Optimization of Post-processing Reconstruction for Orthopedic Metal Implants on Photon-Counting Detector CT: A Within-Patient Comparison

Objectives To determine how iterative metal artifact reduction (iMAR), virtual monoenergetic imaging (VMI), and reconstruction kernel selection affect metal artifacts and image quality around orthopedic implants on photon-counting detector CT (PCD-CT), and to identify task-specific reconstructions for bone and soft-tissue evaluation. Materials and methods This retrospective within-patient study included 10 patients with 11 orthopedic implant sites. All reconstructions were generated from the same PCD-CT raw data. Three predefined comparisons were performed: iMAR off versus on at 70 keV/Br40/1.0 mm; four bone reconstructions combining T3D or 145-keV VMI with Qr64 or Br64 at 0.4 mm; and four soft-tissue reconstructions combining T3D or 65-keV VMI with Br40 or Qr40 at 1.0 mm. CT attenuation, image noise, artifact index (AI), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), 5-point Likert scores, and interreader agreement were evaluated. Results With matched parameters, iMAR increased median bone scores from 2 to 4 and soft-tissue scores from 1 to 2–3. For bone, 145-keV VMI reduced image noise and AI compared with T3D; 145-keV Br64 had the highest subjective scores, whereas 145-keV Qr64 showed the most favorable quantitative metrics. For soft tissue, T3D had lower noise and AI and higher SNR than 65-keV VMI, and T3D Br40 received the highest subjective scores. Weighted κ ranged from 0.635 to 0.717. Conclusion Post-processing optimization on PCD-CT was task specific. iMAR improved image evaluability, 145-keV VMI favored bone and bone-implant interface assessment, and T3D Br40 favored adjacent soft-tissue evaluation.