in leave-one-out analysis (N = 40 members) and for the first time in a clinical study (N = 5 patients undergoing cone-beam CT (CBCT) guided spine surgery), and in simulated low-dose CBCT images. ASM registration achieved (2.0 ± 0.5) mm root-mean-square-error (RMSE) in surface registration in 96% of cases, with outliers owing to limitations in CT image quality (high noise/slice thickness). Trajectory centerlines were conformant to the pedicle in 95% of cases. For all non-breaching trajectories, automatically defined screw diameter and length were similarly conformant to the pedicle and vertebral body (98.7%, Grade A/B). The algorithm performed similarly in CBCT clinical studies (93% centerline and screw conformance) and was consistent at the lowest dose levels tested. Average runtime in planning five-level (lumbar) bilateral screws (ten trajectories) was (312.1 ± 104.0) s. The runtime per level for ASM registration was (41.2 ± 39.9) s, and the runtime per trajectory was (4.1 ± 0.8) s, suggesting a runtime of ~(45.3 ± 39.9) s with a more fully parallelized implementation. The algorithm demonstrated accurate, automatic definition of pedicle screw trajectories, diameter, and length in CT images of the spine without segmentation. The studies support translation to clinical studies in free-hand or robot-assisted spine surgery, quality assurance, and data analytics in which fast trajectory definition is a benefit to workflow.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.