First experience with combined use of adaptive statistical iterative reconstruction and gemstone spectral imaging in spinal fusion CT images

Department of Radiology, Peking Union Medical College Hospital, Beijing, China
Department of Radiology, Austin Health, Melbourne, Victoria, Australia
DOI
10.7287/peerj.preprints.1306v1
Subject Areas
Orthopedics, Radiology and Medical Imaging, Computational Science
Keywords
image noise, metal artifacts, dual-energy computed tomography, iterative reconstruction
Copyright
© 2015 Wang et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Wang F, Zhang Y, Jin Z, Zwar R. 2015. First experience with combined use of adaptive statistical iterative reconstruction and gemstone spectral imaging in spinal fusion CT images. PeerJ PrePrints 3:e1306v1

Abstract

Objective. To explore whether the image noises and the metal artifacts could be further managed by the combined use of two technologies, the adaptive statistical iterative reconstruction (ASIR) and the monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. Materials and Methods. Fifty-one patients with 318 spinal pedicle screws were prospectively scanned with dual energy CT by using fast kV-switching GSI between 80 and 140 kVp. The monochromatic GSI images at 110 keV were reconstructed either without ASIR or with ASIR of various levels (30%, 50%, 70% and 100%). For these five sets of images, both objective and subjective image quality assessments were performed to evaluate the image quality. Results. With objective image quality assessment, the metal artifacts (measured by an artifacts index) significantly decreased when increasing levels of ASIR was utilized (p < 0.001). Moreover, adding ASIR to GSI also decreased the image noise (p < 0.001) and improved the signal-to-noise ratio (SNR, p < 0.001). With subjective image quality analysis, the inter-reader agreements were good, with intra-class correlation coefficients (ICC) of 0.89 to 0.99. Meanwhile, the visualization of the peri-implant soft tissue was improved at higher ASIR levels (p < 0.001). Conclusion. Combined use of ASIR and GSI is shown to decrease the image noise and improve the image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels of over 70%.

Author Comment

This is a submission to PeerJ for review.

Supplemental Information

Raw data of subjective and objective image quality assessment

DOI: 10.7287/peerj.preprints.1306v1/supp-1