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Wang Q, Yao M, Song X, Liu Y, Xing X, Chen Y, Zhao F, Liu K, Cheng X, Jiang S, Lang N. Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning. Acad Radiol 2024; 31:1518-1527. [PMID: 37951778 DOI: 10.1016/j.acra.2023.10.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/11/2023] [Accepted: 10/20/2023] [Indexed: 11/14/2023]
Abstract
OBJECTIVES To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis. MATERIALS AND METHODS This retrospective study included 376 consecutive patients with pathologically confirmed knee synovitis (rheumatoid arthritis, gouty arthritis, and pigmented villonodular synovitis) from two institutions. A semantic segmentation model was trained on manually annotated sagittal proton density-weighted images. The segmentation results of the regions of interest and patients' sex and age were used to classify knee synovitis after feature processing. Classification by the DL method was compared to the classification performed by radiologists. RESULTS Data of the 376 patients (mean age, 42 ± 15 years; 216 men) were separated into a training set (n = 233), an internal test set (n = 93), and an external test set (n = 50). The automated segmentation model showed good performance (mean accuracy: 0.99 and 0.99 in the internal and external test sets). On the internal test set, the DL model performed better than the senior radiologist (accuracy: 0.86 vs. 0.79; area under the curve [AUC]: 0.83 vs. 0.79). On the external test set, the DL diagnostic model based on automatic segmentation performed as well or better than senior and junior radiologists (accuracy: 0.79 vs. 0.79 vs. 0.73; AUC: 0.76 vs. 0.77 vs. 0.70). CONCLUSION DL models for segmentation of SC and IPFD can accurately classify knee synovitis and aid radiologic diagnosis.
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Affiliation(s)
- Qizheng Wang
- Peking University Third Hospital, Department of Radiology, 49 North Garden Road, Haidian District, Beijing, PR China (Q.W., X.X., Y.C., K.L., N.L.)
| | - Meiyi Yao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, PR China (M.Y., X.S., S.J.)
| | - Xinhang Song
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, PR China (M.Y., X.S., S.J.)
| | - Yandong Liu
- Beijing Jishuitan Hospital, Department of Radiology, 31 Xinjiekou East Street, Beijing, PR China (Y.L., X.C.)
| | - Xiaoying Xing
- Peking University Third Hospital, Department of Radiology, 49 North Garden Road, Haidian District, Beijing, PR China (Q.W., X.X., Y.C., K.L., N.L.)
| | - Yongye Chen
- Peking University Third Hospital, Department of Radiology, 49 North Garden Road, Haidian District, Beijing, PR China (Q.W., X.X., Y.C., K.L., N.L.)
| | - Fangbo Zhao
- Peking University, No.5 YiHeYuan Road, Haidian District, Beijing, PR China (F.Z.)
| | - Ke Liu
- Peking University Third Hospital, Department of Radiology, 49 North Garden Road, Haidian District, Beijing, PR China (Q.W., X.X., Y.C., K.L., N.L.)
| | - Xiaoguang Cheng
- Beijing Jishuitan Hospital, Department of Radiology, 31 Xinjiekou East Street, Beijing, PR China (Y.L., X.C.)
| | - Shuqiang Jiang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, PR China (M.Y., X.S., S.J.)
| | - Ning Lang
- Peking University Third Hospital, Department of Radiology, 49 North Garden Road, Haidian District, Beijing, PR China (Q.W., X.X., Y.C., K.L., N.L.).
