Diffusion Tensor and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Correlate with Molecular Markers of Inflammation in the Synovium

Abstract

Objectives: It is difficult to capture the severity of synovial inflammation on imaging. Herein we hypothesize that diffusion tensor imaging (DTI) derived metrics may delineate the aggregation of the inflammatory cells and expression of inflammatory cytokines and dynamic contrast-enhanced (DCE) imaging may provide information regarding vascularity in the inflamed synovium. Patients and methods: Patients with knee arthritis (>3-months duration) underwent conventional (T2-weighted fast spin echo and spin echo T1-weighted images) as well as DTI and DCE MRI and thereafter arthroscopic guided synovial biopsy. DCE and DTI metrics were extracted from the masks of the segments of the inflamed synovium which enhanced on post-contrast T1-weighted MRI. These metrics were correlated with immunohistochemistry (IHC) parameters of inflammation on synovium. Statistical analysis: Pearson’s correlation was performed to study the relationship between DTI- and DCE-derived metrics, IHC parameters, and post-contrast signal intensity. Linear regression model was used to predict the values of IHC parameters using various DTI and DCE derived metrics as predictors. Results: There were 80 patients (52 male) with mean age 39.78 years and mean disease duration 19.82 months. Nineteen patients had tuberculosis and the rest had chronic undifferentiated monoarthritis (n = 31), undifferentiated spondyloarthropathy (n = 14), rheumatoid arthritis (n = 6), osteoarthritis (n = 4), reactive arthritis (n = 3), ankylosing spondylitis (n = 2), and juvenile idiopathic arthritis (n = 1). Fractional anisotropy (FA), a metric of DTI, had significant correlation with number of immune cells (r = 0.87, p < 0.01) infiltrating into the synovium and cytokines (IL-1β, r = 0.55, p < 0.01; TNF-α, r = 0.42, p < 0.01) in all patients and also in each group of patients and adhesion molecule expressed on these cells in all patients (CD54, r = 0.51, p < 0.01). DCE parameters significantly correlated with CD34 (blood flow, r = 0.78, p < 0.01; blood volume, r = 0.76, p < 0.01) in each group of patients, a marker of neo-angiogenesis. FA was the best predictor of infiltrating inflammatory cells, adhesion molecule and proinflammatory cytokines. Amongst the DCE parameters, blood volume, was best predictor of CD34. Conclusion: DTI and DCE metrics capture cellular and molecular markers of synovial inflammation in patients with chronic inflammatory arthritis.

Keywords: ankylosing spondylitis; markers of inflammation; osteoarthritis; rheumatoid arthritis; synovial histology; tuberculosis; undifferentiated arthritis.

Figure 1

Imaging of the knee joints of arthritis patients presenting with varying grades of inflammation. Imaging of the knee joints of arthritis patients presenting with varying grades of inflammation. Fat-suppressed post-contrast T1-weighted images show increase in contrast enhancement on moving from mild to severe inflammation (lane A, 1–3). On post-processing of dynamic contrast-enhanced and diffusion tensor-magnetic resonance imaging data, blood flow (BF), (B), blood volume (BV), (C), rate transfer coefficient k_ep (min⁻¹) (D) and fractional anisotropy (FA) (E) maps show increase, while mean diffusivity (MD) (F) map shows decrease in its values on moving from mild to severe synovitis (1–3).

Figure 2

Immunohistochemistry of knee synovium from arthritis patients showing varying grades (1–3) of severity of inflammation and infiltration by various inflammatory cells. Immunohistochemistry of knee synovium from arthritis patients (1, 2, and 3) showing varying grades of infiltration by various inflammatory cells-. T cells (CD3, CD4, CD8) (lane A, B, C respectively); B cells (CD 20) (lane D), plasma cells (CD138) (lane H); and macrophages (CD 68) (lane G). Cells expressing adhesion molecule ICAM-1(CD54) (lane F), TNF-α (lane I) and IL-1β (lane J) are also shown. Immunostaining for endothelial cells (CD34) (lane E) shows the varying density of micro vessels in the synovial tissue.

Figure 3

Correlation of inflammatory cell infiltration with fractional anisotropy. Spearman’s correlation scatter plots represent the correlation between (A) FA and CD3, (B) CD4, (C) CD8, (D) CD20, (E) IL-1β positive cells, (F) TNF-α positive cells, (G) CD68 and (H) total number of inflammatory cells in the synovium.