Walter P Maksymowych1,2, Robert G Lambert3,4, Xenofon Baraliakos5, Ulrich Weber6,7, Pedro M Machado8,9,10, Susanne J Pedersen11, Manouk de Hooge12,13, Joachim Sieper14, Stephanie Wichuk1, Denis Poddubnyy14, Martin Rudwaleit15,16, Désirée van der Heijde17, Robert Landewe18,19, Iris Eshed20, Mikkel Ostergaard11,21. 1. Department of Medicine, University of Alberta, Edmonton. 2. CARE Arthritis. 3. Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Canada. 4. Medical Imaging Consultants, Edmonton, Canada. 5. Rheumazentrum Ruhrgebiet Herne, Ruhr-University, Bochum, Germany. 6. Department of Rheumatology, Danish Hospital for Rheumatic Diseases, University Hospital of Southern Denmark, Sønderborg. 7. Department of Regional Health Research, University of Southern Denmark, Odense, Denmark. 8. Department of Rheumatology, University College London Hospitals NHS Foundation Trust. 9. Department of Rheumatology, Northwick Park Hospital, London North West University Healthcare NHS Trust. 10. Centre for Rheumatology and MRC Centre for Neuromuscular Diseases, University College London, London, UK. 11. Copenhagen Center for Arthritis Research, Center for Rheumatology and Spine Diseases, Rigshospitalet, Glostrup, Copenhagen, Denmark. 12. VIB Inflammation Research Center, Ghent University. 13. Rheumatology Department, Ghent University Hospital, Ghent, Belgium. 14. Department of Rheumatology, Charité - Universitätsmedizin Berlin and German Rheumatism Research Centre, Berlin. 15. Klinikum Bielefeld, Bielefeld. 16. Department of Rheumatology, Charité - Universitätsmedizin Berlin, Berlin, Germany. 17. Leiden University Medical Centre, Leiden. 18. Department of Rheumatology, Academic Medical Center, University of Amsterdam, Amsterdam. 19. Atrium Medical Center, Heerlen, the Netherlands. 20. Sheba Medical Center, Affiliated to the Sackler School of Medicine, Tel-Aviv University, Tel Aviv, Israel. 21. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.
Abstract
OBJECTIVES: To determine quantitative SI joint MRI lesion cut-offs that optimally define a positive MRI for inflammatory and structural lesions typical of axial SpA (axSpA) and that predict clinical diagnosis. METHODS: The Assessment of SpondyloArthritis international Society (ASAS) MRI group assessed MRIs from the ASAS Classification Cohort in two reading exercises where (A) 169 cases and 7 central readers; (B) 107 cases and 8 central readers. We calculated sensitivity/specificity for the number of SI joint quadrants or slices with bone marrow oedema (BME), erosion, fat lesion, where a majority of central readers had high confidence there was a definite active or structural lesion. Cut-offs with ≥95% specificity were analysed for their predictive utility for follow-up rheumatologist diagnosis of axSpA by calculating positive/negative predictive values (PPVs/NPVs) and selecting cut-offs with PPV ≥ 95%. RESULTS: Active or structural lesions typical of axSpA on MRI had PPVs ≥ 95% for clinical diagnosis of axSpA. Cut-offs that best reflected a definite active lesion typical of axSpA were either ≥4 SI joint quadrants with BME at any location or at the same location in ≥3 consecutive slices. For definite structural lesion, the optimal cut-offs were any one of ≥3 SI joint quadrants with erosion or ≥5 with fat lesions, erosion at the same location for ≥2 consecutive slices, fat lesions at the same location for ≥3 consecutive slices, or presence of a deep (i.e. >1 cm depth) fat lesion. CONCLUSION: We propose cut-offs for definite active and structural lesions typical of axSpA that have high PPVs for a long-term clinical diagnosis of axSpA for application in disease classification and clinical research.
OBJECTIVES: To determine quantitative SI joint MRI lesion cut-offs that optimally define a positive MRI for inflammatory and structural lesions typical of axial SpA (axSpA) and that predict clinical diagnosis. METHODS: The Assessment of SpondyloArthritis international Society (ASAS) MRI group assessed MRIs from the ASAS Classification Cohort in two reading exercises where (A) 169 cases and 7 central readers; (B) 107 cases and 8 central readers. We calculated sensitivity/specificity for the number of SI joint quadrants or slices with bone marrow oedema (BME), erosion, fat lesion, where a majority of central readers had high confidence there was a definite active or structural lesion. Cut-offs with ≥95% specificity were analysed for their predictive utility for follow-up rheumatologist diagnosis of axSpA by calculating positive/negative predictive values (PPVs/NPVs) and selecting cut-offs with PPV ≥ 95%. RESULTS: Active or structural lesions typical of axSpA on MRI had PPVs ≥ 95% for clinical diagnosis of axSpA. Cut-offs that best reflected a definite active lesion typical of axSpA were either ≥4 SI joint quadrants with BME at any location or at the same location in ≥3 consecutive slices. For definite structural lesion, the optimal cut-offs were any one of ≥3 SI joint quadrants with erosion or ≥5 with fat lesions, erosion at the same location for ≥2 consecutive slices, fat lesions at the same location for ≥3 consecutive slices, or presence of a deep (i.e. >1 cm depth) fat lesion. CONCLUSION: We propose cut-offs for definite active and structural lesions typical of axSpA that have high PPVs for a long-term clinical diagnosis of axSpA for application in disease classification and clinical research.
Authors: Walter P Maksymowych; Robert G W Lambert; Liron Caplan; Filip E van den Bosch; Mikkel Østergaard Journal: Nat Rev Rheumatol Date: 2022-05-13 Impact factor: 32.286
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