Abstract
Introduction
Shear‐wave elastographic ultrasound (SW‐EUS) assesses the stiffness of human tissues. It is used in liver, thyroid and breast imaging but has not been studied in synovium. Soft tissues have a slower shear‐wave velocity (SWV) than stiff tissues. We hypothesised that rheumatoid arthritis (RA) patients would have softer synovium than controls and this could be quantified with a slower SWV. We also assessed whether SWV varied with disease activity.
Methods
Nine patients with RA were consecutively recruited and matched with five controls. Participants underwent clinical assessment, blood sampling, grey scale ultrasound (GSUS), power Doppler ultrasound and SW‐EUS of MCP joints 2–5 on the dominant hand.
Results
Average age was 60. Mean RA disease activity (DAS28‐ESR) was moderate at 3.65. Patients with RA had lower maximum synovial SWV than controls (6.38 m/s vs. 6.99 m/s P = 0.042). Negative Pearson's correlation coefficients (PCC) were observed between maximum SWV and disease activity markers including GSUS graded synovial thickness (PCC = −0.57, P = 0.03) and ESR (PCC = −0.46, P = 0.095). Intra‐ and interobserver reliability was good with intraclass correlation coefficients (ICC) of 0.66 and 0.58, respectively, for quantitative maximum SWV and ICC > 0.80 for colour scale rated SWV.
Conclusion
This is the first pilot study of SW‐EUS in synovium. Maximum synovial SWV was significantly lower in RA than controls. There was a negative correlation between maximum SWV and GSUS synovial thickening. Further study is warranted to confirm the role of SW‐EUS in diagnosing and assessing disease activity in RA.
Keywords: elasticity imaging techniques, elastography, rheumatoid arthritis, synovium, ultrasonography
Introduction
Musculoskeletal ultrasonography has an established role in diagnosing, monitoring disease activity and assessing joint damage in rheumatoid arthritis. The standard modalities are grey scale ultrasound (GSUS) which assesses tissue morphology, and power Doppler ultrasound (PDUS) which measures blood flow. Shear‐wave elastographic ultrasound (SW‐EUS) is a third modality that is currently used in liver, thyroid and breast imaging but has never before been studied in synovial tissue. We hypothesised that quantification of synovial stiffness using SW‐EUS may assist in the diagnosis and assessment of disease activity in rheumatoid arthritis (RA).
While GSUS and PDUS can accurately detect synovitis and joint damage and may help to predict future erosions in RA, they have significant limitations.1, 2, 3 Synovial thickening and power Doppler flow may be seen in up to 8.5% patients with OA which contributes to diagnostic uncertainty.4 Sensitivity for erosions is as low as 45%, and PDUS prediction of erosions is imperfect with Pearson's correlation of 0.6.5, 6 Magnetic resonance imaging (MRI) has a number of similar limitations.6
SW‐EUS is one of four elastographic ultrasound techniques that can be used to measure the stiffness of human tissue. It is considered more reliable than strain‐based elastography as it does not require the operator to apply a constant axial force. The technique involves emission of a push pulse of energy from an ultrasound probe into the tissue of interest. This pulse results in the generation of shear waves in the target tissue. The shear‐wave velocity (SWV) relates to tissue stiffness according to the formula Stiffness = 3000 × SWV2 (assuming soft tissue density = 1000 kg/m3).7 According to this relationship, faster SWV is indicative of stiffer tissue and slower SWV indicates softer tissue.2, 7
We hypothesised that patients with RA would have softer synovium than controls, and this could be quantified by slower SWV. Furthermore, we believed that patients with high disease activity would have softer synovium (quantified by slower SWV) than those with low disease activity. Thus, there would be a negative correlation between SWV and disease activity. These hypotheses were based on elastographic and histopathological findings in inflamed Achilles tendons and the fact that ‘soft’ or ‘boggy’ joint swelling is characteristic of active RA.7, 8, 9, 10, 11
Based on these hypotheses, our study had four key objectives:
Develop an assessment and scoring system for SW‐EUS in synovial tissue
Perform a quantitative and qualitative analysis of SW‐EUS in MCP synovium of patients with RA and controls
Determine whether there is a correlation between SW‐EUS and disease activity
Assess the intra‐ and interobserver reliability of SWV‐EUS in synovial tissue
Methods
Nine patients with RA and five controls were enrolled in the study. Patients with RA were recruited consecutively from a single rheumatology practice over a 5‐day period in June 2015. All 106 patients presenting to this practice during this week were screened against the inclusion and exclusion criteria outlined in Figure 1. Twenty‐three patients met these criteria and nine consented and were available to attend the study visit. The five age‐ and sex‐matched controls did not have a history of connective tissue disease, inflammatory arthritis or MCP injury.
