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BACKGROUND: To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR). METHODS: Conventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used. RESULTS: Significantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010). CONCLUSIONS: DL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients. RELEVANCE STATEMENT: DL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application. KEY POINTS: ⢠Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. ⢠A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. ⢠DL-MAR showed best image quality and diagnostic confidence. ⢠Highest contrast-to-noise ratios were observed on the DL-MAR images.
Subject(s)
Arthroplasty, Replacement, Hip , Deep Learning , Humans , Tomography, X-Ray Computed/methods , Artifacts , AlgorithmsABSTRACT
BACKGROUND: Double inversion recovery (DIR) MRI has the potential to accentuate the synovium without using contrast agents, as it allows simultaneous signal suppression of fluid and fat. The purpose of this study was (1) to compare DIR MRI to conventional contrast-enhanced (CE) MRI for delineation of the synovium in the knee in children with juvenile idiopathic arthritis (JIA) and (2) to assess the agreement between DIR MRI and CE-MRI regarding maximal synovial thickness measurements. RESULTS: In this prospective study, 26 children with JIA who consecutively underwent 3.0-T knee MRI between January 2018 and January 2021 were included (presence of knee arthritis: 13 [50%]; median age: 14 years [interquartile range [IQR]: 11-17]; 14 girls). Median confidence to depict the synovium (0-100 mm visual analogue scale; scored by 2 readers [consensus based]) was 88 (IQR: 79-97) for DIR MRI versus 100 (IQR: 100-100) for CE-MRI (p value = < .001). Maximal synovial thickness per child (millimeters; scored by 4 individual readers) on DIR MRI was greater (p value = < .001) in the children with knee arthritis (2.4 mm [IQR: 2.1-3.1]) than in those without knee arthritis (1.4 mm [IQR: 1.0-1.6]). Good inter-technique agreement for maximal synovial thickness per child was observed (rs = 0.93 [p value = < .001]; inter-reader reliability: ICC DIR MRI = 0.87 [p value = < .001], ICC CE-MRI = 0.90 [p value = < .001]). CONCLUSION: DIR MRI adequately delineated the synovium in the knee of children with JIA and enabled synovial thickness measurement similar to that of CE-MRI. Our results demonstrate that DIR MRI should be considered as a child-friendly alternative to CE-MRI for evaluation of synovitis in children with (suspected) JIA.
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OBJECTIVES: To develop and validate a protocol for MRI assessment of the distal radial and ulnar periphyseal area in gymnasts and non-gymnasts. METHODS: Twenty-four gymnasts with wrist pain, 18 asymptomatic gymnasts and 24 non-gymnastic controls (33 girls) underwent MRI of the wrist on a 3T scanner. Sequences included coronal proton density-weighted images with and without fat saturation, and three-dimensional water-selective cartilage scan and T2 Dixon series. Skeletal age was determined using hand radiographs. Three experienced musculoskeletal radiologists established a checklist of possible (peri)physeal abnormalities based on literature and clinical experience. Five other musculoskeletal radiologists and residents evaluated 30 MRI scans (10 from each group) using this checklist and reliability was determined using the intraclass correlation coefficient (ICC) and Fleiss' kappa. A final evaluation protocol was established containing only items with fair to excellent reliability. RESULTS: Twenty-seven items were assessed for reliability. Intra-rater and inter-rater agreement was good to excellent (respective ICCs 0.60-0.91 and 0.60-0.78) for four epiphyseal bone marrow oedema-related items, physeal signal intensity, metaphyseal junction and depth of metaphyseal intrusions. For physeal thickness, thickness compared with proximal physis of first metacarpal, metaphyseal intrusions, physeal connection of intrusions and metaphyseal bone marrow signal intensity, intra-rater agreement was fair to excellent (ICC/kappa 0.55-0.85) and inter-rater agreement was fair (ICC/kappa 0.41-0.59). Twelve items were included in the final protocol. CONCLUSION: The Amsterdam MRI assessment of the Physis protocol facilitates patient-friendly and reliable assessment of the (peri)physeal area in the radius and ulna.
