Patients
Twelve patients with early rheumatoid arthritis were recruited as part of an ongoing study in patients with early inflammatory arthritis. Disease duration was considered to be from reported symptom onset. All patients were recruited from the early arthritis clinic within the department of rheumatology, Barts Health NHS Trust. All patients had a clinically involved knee joint and fulfilled the American College of Rheumatology (AC) diagnostic criteria (1987) for rheumatoid arthritis. Patients were treatment-naive prior to all assessment and received a clinical assessment, US examination and US-guided synovial biopsy from the supra-patella pouch (SPP). All procedures were performed following written informed consent and were approved by Kings College hospital, London, ethics committee (REC 05/Q0703/198).
Ultrasound-guided synovial biopsy technique
US-guided synovial biopsy and standard US images were performed using a GE Logic 9 ultrasound machine with a two-dimensional M12L transducer as previously described [16]. Using a 14G Quick-Core® Biopsy Needle (Cook medical, Limerick, Ireland), tissue was harvested from the medial, middle and lateral aspects of the supra-patella pouch. The needle biopsy was repeatedly positioned in each of the three segments and the US probe used to guide the throw of the needle into the correct anatomical position. A minimum of six samples were retrieved from each region of interest (ROI) (typically 6 to 10 samples). Samples were retrieved from each region and separately processed for immunohistochemistry and RNA extraction.
Ultrasound score
US images of the knee and supra-patella pouch (SPP) were recorded by a single operator (MD) and analysed by two independent examiners (SK, NN) blinded to the clinical and histological data. Three standardised, 3-second cine loops, were recorded pre-biopsy from i) the midline SPP pouch ii) the medial SPP pouch iii) the lateral SPP pouch corresponding to region of synovial tissue sampling with the knee in 30 degrees of flexion. A single sonographer acquired all images. The area demonstrating the maximum Doppler and synovial thickness within each third of the SPP was selected. Training was provided alongside an atlas of probe positions to guide image acquisition. The superior border of the patella was visualized prior to image acquisition. The medial corner of the upper border of the patella corresponding to the base of the medial US image and the lateral corner similarly corresponding to the base of the lateral US image. The midline image included the quadriceps tendon as it inserts into the patella with visualization of the pre-patella fat pad lying superior to the SPP. Synovial tissue was defined as hypoechoic non-compressible intra-articular tissue. Power Doppler settings were adjusted to the lowest permissible pulse repetition frequency to maximize sensitivity. Maximum colour gain was used without creating artefact noise. A standard depth of 3.8 cm was used for each image acquisition. Quantitative analysis of the recorded cine loops was performed using Image J (NIH, [17]. 1997 to 2008) non-proprietary freeware. A dedicated macro was used. The use of a cine loop allows selection of the maximal Doppler signal in that particular ROI given the variations with blood flow with cardiac output. The software facilitates manual drawing of the outline of the synovium within the SPP. Care was taken to isolate synovial fluid from the ROI. The output of the software provides information on the image selected and corresponding pixel count for both synovial area and Doppler signal. Quantitative measurements provided included synovial area quantitative score (SQuant) and power Doppler area quantitative score (PQuant), high-intensity power Doppler signal (representing high-velocity blood flow) over a predetermined colour threshold (PDHi) and a ratio of synovial to Doppler area (PQuant/SQuant). A qualitative score was applied to both the grey-scale synovial thickness (synovial semiquantitative score, SSS) and total power Doppler vascular signal (power Doppler semiquantitative score, PSS) for each region of the SPP on an ordinal scale of 0 to 3. Images were scored quantitatively and qualitatively by two experienced readers (NN and SK) with good agreement (grey-scale synovial thickness intraclass correlation coefficient (ICC) 0.87, power Doppler ICC 0.96).
Synovial tissue processing
Each synovial specimen was divided into two parts: one was formalin fixed and paraffin embedded for immunohistologic analysis and the second was stored in RNA later (AMBION Life Technologies Ltd, UK) at −80°C until RNA extraction and quantitative PCR analysis.
