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Koppikar S, Diaz P, Kaeley GS, Eder L. Seeing is believing: Smart use of musculoskeletal ultrasound in rheumatology practice. Best Pract Res Clin Rheumatol 2023; 37:101850. [PMID: 37481369 DOI: 10.1016/j.berh.2023.101850] [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: 05/10/2023] [Accepted: 06/19/2023] [Indexed: 07/24/2023]
Abstract
Musculoskeletal ultrasonography has become an increasingly valuable tool as a complement to the physical exam in rheumatology practice. Its point-of-care access, low cost, safety, portability, and reliability in trained hands, make this technique especially useful in patients with inflammatory arthritis. Growing evidence has demonstrated the value of musculoskeletal ultrasound in the detection of inflammatory and structural changes in patients with joint pain without obvious joint swelling, in differentiating various inflammatory diagnoses, in the monitoring of inflammatory arthritis, and interventional procedures. The potential role of ultrasound guiding treat-to-target strategies or tapering treatment in inflammatory arthritis requires further research. However, musculoskeletal ultrasound can also have pitfalls and limitations that a clinician should be aware of.
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Affiliation(s)
- Sahil Koppikar
- Division of Rheumatology, Women's College Hospital, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Pamela Diaz
- Departamento de Inmunologia Clinica y Reumatologia, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - Gurjit S Kaeley
- Division of Rheumatology and Clinical Immunology, University of Florida College of Medicine, Jacksonville, FL, USA
| | - Lihi Eder
- Division of Rheumatology, Women's College Hospital, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada.
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Kato M, Ikeda K, Sugiyama T, Tanaka S, Iida K, Suga K, Nishimura N, Mimura N, Kasuya T, Kumagai T, Furuya H, Iwamoto T, Iwata A, Furuta S, Suto A, Suzuki K, Kawakami E, Nakajima H. Associations of ultrasound-based inflammation patterns with peripheral innate lymphoid cell populations, serum cytokines/chemokines, and treatment response to methotrexate in rheumatoid arthritis and spondyloarthritis. PLoS One 2021; 16:e0252116. [PMID: 34019595 PMCID: PMC8139502 DOI: 10.1371/journal.pone.0252116] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 05/10/2021] [Indexed: 01/22/2023] Open
Abstract
Objectives We aimed to explore the associations of musculoskeletal inflammation patterns with peripheral blood innate lymphoid cell (ILC) populations, serum cytokines/chemokines, and treatment response to methotrexate in patients with rheumatoid arthritis (RA) and spondyloarthritis (SpA). Methods We enrolled 100 patients with either RA or SpA and performed ultrasound to evaluate power Doppler signals for synovitis (52 joint regions), tenosynovitis (20 tendons), and enthesitis (44 sites). We performed clustering analysis using unsupervised random forest based on the multi-axis ultrasound information and classified the patients into groups. We identified and counted ILC1-3 populations in the peripheral blood by flow cytometry and also measured the serum levels of 20 cytokines/chemokines. We also determined ACR20 response at 3 months in 38 patients who began treatment with methotrexate after study assessment. Results Synovitis was more prevalent and severe in RA than in SpA, whereas tenosynovitis and enthesitis were comparable between RA and SpA. Patients were classified into two groups which represented synovitis-dominant and synovitis-nondominant inflammation patterns. While peripheral ILC counts were not significantly different between RA and SpA, they were significantly higher in the synovitis-nondominant group than in the synovitis-dominant group (ILC1-3: p = 0.0007, p = 0.0061, and p = 0.0002, respectively). On the other hand, clustering of patients based on serum cytokines/chemokines did not clearly correspond either to clinical diagnoses or to synovitis-dominant/nondominant patterns. The synovitis-dominant pattern was the most significant factor that predicted clinical response to methotrexate (p = 0.0065). Conclusions Musculoskeletal inflammation patterns determined by ultrasound are associated with peripheral ILC counts and could predict treatment response to methotrexate.
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Affiliation(s)
- Manami Kato
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Kei Ikeda
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
- * E-mail:
| | - Takahiro Sugiyama
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Shigeru Tanaka
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Kazuma Iida
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Kensuke Suga
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Nozomi Nishimura
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Norihiro Mimura
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Tadamichi Kasuya
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Takashi Kumagai
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Hiroki Furuya
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Taro Iwamoto
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Arifumi Iwata
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Shunsuke Furuta
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Akira Suto
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Kotaro Suzuki
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Eiryo Kawakami
- Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
- Medical Sciences Innovation Hub Program, RIKEN, Wako, Saitama, Japan
| | - Hiroshi Nakajima
- Department of Allergy and Clinical Immunology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
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