Advanced Iterative Metal Artifact Reduction With Intrinsic Spectral Information From Photon-counting Detector Computed Tomography

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. Results: Artifact severity in the bone adjacent to the implant significantly decreased from 226 HU (no iMAR) to 174 HU (current iMAR) and to 159 HU with the new iMAR ( P < 0.001). Adjacent to the femur, artifact severity decreased from 63 HU to 48 HU and to 29 HU, respectively ( P < 0.05). Qualitative scores differed significantly between reconstructions ( P < 0.05), with highest ratings for new iMAR across all categories. Current iMAR introduced new artifacts near the implant, which did not occur with new iMAR ( P < 0.05). 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.