Figure 1.
Study Recruitment and Methodology.
Clinical and ultrasound examinations were performed over two study visit days in July 2015. Blood was collected either on the day of examination or in the preceding 8 days and analysed in a single laboratory for C‐reactive protein (CRP) and erythrocyte sedimentation rate (ESR). The clinical visit involved completion of a questionnaire, clinical joint examination, GSUS, PDUS and SW‐EUS studies. Rheumatoid factor (RF) and anticitrullinated protein (CCP) levels for patients with RA were obtained from medical records.
Clinical examination was performed by a non‐blinded clinician and involved a 28 joint count for swelling and tenderness. Ultrasound examination was undertaken by two musculoskeletal trained sonographers. Both were blinded to patient diagnosis, clinical examination results, pathology and previous ultrasound findings. SW‐EUS was performed first, followed by GSUS and PDUS. Sonographers scored the studies at time of scanning. Five patients were scanned twice by the same sonographer, and five patients were scanned by both sonographers to allow assessment of intra‐ and interobserver reliability. Scanning was carried out using the Siemens HELX Evolution ACUSON™ S2000 ultrasound using 9L4 linear array transducer at 8 mHz frequency and Virtual Touch™ software.
MCP 2, 3, 4 and 5 of the dominant hand were scanned with joints resting at 20 degrees of flexion. We did not use a stand‐off pad. The dorsal aspect of the joint was imaged in three planes; longitudinal midline (DLM), longitudinal radial (30° radial offset from midline, DLR) and longitudinal ulnar (30% ulnar offset from midline, DLU). The palmar aspect of each joint was scanned in the longitudinal midline (PLM) plane only.
A SW‐EUS image was obtained at each location and at the time of scanning the sonographer chose the point of maximum SWV and recorded the value. GSUS synovial thickening and PDUS flow was graded on a 0–3 scale as described previously by Wakefield et al.1, 12 All images were stored for subsequent descriptive analysis. An illustration of patient positioning, probe locations and a SW‐EUS colour image is presented in Figure 2.
Figure 2.
Shear‐Wave Elastographic Ultrasound Set‐up Including Probe Locations and Colour Scale Image of a MCP Joint in a Patient with RA.
Two blinded clinicians subsequently scored each of the stored SW‐EUS images independently. GSUS images were used to help identify the synovial boundary when the SW‐EUS colour scheme obscured the anatomical landmarks. Due to difficulties in accurately assessing the synovial boundary for palmar images, only dorsal locations were included. A total of 168 images were included in the SW‐EUS data set comprising DLR, DLM, DLU locations for MCPs 2, 3, 4 and 5 across 14 patients.
A qualitative assessment of each image was made with respect to the seven parameters listed below. The two clinicians reviewed ten random SW‐EUS and GSUS images to calibrate scoring before commencing the blinded assessment. Average and minimum SWV results were averaged by patient to allow comparison of results between the RA and control cohorts.
Average synovial SWV according to colour scale (1–5): 1 = blue, 2 = aqua, 3 = green, 4 = yellow, 5 = red
Minimum synovial SWV according to colour scale (1–5): 1 = blue, 2 = aqua, 3 = green, 4 = yellow, 5 = red
Heterogeneity of synovial SWV colour pattern (1–3): 1 = homogenous, 2 = mixed, 3 = heterogeneous
SWV in synovium compared with bone (1–3): 1 = Slower in synovium, 2 = similar, 3 = faster in synovium
SWV in synovium compared with adjacent soft tissue (1–3): 1 = Slower in synovium, 2 = similar, 3 = faster in synovium
Longitudinal location of maximum and minimum SWV within synovium (1–3): 1 = proximal, 2 = mid‐joint, 3 = distal
Depth of maximum and minimum SWV within synovium (1–2): 1 = superficial, 2 = deep
Statistical analysis was performed using SPSS version 22. A two‐tailed independent samples t‐test was used to compare means with a P value less than 0.05 considered significant. Pearson's correlation coefficient was used to correlate SWV against disease activity markers, and intra‐ and interobserver reliability was assessed using intraclass correlation coefficients (ICC).
