Iterative metal artefact reduction in CT: can dedicated algorithms improve image quality after spinal instrumentation?
Introduction
Computed tomography (CT) is the method of choice in the detection of postoperative complications after spinal instrumentation. Streak and band artefacts from metallic devices may limit diagnostic confidence and can potentially mask postoperative complications.
Metal artefact reduction (MAR) in CT can be achieved by different approaches including beam-hardening correction,1 segmentation with interpolation,2 or dual-energy CT.3, 4 Recently, an iterative MAR (iMAR) technique became available and initial studies demonstrated a high potential in patients with hip implants,5 dental implants,6 deep brain-stimulating electrodes,7 and spinal implants.8
IMAR algorithms use multiple iterations and combine different techniques including beam-hardening correction, normalised sinogram inpainting, and frequency split algorithm.9 Different reconstruction parameters can be selected to adjust the algorithm to the implemented metallic devices and improve image quality.
Kotsenas et al.8 demonstrated artefact reduction and improvement of soft-tissue visualisation by using an iMAR prototype with parameters adjusted to spinal hardware; however, only one iMAR algorithm with arbitrarily selected parameters was used and comparison was only made to weighted filtered back projection (WFPB). Therefore, the aim of the present study was to evaluate two novel iMAR algorithms regarding artefact reduction and image-quality improvement in patients after spinal instrumentation.
Section snippets
Patient population
This retrospective study was approved by the local ethics committee. Patients who had received a post-surgical spinal CT examination between March 2015 and July 2016 and in which the raw data of the scan were available at the time of the retrospective study were included.
CT protocol
CT examinations were performed on a 64-row CT system (n=9; Somatom Definition AS with sliding gantry; Siemens Healthcare, Erlangen, Germany) and a 128-row dual-source CT system using the single-source mode (n=15; Somatom
Patients
Twenty-four patients (13 male, 11 female; mean age 60.1±16.6; range 22–88 years) were included in the study. Surgery was performed in all cases. Spinal implants were 21 dorsal stabilisation devices and three ventral stabilisation devices. Additionally, nine patients had intervertebral cages and five patients had vertebral cages. Diagnoses that led to the spinal surgery were spondylolisthesis (n=4), spondylodiscitis (n=5), pathological fractures (n=6), traumatic fractures (n=3), and spinal
Discussion
Both investigated iMAR algorithms reduced artefacts from spinal metallic devices and improved image quality of adjacent bone and soft tissue compared with WFBP (Fig 2). The iMAR algorithm with dedicated parameters for large metallic implants led to a stronger artefact reduction and improved quality compared with the algorithm that was specifically tailored to CT of patients with spinal implants by the vendor (Figure 3, Figure 4).
The mean reconstruction time per volume was 163 seconds. Initial
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