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Raya JG, Duarte A, Wang N, Mazzoli V, Jaramillo D, Blamire AM, Dietrich O. Applications of Diffusion-Weighted MRI to the Musculoskeletal System. J Magn Reson Imaging 2024; 59:376-396. [PMID: 37477576 DOI: 10.1002/jmri.28870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 07/22/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- José G Raya
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - Alejandra Duarte
- Division of Musculoskeletal Radiology, Department of Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, Indiana, USA
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Diego Jaramillo
- Department of Radiology, Columbia University Medical Center, New York, New York, USA
| | - Andrew M Blamire
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Olaf Dietrich
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
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Mostert JM, Dur NB, Li X, Ellermann JM, Hemke R, Hales L, Mazzoli V, Kogan F, Griffith JF, Oei EH, van der Heijden RA. Advanced Magnetic Resonance Imaging and Molecular Imaging of the Painful Knee. Semin Musculoskelet Radiol 2023; 27:618-631. [PMID: 37935208 PMCID: PMC10629992 DOI: 10.1055/s-0043-1775741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023]
Abstract
Chronic knee pain is a common condition. Causes of knee pain include trauma, inflammation, and degeneration, but in many patients the pathophysiology remains unknown. Recent developments in advanced magnetic resonance imaging (MRI) techniques and molecular imaging facilitate more in-depth research focused on the pathophysiology of chronic musculoskeletal pain and more specifically inflammation. The forthcoming new insights can help develop better targeted treatment, and some imaging techniques may even serve as imaging biomarkers for predicting and assessing treatment response in the future. This review highlights the latest developments in perfusion MRI, diffusion MRI, and molecular imaging with positron emission tomography/MRI and their application in the painful knee. The primary focus is synovial inflammation, also known as synovitis. Bone perfusion and bone metabolism are also addressed.
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Affiliation(s)
- Jacob M. Mostert
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Niels B.J. Dur
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Orthopedics and Sports Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Xiufeng Li
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota
| | - Jutta M. Ellermann
- Department of Radiology, Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, Minnesota
| | - Robert Hemke
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Laurel Hales
- Department of Radiology, Stanford University, Stanford, California
| | | | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, California
| | - James F. Griffith
- Department of Imaging and Interventional Radiology Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong
| | - Edwin H.G. Oei
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Rianne A. van der Heijden
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
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Hayashi D, Roemer FW, Jarraya M, Guermazi A. Update on recent developments in imaging of inflammation in osteoarthritis: a narrative review. Skeletal Radiol 2023; 52:2057-2067. [PMID: 36542129 DOI: 10.1007/s00256-022-04267-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/11/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022]
Abstract
Synovitis is an important component of the osteoarthritis (OA) disease process, particularly regarding the "inflammatory phenotype" of OA. Imaging plays an important role in the assessment of synovitis in OA with MRI and ultrasound being the most deployed imaging modalities. Contrast-enhanced (CE) MRI, particularly dynamic CEMRI (DCEMRI) is the ideal method for synovitis assessment, but for several reasons CEMRI is not commonly performed for OA imaging in general. Effusion-synovitis and Hoffa-synovitis are commonly used as surrogate markers of synovitis on non-contrast-enhanced (NCE) MRI and have been used in many epidemiological observational studies of knee OA. Several semiquantitative MRI scoring systems are available for the evaluation of synovitis in knee OA. Synovitis can be a target tissue for disease-modifying OA drug (DMOAD) clinical trials. Both MRI and ultrasound may be used to determine the eligibility and assess the therapeutic efficacy of DMOAD approaches. Ultrasound is mostly used for evaluation of synovitis in hand OA, while MRI is typically used for larger joints, namely knees and hips. The role of other modalities such as CT (including dual-energy CT) and nuclear medicine imaging (such as positron-emission tomography (PET) and its hybrid imaging) is limited in the context of synovitis assessment in OA. Despite research efforts to develop NCEMRI-based synovitis evaluation methods, these typically underestimate the severity of synovitis compared to CEMRI, and thus more research is needed before we can rely only on NCEMRI.
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Affiliation(s)
- Daichi Hayashi
- Department of Radiology, Stony Brook University Renaissance School of Medicine, HSc Level 4, Room 120, Stony Brook, NY, 11794, USA.
- Department of Radiology, Boston University School of Medicine, Boston, MA, USA.
