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Late synovial enhancement detects effects of intraarticular steroids on synovitis better than synovial volume A. D. Gait1, E. J. Marjanovic1,2, M. J. Parkes2,R. Hodgson1, T. F. Cootes1, T. W. O'Neill2,5, C. E. Hutchinson3, D. T. Felson2,4,5 1Department of Imaging Science and Biomedical Engineering (ISBE), Univ. of Manchester, Manchester, UNITED KINGDOM. in Osteoarthritis Manchester (ROAM), Arthritis Research UK Epidemiology Unit, Univ. of Manchester, Manchester, UNITED KINGDOM. School, Univ. of Warwick, Coventry, UNITED KINGDOM. 4Clinical Epidemiology Unit, Boston Univ. School of Medicine, Boston, MA, USA. 5NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester NHS Foundation Trust, Manchester Academic Health Sciences Centre, Manchester, UNITED KINGDOM. 2Research 3Warwick Medical BACKGROUND In knee OA, knee pain decreases after intra-articular steroid treatment but the optimal way to assess an effect of this treatment on synovium is unknown. On contrast enhanced MRI, static synovial volume can be quantified as can the dynamic rate of enhancement of synovium at different times after contrast injection. The best way to evaluate synovium after treatment would maximize the correlation between synovial change and pain change. AIM In persons undergoing intra-articular steroid injections of the knee, do changes in dynamic parameters of synovial enhancement correlate better with reduction in knee pain than changes in static synovial volumes? METHODS Subjects with symptomatic knee OA (ACR criteria) Design: Open Label Clinical Trial (‘TASK’) ISRCTN07329370, in which subjects had 2 contrast enhanced MRI’s, one before intraarticular steroid injection and one 5-15 days afterward. Intervention: Intra-articular depomedrone 80mg Pain Assessments: VAS score - pain on nominated activity (VASNA): 0 (no pain) to 10 Assessments at baseline and 5-15 days post injection FIGURE 2: EXAMPLES OF RESULTS OF IMAGE ANALYSIS FOLLOWING MANUAL SEGMENTATION OF SYNOVIAL TISSUE LAYER (CARTILAGE: GREEN; SYNOVIAL FLUID: BLUE; SYNOVIAL TISSUE: RED) Baseline, TA024 Baseline, TA009 Visit 2, TA024 Visit 2, TA009 We overlaid the manually segmented regions of synovial tissue onto these parameter images (via image registration) and calculated the median value. STATISTICAL ANALYSIS Assessment of the change in static volume V and dynamic parameters from baseline to post-injection visit was done by calculation of a Pearson coefficient correlation matrix. Assessment of linear regression measures between each of these parameters and each pain scale was then performed. RESULTS For the 72 patients (41.7% female, mean age 64.3), every dynamic parameter showed a reduction in response to treatment between baseline and follow-up (Table 1). TABLE 1: STANDARDISED RESPONSE MEANS FOR CHANGE IN EACH PARAMETER IN THE STUDY, FOLLOWING TREATMENT IMAGING Variable MRI Scan: 3T Philips MRI, Gadolinium-enhanced sequences (~7 minutes, axial, 18 images at ~22-second intervals) TR 5.3 ms, TE 1.463 ms, FoV 14cmx14cm, Slice thickness 3mm (used for dynamic data) (sagittal), taken ~8 minutes after enhancement: TR 500ms, TE 17ms, FoV 15.9cm x 15.9cm, Slice thickness 3mm (used for static volumes) (Figure 1) Variable description SRM (mean change / SD(mean change)) Permeability parameter in Tofts equation Fractional volume of extrave cellular space Fractional volume of plasma vp space Ktrans V FIGURE 1: POST GD-ENHANCED