Ethics approval was obtained from the South East Sydney Local Health District Human Research Ethics Committee.
Results
Patient characteristics
The mean age of participants was 60 years, and 50% were female. Comorbidities were similar between patients with RA and controls. All patients with RA were taking disease modifying anti rheumatic therapy with seven taking methotrexate, two leflunomide, five TNF inhibitors and two prednisone. Mean time since diagnosis was 10.3 years. Seven of nine patients with RA had a positive CCP or RF with mean CCP of 125 units/mL and RF of 203 international units/mL. Details are presented in Table 1.
Table 1.
Patient characteristics
| RA, n = 9 (range) | Controls, n = 5 (range) | P | |
|---|---|---|---|
| Age, mean | 59.7 (40–79) | 59.8 (39–70) | 0.98 |
| Females, n | 5 | 2 | 1.00 |
| Prednisone dose in mg, mean | 1.3 (0–7) | 0 | 0.30 |
| BMI, mean | 27.3 (21.1–33.6) | 24.5 (23.0–25.7) | 0.16 |
| CCP in U/mL, mean | 125 (2–600) | N/A | N/A |
| RF in IU/mL, mean | 203 (9–1098) | N/A | N/A |
| Years since diagnosis | 10.3 (1–16) | N/A | N/A |
| CRP in mg/L, mean | 2.6 (1–5) | 2.2 (1–6) | 0.73 |
| ESR in mm/h, mean | 13.1 (5–29) | 7.0 (4–10) | 0.07 |
| Swollen joints (MCP 2–5), mean number | 1.56 (0–4) | 0 | 0.05 |
| Tender joints (MCP 2–5), mean number | 1.10 (0–4) | 0 | 0.19 |
| RAPID 3 score, mean | 2.6 (0–6.7) | 0 | 0.04 |
| HAQ‐DI score, mean | 0.46 (0–1.9) | 0 | 0.24 |
| DAS28‐CRP, mean | 3.3 (1.6–6.7) | 1.4 (1.2–1.7) | 0.03 |
| DAS28‐ESR, mean | 3.7 (2.4–7.4) | 1.4 (1.0–1.9) | 0.01 |
| Current smoker, n | 2 | 0 | 0.51 |
| Ex smoker, n | 4 | 0 | 0.22 |
| 2+ standard alcoholic drinks/day, n | 1 | 0 | 1.00 |
| Diabetes, n | 2 | 1 | 1.00 |
| Hypertension, n | 4 | 3 | 1.00 |
| Osteoarthritis (self reported), n | 5 | 0 | 0.09 |
| Crystal arthropathy, n | 3 | 0 | 0.26 |
| Methotrexate use, n | 7 | 0 | N/A |
| Biological DMARD use, n | 5 | 0 | N/A |
N/A = not available.
Clinical, serological and GSUS and PDUS results
The RA cohort had moderate disease activity with a mean DAS28‐ESR of 3.65. On average, 1.6/4 MCP joints were clinically swollen. Mean GSUS synovial thickness was 0.99/3, and PDUS flow was 0.17/3.
SW‐EUS results
The mean maximum SWV was 6.60 m per second (m/s) with a significantly lower result for patients with RA than controls (6.38 m/s vs. 6.99 m/s, P = 0.042). Patients with RA had lower mean maximum SWV than controls for all MCP joints and probe locations, but differences were not statistically significant (Table 2). Colour scale graded synovial SWV results were also lower for the patients with RA than controls. Average and minimum synovial SWV was 2.62/5 and 1.57/5 for patients with RA compared with 2.90/5 and 2.01/5 for controls (P value not significant).
