Background:Metal artifacts caused by hip arthroplasty stems limit the diagnostic value of computed tomography (CT) in the evaluation of periprosthetic fractures or implant loosening. The aim of this ex vivo study was to evaluate the influence of different scan parameters and metal artifact algorithms on image quality in the presence of hip stems.Methods:Nine femoral stems, 6 uncemented and 3 cemented, that had been implanted in subjects during their lifetimes were exarticulated and investigated after death and anatomical body donation. Twelve CT protocols consisting of single-energy (SE) and single-source consecutive dual-energy (DE) scans with and without an iterative metal artifact reduction algorithm (iMAR; Siemens Healthineers) and/or monoenergetic reconstructions were compared. Streak and blooming artifacts as well as subjective image quality were evaluated for each protocol.Results:Metal artifact reduction with iMAR significantly reduced the streak artifacts in all investigated protocols (p = 0.001 to 0.01). The best subjective image quality was observed for the SE protocol with a tin filter and iMAR. The least streak artifacts were observed for monoenergetic reconstructions of 110, 160, and 190 keV with iMAR (standard deviation of the Hounsfield units: 151.1, 143.7, 144.4) as well as the SE protocol with a tin filter and iMAR (163.5). The smallest virtual growth was seen for the SE with a tin filter and without iMAR (4.40 mm) and the monoenergetic reconstruction of 190 keV without iMAR (4.67 mm).Conclusions:This study strongly suggests that metal artifact reduction algorithms (e.g., iMAR) should be used in clinical practice for imaging of the bone-implant interface of prostheses with either an uncemented or cemented femoral stem. Among the iMAR protocols, the SE protocol with 140 kV and a tin filter produced the best subjective image quality. Furthermore, this protocol and DE monoenergetic reconstructions of 160 and 190 keV with iMAR achieved the lowest levels of streak and blooming artifacts.Level of Evidence:Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Purpose Despite advances of three-dimensional imaging pelvic radiographs remain the cornerstone in the evaluation of the hip joint. However, large inter- and intra-rater variabilities were reported due to subjective landmark setting. Artificial intelligence (AI)–powered software applications could improve the reproducibility of pelvic radiograph evaluation by providing standardized measurements. The aim of this study was to evaluate the reliability and agreement of a newly developed AI algorithm for the evaluation of pelvic radiographs. Methods Three-hundred pelvic radiographs from 280 patients with different degrees of acetabular coverage and osteoarthritis (Tönnis Grade 0 to 3) were evaluated. Reliability and agreement between manual measurements and the outputs of the AI software were assessed for the lateral-center-edge (LCE) angle, neck-shaft angle, sharp angle, acetabular index, as well as the femoral head extrusion index. Results The AI software provided reliable results in 94.3% (283/300). The ICC values ranged between 0.73 for the Acetabular Index to 0.80 for the LCE Angle. Agreement between readers and AI outputs, given by the standard error of measurement (SEM), was good for hips with normal coverage (LCE-SEM: 3.4°) and no osteoarthritis (LCE-SEM: 3.3°) and worse for hips with undercoverage (LCE-SEM: 5.2°) or severe osteoarthritis (LCE-SEM: 5.1°). Conclusion AI-powered applications are a reliable alternative to manual evaluation of pelvic radiographs. While being accurate for patients with normal acetabular coverage and mild signs of osteoarthritis, it needs improvement in the evaluation of patients with hip dysplasia and severe osteoarthritis.
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