MRI SHOWING SYNOVITIS CHANGE -0.62 -0.46 -0.23 (Static) volume -0.41 V×s (Static) volume * synovial fraction -0.37 Gmax Maximum gradient -0.63 Sl Late relative enhancement -0.76 Maximum relative enhancement Visual analogue scale for Pain on nominated activity VAS pain, completed by patient Sr Baseline visit Post-injection visit IMAGE ANALYSIS: MANUAL SEGMENTATION Manual segmentation of the synovial tissue layer (including fluid and possibly cartilage) was performed on the post contrast knee image by a single observer (ICC=0.94). We excluded cartilage within the segmented space by thresholding in a registered sagittal scan (3DWATSc: TR 20ms, TE 7.7ms, FoV 15cmx15cm, slice thickness 1.5mm). We calculated the proportion s of synovial tissue in every voxel using s=(S-mf)/(ms-mf) truncated to [0,1], where S is the voxel intensity and mf, ms are the means of the intensity distributions of fluid and synovial tissue volume (Figure 2). Sl, Sr and Gmax all correlated with K trans -0.73 -1.17 (Table 2). TABLE 2: PEARSON CORRELATION COEFFICIENT MATRIX Correlations Ktrans Ktrans 1.00 ve vp ve 0.71 1.00 vp -0.13 -0.10 1.00 V V×s G max Sl Sr V 0.15 0.10 0.04 1.00 V×s 0.11 0.08 0.13 0.94 1.00 Gmax 0.70 0.34 0.21 0.09 0.03 1.00 Sl 0.78 0.66 -0.04 0.23 0.18 0.71 1.00 Sr 0.74 0.61 -0.05 0.20 0.14 0.74 0.98 1.00 Pain on nominated activity VAS* 0.27 0.23 0.02 0.19 0.19 0.07 0.29 0.29 Pain on nominated activity VAS* Colour Scale: 1.00 0.75 0.50 0.25 0.00 -0.25 -0.50 -0.75 -1.00 1.00 *Observations are 64 due to 8 patients missing VAS observations (patients did not complete question) The parameter with the strongest correlation with change in VAS IMAGE ANALYSIS: DYNAMIC PARAMETERS We used the extended Tofts model 𝑡 𝐾 𝑡𝑟𝑎𝑛𝑠 (𝑡−𝜏) − FIGURE 3: DIAGRAM OF DYNAMIC PARAMETERS 𝑑𝜏 𝐶𝑡 𝑡 = 𝑣𝑝 𝐶𝑝 𝑡 + 𝐾 𝑡𝑟𝑎𝑛𝑠 0 𝐶𝑝 (𝜏)𝑒 𝑣𝑒 which is a solution of the pharmacokinetic ve trans ve equation, to calculate the parameters K Ktrans (permeability), ve (extra-cellular space) and vp vi (plasma space) at every image voxel (Figure 3). vi We calculated parameters at each voxel based vp upon the time series of intensity Si (i=0,..,n) over the dynamic sequence: (a) the maximum gradient Gmax, (b) the maximum relative enhancement Sr=Smax/S0, and (c) the late relative enhancement Sl=(Sn+…+Sn-3)/(4*S0) pain was change in Sl (r=0.29, b=0.64; 95% CI 0.11 to 1.17; p=0.02), which is a stronger correlation than change in volume V*s (r=0.19, b=0.18; 95% CI -0.05 to 0.41; p=0.13). Other parameters with strong correlations to change in VAS pain were change in Sr (r=0.29, b=0.56; 95% CI 0.09 to 1.03; p=0.02) and change in Ktrans (r=0.27, b=26.93; 95% CI 2.24 to 51.63; p=0.03). CONCLUSION Dynamic measures of synovial enhancement correlate more strongly with pain reduction after intraarticular steroid injection than static measures of change in synovial volume. In studies examining synovial response to treatment in osteoarthritis, dynamic parameters may optimize the detection of treatment effects. ACKNOWLEDGEMENTS Thanks to Ross Little and Sue Cheung of Imaging Sciences, University of Manchester, and to Gio Buccanorsi of Bioxydyn, for their insights into the DCE-MRI modelling used in this work, gained from their experiences in oncological studies over a number of years. Supported by Arthritis Research UK programme grant 18676; Manchester Academic Health Science Centre (MAHSC); Salford Royal NHS Foundation Trust; National Institute for Health Research (NIHR)