Table 2.
GSUS, PDUS and SW‐EUS results
| Full cohort | RA | Controls | P (RA vs. control) | ||
|---|---|---|---|---|---|
| GSUS graded synovial thickness, mean (0–3) | All locations | 0.75 | 0.99 | 0.34 | 0.11 |
| Power Doppler flow, mean (0–3) | All locations | 0.11 | 0.17 | 0 | 0.48 |
| Maximum SWV, mean (m/s) | All locations | 6.60 | 6.38 | 6.99 | 0.04 |
| Average SWV (colour scale 1–5) | Dorsal locations | 2.72 | 2.62 | 2.90 | 0.37 |
| Minimum SWV (colour scale 1–5) | Dorsal locations | 1.73 | 1.57 | 2.01 | 0.16 |
| Maximum SWV by joint, mean (m/s) | MCP 2 | 6.46 | 6.25 | 6.85 | 0.24 |
| MCP 3 | 6.61 | 6.56 | 6.71 | 0.74 | |
| MCP 4 | 6.68 | 6.43 | 7.14 | 0.12 | |
| MCP 5 | 6.70 | 6.45 | 7.15 | 0.09 | |
| Maximum SWV by location on joint, mean (m/s) | Dorsal radial | 6.41 | 6.16 | 6.86 | 0.06 |
| Dorsal midline | 6.42 | 6.20 | 6.82 | 0.12 | |
| Dorsal ulnar | 6.21 | 5.95 | 6.66 | 0.15 | |
| Palmar midline | 7.35 | 7.21 | 7.61 | 0.22 |
The location of maximum SWV was most frequently deep and in the mid‐ to distal aspect of the joint. In contrast, minimum SWV was most frequently in the proximal to mid‐joint. Synovial SWV was slower or of similar velocity to bone in 98% cases. The colour pattern was most commonly observed to be heterogeneous or mixed heterogeneous/homogeneous (Table 3).
Table 3.
Descriptive analysis based on colour SW‐EUS images
| RA (108 images) | Control (60 images) | ||
|---|---|---|---|
| Heterogeneity of colour pattern | 1 – Homogeneous | 17 | 10 |
| 2 – Mixed | 47 | 52 | |
| 3 – Heterogeneous | 36 | 38 | |
| Average colour | 1 – Blue | 7 | 3 |
| 2 – Aqua | 40 | 27 | |
| 3 – Green | 36 | 47 | |
| 4 – Yellow | 17 | 23 | |
| 5 – Red | 0 | 0 | |
| Location of maximum SWV, depth | 1 – Superficial | 22 | 8 |
| 2 – Deep | 78 | 92 | |
| Location of maximum SWV, longitudinal | 1 – Proximal | 1 | 2 |
| 2 – Mid‐joint | 69 | 72 | |
| 3 – Distal | 31 | 27 | |
| Location of minimum SWV, depth | 1 – Superficial | 40 | 67 |
| 2 – Deep | 60 | 33 | |
| Location of minimum SWV, longitudinal | 1 – Proximal | 43 | 33 |
| 2 – Mid‐joint | 55 | 63 | |
| 3 – Distal | 3 | 5 | |
| SWV in synovium compared with bone | 1 – Slower in synovium | 63 | 70 |
| 2 – Similar | 35 | 28 | |
| 3 – Faster in synovium | 2 | 2 | |
| SWV in synovium compared with adjacent soft tissue | 1 – Slower in synovium | 46 | 38 |
| 2 – Similar | 42 | 48 | |
| 3 – Faster in synovium | 12 | 13 |
Negative Pearson's correlations were observed for mean maximum SWV against a range of established disease activity markers including GSUS synovial thickening (−0.57, P = 0.03) and ESR (−0.46 P = 0.095) as presented in Figure 3.
Figure 3.
Pearson Correlation Coefficient (PCC) Comparing Maximum SWV (m/s) with Disease Activity Markers.
ICC was 0.66 for intra‐observer quantitative SWV readings and 0.58 for quantitative interobserver readings. ICC for colour scale readings was 0.84 for average SWV (intra‐ and interobserver) and 0.89 for minimum SWV (intra and interobserver).
