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Bone structure and perfusion quantification of bone marrow edema pattern in the wrist of patients with rheumatoid
Jose R Teruel1, Andrew J Burghardt1, Julien Rivoire1
1From the Musculoskeletal Quantitative Imaging Research Group, Department of Radiology and Biomedical Imaging, University of California, San Francisco; San Francisco, California, USA.J.R. Teruel, MSc, Research Fellow, Department of Radiology and Biomedical Imaging, University of California, San Francisco (UCSF); PhD Candidate, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; A.J. Burghardt, Researcher, Department of Radiology and Biomedical Imaging, UCSF; J. Rivoire, PhD, Postdoctoral Research Fellow, Department of Radiology and Biomedical Imaging, UCSF; W. Srikhum, MD, Research Fellow, Department of Radiology and Biomedical Imaging, UCSF; Lecturer in Radiology, Department of Radiology, Thammasat University, Pathum Thani, Thailand; S.M. Noworolski, PhD, Associate Professor, Department of Radiology and Biomedical Imaging, UCSF; T.M. Link, MD, PhD, Professor of Radiology, Chief, Musculoskeletal Imaging and Clinical Director, Musculoskeletal and Quantitative Imaging Research Group, Department of Radiology and Biomedical Imaging, UCSF; J.B. Imboden, MD, Professor of Rheumatology, Department of Medicine, UCSF; X. Li, PhD, Associate Professor, Department of Radiology and Biomedical Imaging, UCSF.
Objective:
To quantify bone structure and perfusion parameters in regions of bone marrow edema pattern (BMEP), non-edematous bone marrow (NBM), and pannus tissue areas in the wrists of patients with rheumatoid arthritis (RA) using 3-Tesla (3T) magnetic resonance imaging (MRI), and high resolution peripheral quantitative computed tomography (HR-pQCT).
Methods:
Sixteen subjects fulfilling American College of Rheumatology classification were imaged using a HR-pQCT system and a 3T MRI scanner with an 8-channel wrist coil. Coronal T2-weighted and dynamic contrast-enhanced (DCE-MRI) images were acquired. BMEP and pannus tissue areas were segmented semiautomatically in T2-weighted images. NBM areas were placed at a similar distance from the joint space as BMEP regions. MR and HR-pQCT images were registered, and bone variables were calculated within the BMEP and NBM regions. Perfusion parameters in BMEP, pannus tissue, and NBM regions were calculated based on the signal-time curve obtained from DCE-MRI.
Results:
Eighteen BMEP areas were segmented, 15 of them presented proximal to pannus-filled erosions. Significant increases in bone density and trabecular thickness and number were observed in all BMEP regions compared to NMB (p < 0.05). Significantly elevated perfusion measures were observed in both BMEP and pannus tissue regions compared to NBM (p < 0.05).
Conclusion:
BMEP regions showed significantly increased bone density and structures as well as perfusion measures, suggesting bone remodeling and active inflammation. Combining MRI and HR-pQCT provides a powerful multimodality approach for understanding BMEP and erosions, and for potentially identifying novel imaging markers for disease progression in RA.
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