Immunohistochemistry
Paraffin-embedded tissue specimens were cut in consecutive 3-μm-thick sections. Haematoxylin and eosin stain was performed to ensure tissue morphology was preserved: only tissue sections with an intact lining layer were used and tissue was graded according to a previously reported scoring system (Krenn synovitis score) [18]. Immunohistochemistry-stained specimens for T-cells, macrophages and plasma cells (CD3, CD68 and CD138 respectively) are scored on a 5-point scale of 0 to 4 depending on the increasing number of positively stained cells calibrated against a standardised atlas [19].
To quantify vascular density in the synovial tissue in terms of both number and size of vessel profiles, double immunofluorescent staining for factor VIII and α smooth muscle actin (α-SMA) was used. The following primary antibodies were used for immunofluorescence analysis: mouse anti human factor VIII (clone F8/86; Dako, Glostrup, Denmark), Cy3 conjugated mouse anti α-SMA (clone 1A4; Sigma-Aldrich, St Louis, MO, USA). The appropriate secondary antibody for factor VIII was obtained from Invitrogen, Paisley, UK. As negative control irrelevant isotype-matched antibodies (Dako, Glostrup, Denmark) were used. Briefly, antigen retrieval was performed by heating for 35 minutes at 95°C in Dako Target Retrieval Solution. Sections when then washed in Tris buffered saline, incubated with protein block (Dako) and then in the first primary antibody for one hour (mouse anti human factor-VIII using antibody dilution of 1:50). After washing, the appropriate Alexa-488 conjugated secondary antibody was applied for 30 minutes; sections were then washed and the directly conjugated second primary antibody, α-SMA, was added at dilution of 1:200. Synovial tissue was counterstained with 4’-6-diamidino-2-phenylindole (DAPI) and mounted with anti-fade mounting medium. To obtain a more representative assessment of synovial vascularity all available synovial specimens were cut and stained at two different cutting levels 50 μm apart. Sections without a defined synovial lining, or with folded areas after staining, were omitted from the analysis. Assessors of histological scores and vascular area assessments were blinded to patient characteristics and US findings.
Digital image analysis for synovial vascularity evaluation
One observer, blinded to patients and clinical data, performed both image acquisition and subsequent image analysis for all the sections. Digital images of immunofluorescent-stained synovial blood vessels, were acquired at 20 times magnification on a fully automated Olympus BX61 microscope, captured using a video camera and then digitized using Cell P image analysis software. Each acquisition was performed in one single session for each vascular marker, factor-VIII and α-SMA, respectively, with fixed variable as derived from the calibration. The obtained factor-VIII and α-SMA stained images were saved in jpeg format and used for the subsequent digital images analysis. A selected area was defined as the ROI for both blood vessel density evaluation and digital vessel size analysis. The vascular objects greater than 10 μm in diameter were quantified within the selected ROI, using Cell P analysis software and expressed as blood vessel numerical density (number of vessels per square millimeter, BV/mm2) and vessel fractional area (synovial vascular area, SVA/mm2), respectively (Figure 1A). Vessels were sub-catergorised using a unique colour based on blood vessel area (Figure 1B). Vascular density, cellular markers of inflammation and US parameters were assessed for each region within the SPP (Figure 1C).
Quantitative (QT)-PCR of endothelial-specific genes
Total RNA was extracted from the remaining portion of synovial tissue stored in RNA later, using the RNeasy Mini Kit (Qiagen, Chatsworth, CA, USA), with on-column DNase I digestion to avoid genomic DNA contamination. Seven of the thirteen patients had additional tissue available for RNA extraction. cDNA was generated from 1 ug of RNA using the Thermoscript RT-PCR System (Invitrogen, San Diego, CA, USA). QT-PCR was performed to detect mRNA expression levels of Ang-1, Ang 2, VEGF-A, VEGF-C Tie-2 and VEGFR3. The RT-PCR was run in triplicate with an equal loading of 20 ng of cDNA/well. Results were analysed after 40 cycles of amplification using the ABI PRISM 7900HT Sequence Detection System Version 3. Relative quantification was measured using the comparative Ct (threshold cycle) method. cDNA from human placenta was used as a positive control.
Statistics
Statistical analysis was performed with SPSS version 16. Demographic characteristics of patients are described with mean and interquartile range. Correlation between variables were expressed by Spearman's rho test. Multiple linear regression was performed to analyse the relationship between US parameters and vascular area, immunohistochemistry and gene expression. P-values <0.05 were taken as statistically significant.