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Frank W Roemer
- Department of Radiology, Boston University School of Medicine, Boston, MA, USA
- Department of Radiology, Universitätsklinikum Erlangen & Friedrich-Alexander Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany
| | - Mohamed Jarraya
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ali Guermazi
- Department of Radiology, Boston University School of Medicine, Boston, MA, USA
- VA Boston Healthcare System, West Roxbury, Boston, MA, USA
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Gao MA, Tan ET, Neri JP, Li Q, Burge AJ, Potter HG, Koch KM, Koff MF. Diffusion-weighted MRI of total hip arthroplasty for classification of synovial reactions: A pilot study. Magn Reson Imaging 2023; 96:108-115. [PMID: 36496096 PMCID: PMC9929560 DOI: 10.1016/j.mri.2022.12.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 11/15/2022] [Accepted: 12/04/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Conventional quantitative diffusion-weighted imaging (DWI) is sensitive to changes in tissue microstructure, but its application to evaluating patients with orthopaedic hardware has generally been limited due to metallic susceptibility artifacts. The apparent diffusion coefficient (ADC) and T2-values from a multi-spectral imaging (MSI) DWI combined with 2D multi-spectral imaging with a 2D periodically rotated overlapping parallel lines with enhanced reconstruction (2D-MSI PROPELLER DWI) based sequence and a MAVRIC based T2 mapping sequence, respectively, may mitigate the artifact and provide additional quantitative information on synovial reactions in individuals with total hip arthroplasty (THA). The aim of this pilot study is to utilize a 2D-MSI PROPELLER DWI and a MAVRIC-based T2 mapping to evaluate ADC and T2-values of synovial reactions in patients with THA. METHODS Coronal morphologic MRIs from THA patients underwent evaluation of the synovium and were assigned a synovial classification of 'normal', or 'grouped abnormal' (consisting of sub-groups 'infection', 'polymeric', 'metallosis', 'adverse local tissue reaction' [ALTR], or 'non-specific') and type of synovial reaction present (fluid-like, solid-like, or mixed). Regions of interest (ROIs) were placed in synovial reactions for measurement of ADC and T2-values, obtained from the 2D-MSI PROPELLER DWI and T2-MAVRIC sequences, respectively. A one-way analysis of variance (ANOVA) and Kruskal-Wallis rank sum tests were used to compare the differences in ADC and T2-values across the different synovial reaction classifications. A Kruskal-Wallis test was used to compare the ROI areas for the ADC and T2-values. A principal component analysis (PCA) was performed to evaluate the possible effects of ADC values, size of the ADC ROI, T2-values, and size of the T2 ROI with respect to synovial reaction classification. RESULTS Differences of ADC and T2 among the individual synovial reactions were not found. A difference of ADC between 'normal' and 'grouped abnormal' synovial reactions was also not detected even as the ADC area of 'grouped abnormal' synovial reactions were significantly larger (p = 0.02). The 'grouped abnormal' synovial reactions had significantly shorter T2-values than 'normal' synovial reactions (p = 0.02), and that the T2 area of 'grouped abnormal' synovial reactions were significantly larger (p = 0.01). A larger ROI area on the T2-maps was observed in the mixed synovial reaction type as compared to the fluid-like reaction type area (p = 0.01). Heterogeneity was noted in calculated ADC and T2 maps. PCA analysis revealed obvious clustering by the 'normal' and 'grouped abnormal' classifications. CONCLUSIONS 2D-MSI PROPELLER DWI and MAVRIC-T2 generate quantitative images of periprosthetic tissues within clinically feasible scan times. The combination of derived ADC and T2-values with area of synovial reaction may aid in differentiating normal from abnormal synovial reactions between types of synovial reactions in patients with THA.
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Affiliation(s)
- Madeleine A Gao
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - Ek T Tan
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - John P Neri
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - Qian Li
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - Alissa J Burge
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - Hollis G Potter
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America
| | - Kevin M Koch
- Medical College of Wisconsin, 8701 W Watertown Plank Rd, Milwaukee, WI 53226, United States of America
| | - Matthew F Koff
- Hospital of Special Surgery, 535 East 70(th) Street, New York, NY 10021, United States of America.
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Hayashi D, Roemer FW, Link T, Li X, Kogan F, Segal NA, Omoumi P, Guermazi A. Latest advancements in imaging techniques in OA. Ther Adv Musculoskelet Dis 2022; 14:1759720X221146621. [PMID: 36601087 PMCID: PMC9806406 DOI: 10.1177/1759720x221146621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 12/05/2022] [Indexed: 12/28/2022] Open
Abstract
The osteoarthritis (OA) research community has been advocating a shift from radiography-based screening criteria and outcome measures in OA clinical trials to a magnetic resonance imaging (MRI)-based definition of eligibility and endpoint. For conventional morphological MRI, various semiquantitative evaluation tools are available. We have lately witnessed a remarkable technological advance in MRI techniques, including compositional/physiologic imaging and automated quantitative analyses of articular and periarticular structures. More recently, additional technologies were introduced, including positron emission tomography (PET)-MRI, weight-bearing computed tomography (CT), photon-counting spectral CT, shear wave elastography, contrast-enhanced ultrasound, multiscale X-ray phase contrast imaging, and spectroscopic photoacoustic imaging of cartilage. On top of these, we now live in an era in which artificial intelligence is increasingly utilized in medicine. Osteoarthritis imaging is no exception. Successful implementation of artificial intelligence (AI) will hopefully improve the workflow of radiologists, as well as the level of precision and reproducibility in the interpretation of images.