Discussion
This is the first ever pilot study of SW‐EUS in synovial tissue despite the technology having an established role in liver, thyroid and breast imaging.7 Higher SWV, indicating stiffer tissue, has been shown to correlate with increasing histological degree of hepatic fibrosis13, 14 and an increased chance of malignancy in breast and thyroid lesions.15, 16, 17, 18, 19 In musculoskeletal imaging, small studies have shown that softer Achilles tendons as detected by strain elastography correlate with histopathological features including loss of parallel collagen structure, loss of fibre integrity and capillary proliferation.10 Softer Achilles tendons have also been shown to correlate with ultrasound features including tendinous enlargement and erosions in ankylosing spondylitis (AS) patients and healthy volunteers.8, 9, 11 It is feasible that histopathological features distinguishing RA from OA such as cellular infiltrate and vascularity20 may influence tissue stiffness and thus be detectable using elastography.
Despite our small patient cohort, we found that maximum SWV was significantly lower in the RA cohort than controls. This suggests that patients with RA may have softer synovium than age‐ and sex‐matched people without inflammatory arthritis. Furthermore, there was a negative Pearson correlation between SWV and a number of disease activity markers indicating that softer synovium may equate with higher disease activity. As the Pearson correlation result was only statistically significant for GSUS synovial thickness, it needs to be interpreted with caution. The lack of statistically significant correlations with other disease activity markers may in part be due to relatively low disease activity in the RA cohort and our small sample size. It is also possible that stiffness, which is a previously unstudied synovial tissue property, may not correlate with the full range of existing established disease markers.
SW‐EUS proved to be a reliable technique with excellent intra‐ and interobserver reliability (ICC > 0.80) for colour scale ratings of average and minimum SWV. Moderate‐to‐good reliability was observed for quantitative SWV with ICC of 0.66 and 0.58 for intra‐ and inter‐observer readings. Factors contributing to the lower ICC for quantitative SWV may include sampling error as we recorded maximum SWV from a single point in the synovium, difficulty assessing synovium/cartilage and synovium/soft tissue interfaces and inadequate sonographer training and standardisation. Studies in liver, thyroid and breast imaging have used average SWV readings between 3 and 20 points to improve reliability.13, 15, 19
Strengths of this pilot study include positive findings in keeping with our original hypothesis, prospective recruitment of consecutive RA patients and blinding of sonographers and assessors. The major limitation is the small sample size. Another limitation is the relatively low disease activity amongst RA cohort which may have minimised the spread of SWV results. Our quantitative scoring system using a single point of maximum SWV proved only moderately reliable.
Moving forward we propose further study in three areas:
Validate our results using a larger cohort of RA patients with greater variability in disease activity, time from diagnosis (including newly diagnosed patients) and comparison to other imaging techniques including magnetic resonance imaging (MRI).
Improve reliability of quantitative SWV assessment by sampling a larger number of points in the synovium and improving sonographer training and standardisation. We would propose sampling five to ten points distributed through the synovium to arrive at an averaged quantitative SWV per scanning location. Sonographers may benefit from training in how best to visualise the synovial boundaries behind the elastography colour scale, choose appropriate points to record SWV and avoid readings from cartilage and bone interfaces.
Follow patients over time to assess if SW‐EUS can predict future disease activity, joint damage and response to treatment.
Conclusion
This is the first pilot study to assess SW‐EUS in synovial tissue. Despite the limitation of a small sample size, we found that patients with RA had significantly softer synovium than controls as quantified by lower mean maximum SWV. Furthermore, there was a negative Pearson correlation between SWV and disease activity markers (significant for GSUS synovial thickening only) suggesting that the degree of softness may indicate higher disease activity. SW‐EUS may have a role in the diagnosis and assessment of disease activity in RA and warrants further investigation.
Authorship declaration
The author listing conforms with the journal's authorship policy, and all authors are in agreement with the content of the submitted manuscript.
Disclosure
No financial support was received for this study.
Acknowledgements
The authors would like to acknowledge St George Private Radiology for the use of facilities and ultrasound equipment.
[Correction added on 24 May 2017: Authors' position titles were removed from the author byline.]
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