Advanced Iterative Metal Artifact Reduction With Intrinsic Spectral Information From Photon-counting Detector Computed Tomography: Improving the Assessment of Metal-bone Interface

Background: Metallic implants can cause relevant artifacts in computed tomography (CT) imaging, affecting the quality and diagnostic utility of scans. Previous advancements in metal artifact reduction techniques have shown promise but still exhibit limitations in artifact reduction, particularly close to metal implants. Purpose: To evaluate a novel, advanced iterative metal artifact reduction (iMAR) algorithm for photon-counting detector CT in an experimental study focused on visualizing the vicinity of a fixation nail implant. Methods: Three bovine femur bones with titanium-based trochanteric fixation nail implants were scanned on a clinical photon-counting detector CT scanner. Images were reconstructed (1) without iMAR, (2) with the current iMAR algorithm, and (3) with a new prototype iMAR algorithm. The new iMAR prototype algorithm advances state-of-the-art iMAR for photon-counting detector CT by utilizing intrinsically available spectral information. Attenuation and artifact severity (SD of attenuation) were quantified by placing regions-of-interest on each reconstruction across 3 different axial slices: One in the bone marrow immediately adjacent to the metal implant and one in the water adjacent to the femur with the implant. Qualitative image quality, newly introduced artifacts, and diagnostic confidence were rated by 3 radiologists using 5-point Likert scales. Differences between reconstructions were tested using the Friedman test with Wilcoxon post hoc tests; interreader agreement was assessed using Krippendorff alpha. Conclusion: Experimental evidence from a bovine femur implant model suggests that a new, advanced iterative metal artifact reduction algorithm leveraging intrinsic spectral information from photon-counting detector CT effectively reduces metal artifacts and further improves the visualization of the metal-bone interface. Thus, this technique has the potential to enhance the assessment of implant-related complications such as aseptic loosening.

Authors

Publication Details

Journal
Universität Zürich, ZORA
Published
2026-02-25
DOI
https://doi.org/10.5167/uzh-292716
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Advanced Iterative Metal Artifact Reduction With Intrinsic Spectral Information From Photon-counting Detector Computed Tomography: Improving the Assessment of Metal-bone Interface

Matthias Eberhard, Sandro-Michael Heining, Thilo Schikorra, Andreas Specovius et al.
Universität Zürich, ZORA
Advanced X-ray and CT Imaging
article

Advanced Iterative Metal Artifact Reduction With Intrinsic Spectral Information From Photon-counting Detector Computed Tomography: Improving the Assessment of Metal-bone Interface

Matthias Eberhard, Sandro-Michael Heining, Thilo Schikorra, Andreas Specovius, Tristan T Demmert, Victor Mergen, Hatem Alkadhi, Konstantin Klambauer, Lukas J Moser, Thomas Flohr, Bernhard Schmidt
article en

Abstract

Background: Metallic implants can cause relevant artifacts in computed tomography (CT) imaging, affecting the quality and diagnostic utility of scans. Previous advancements in metal artifact reduction techniques have shown promise but still exhibit limitations in artifact reduction, particularly close to metal implants. Purpose: To evaluate a novel, advanced iterative metal artifact reduction (iMAR) algorithm for photon-counting detector CT in an experimental study focused on visualizing the vicinity of a fixation nail implant. Methods: Three bovine femur bones with titanium-based trochanteric fixation nail implants were scanned on a clinical photon-counting detector CT scanner. Images were reconstructed (1) without iMAR, (2) with the current iMAR algorithm, and (3) with a new prototype iMAR algorithm. The new iMAR prototype algorithm advances state-of-the-art iMAR for photon-counting detector CT by utilizing intrinsically available spectral information. Attenuation and artifact severity (SD of attenuation) were quantified by placing regions-of-interest on each reconstruction across 3 different axial slices: One in the bone marrow immediately adjacent to the metal implant and one in the water adjacent to the femur with the implant. Qualitative image quality, newly introduced artifacts, and diagnostic confidence were rated by 3 radiologists using 5-point Likert scales. Differences between reconstructions were tested using the Friedman test with Wilcoxon post hoc tests; interreader agreement was assessed using Krippendorff alpha. Conclusion: Experimental evidence from a bovine femur implant model suggests that a new, advanced iterative metal artifact reduction algorithm leveraging intrinsic spectral information from photon-counting detector CT effectively reduces metal artifacts and further improves the visualization of the metal-bone interface. Thus, this technique has the potential to enhance the assessment of implant-related complications such as aseptic loosening.

Universität Zürich, ZORA
Openalex Percentile: Top 37%
Advanced X-ray and CT Imaging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.