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Affiliation(s)
- Daichi Hayashi
- Department of Radiology, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA,Department of Radiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA
| | - Frank W. Roemer
- Department of Radiology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA,Department of Radiology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Thomas Link
- Department of Radiology, University of California San Francisco, San Franciso, CA, USA
| | - Xiaojuan Li
- Department of Radiology, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA
| | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Neil A. Segal
- Department of Rehabilitation Medicine, The University of Kansas, Kansas City, KS, USA
| | - Patrick Omoumi
- Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
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Frenken M, Rübsam G, Mewes A, Radke KL, Li L, Wilms LM, Nebelung S, Abrar DB, Sewerin P. To Contrast or Not to Contrast? On the Role of Contrast Enhancement in Hand MRI Studies of Patients with Rheumatoid Arthritis. Diagnostics (Basel) 2022; 12:diagnostics12020465. [PMID: 35204555 PMCID: PMC8871222 DOI: 10.3390/diagnostics12020465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 02/01/2022] [Accepted: 02/09/2022] [Indexed: 12/10/2022] Open
Abstract
Currently, clinical indications for the application of gadolinium-based contrast agents (GBCA) in magnetic resonance imaging (MRI) are increasingly being questioned. Consequently, this study aimed to evaluate the additional diagnostic value of contrast enhancement in MRI of the hand in patients with rheumatoid arthritis (RA). Thirty-one patients with RA (mean age, 50 ± 14 years (range, 18–72 years)) underwent morphologic MRI scans on a clinical 3 T scanner. MRI studies were analyzed based on (1) the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) and (2) the GBCA-free RAMRIS version, termed RAMRIS Sine-Gadolinium-For-Experts (RAMRIS-SAFE), in which synovitis and tenosynovitis were assessed using the short-tau inversion-recovery sequence instead of the post-contrast T1-weighted sequence. The synovitis subscores in terms of Spearman’s ρ, as based on RAMRIS and RAMRIS-SAFE, were almost perfect (ρ = 0.937; p < 0.001), while the tenosynovitis subscores were less strongly correlated (ρ = 0.380 p = 0.035). Correlation between the total RAMRIS and RAMRIS-SAFE was also almost perfect (ρ = 0.976; p < 0.001). Inter-rater reliability in terms of Cohen’s κ was high (0.963 ≤ κ ≤ 0.925). In conclusion, RAMRIS-SAFE as the GBCA-free version of the well-established RAMRIS is a patient-friendly and resource-efficient alternative for assessing disease-related joint changes in RA. As patients with RA are subject to repetitive GBCA applications, non-contrast imaging protocols should be considered.
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Affiliation(s)
- Miriam Frenken
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
- Correspondence:
| | - Gesa Rübsam
- Department and Hiller Research Unit of Rheumatology, Heinrich Heine University Düsseldorf, UKD, Moorenstrasse 5, 40225 Düsseldorf, Germany; (G.R.); (P.S.)
| | - Alexander Mewes
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
| | - Karl Ludger Radke
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
| | - Lien Li
- Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Marchioninistr. 15, 81377 Munich, Germany;
| | - Lena M. Wilms
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
| | - Sven Nebelung
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
- Department of Diagnostic and Interventional Radiology, Aachen University Hospital, 52074 Aachen, Germany
| | - Daniel B. Abrar
- Institute of Diagnostic and Interventional Radiology, University Hospital of Düsseldorf, Moorenstraße 5, 40225 Dusseldorf, Germany; (A.M.); (K.L.R.); (L.M.W.); (S.N.); (D.B.A.)
| | - Philipp Sewerin
- Department and Hiller Research Unit of Rheumatology, Heinrich Heine University Düsseldorf, UKD, Moorenstrasse 5, 40225 Düsseldorf, Germany; (G.R.); (P.S.)
- Rheumazentrum Ruhrgebiet Herne, Ruhr-University Bochum, 44649 Herne, Germany
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