Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by polyarticular inflammation and pannus formation, leading to joint destruction and severe disability. Precise evaluation of synovial inflammation and bony deformity is very important for the management of RA, especially for early detection and evaluation of disease activity during follow-up. Serum Midkine, C reactive protein, and 28 joints-erythrocyte sedimentation rate score can be used as an inflammatory marker for detection of RA activity. The richness of pannus blood flow signals can reflect the severity of RA disease, so as to evaluate the development of RA disease. In tradition, power Doppler imaging (PDI) is used to detect the synovial vascularity, but because of the interference of tissue movement, it is not very sensitive to microvascular patterns and low blood flow velocity. Superb microvascular imaging (SMI) is a novel ultrasonic technology, which uses adaptive principle to display low-speed blood flow signal and several studies had suggested that SMI, as a promising alternative, can evaluate joint lesions in RA more sensitively comparable to PDI. However, the results of these studies have been contradictory and the sample sizes were small. Therefore, we performed the present meta-analysis to compare SMI with PDI for evaluating joint lesion scores in RA based on high quality clinical cohort or case control studies.
2.1 PROSPERO registration
This protocol has been reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol statement guidelines, and it has been registered in the INPLASY202060089.
2.2 Ethics and dissemination
No ethical approval is required in this study, because it will only analyze published data. It is supposed to be published on a peer reviewed journal or presented in a conference meeting.
2.3 Literature search
We searched Medline (via PubMed), Web of Science, Cochrane Library, Embase, and CBM databases without restrictions of language and publication status. The search strategy sample for PubMed is “Rheumatoid arthritis[Title/Abstract] AND superb microvascular imaging[Title/Abstract] AND power Doppler[Title/Abstract] (“2015/03/01”[PDat]: “2020/04/01”[PDat]).” We also reviewed references from eligible articles for additional relevant studies.
2.4 Selection criteria
- (1) Participants. Any patients who fulfilled the 2011 American College of Rheumatology/European League Against Rheumatism diagnosis criteria for RA will be included in spite of race, nationality, and sex.
- (2) Intervention and comparison. All patients were assessed with SMI and PDI.
- (3) Outcomes. The primary outcomes include a semi-quantitative scoring system, through which synovial vascularity intensity was evaluated by means of both PDI and SMI.
- (4) Type of studies. This study will only include high quality clinical cohort or case control studies that compare SMI with PDI for evaluating joint lesion scores in RA.
2.5 Data extraction and quality assessment
Two investigators will independently extract the data from all included studies. The following data were extracted from each included research: year of article, the first author's surname, sample size, examination position, mean of disease activity score of 28 joints, Instrument. The quality of selected studies was independently evaluated according to a tool for the quality assessment of methodological index for nonrandomized studies (MINORS). The MINORS criteria included 12 assessment items. Each of these items was scored as “yes” (2), “no” (0), or “unclear” (1). MINORS score ranged from 0 to 24; and score ≥17 indicate a good quality. Any disagreements between 2 investigators will be solved through discussion or consultation by a 3rd investigator
2.6 Statistical analysis
The STATA version 15.1 software (Stata Corporation, College Station, TX) was used for meta-analysis. We calculated the pooled summary odds ratio (OR) and its 95% confidence interval (CI). The Cochran Q-statistic and I2 test were used to evaluate potential heterogeneity between studies. If Q test shows a P < .05 or I2 test exhibits > 50% which indicates significant heterogeneity, the random-effect model was conducted, or else the fixed-effects model was used. In order to evaluate the influence of single study on the overall estimate, sensitivity analysis was performed. We also performed sub group and meta-regression analyses to investigate potential sources of heterogeneity. The Begg funnel plot and Egger test were applied to assess the publication bias.
3.1 Characteristics of included studies
Initially, the searched keywords identified 55 articles. We reviewed the titles and abstracts of all articles and excluded 14 articles; full texts and data integrity were also reviewed and 30 were further excluded. Finally, 11 studies (Table 1) that met all inclusion criteria were included in this meta-analysis. Figure 1 showed the selection process of eligible articles. A total of 4342 joints were assessed through both SMI and PDI. MINORS scores of all included studies were more than or equal to 17.
3.2 Quantitative data synthesis
Sensitivity analysis was carried out, and none of them caused obvious interference to the results of this meta-analysis (Fig. 2). The pooled summary OR was 2.12 (95% CI = 1.80–2.51) with statistical significance (z = 8.82, P < .01), which indicated SMI was more sensitive for evaluating joint lesions in RA comparable to PDI (Fig. 3). In subgroup analyses, the results revealed that SMI exhibited more sensitive performance in different subgroups (Table 2, Fig. 4). Meta-regression analysis results confirmed that no factor could explain potential sources of heterogeneity (Table 3). The funnel plots indicated little evidence of significant publication bias (Fig. 5), and Egger test confirmed this (t = 0.55, P = .598).
PDI has high sensitivity to the examination of low velocity blood flow without angle dependence, and performs a good consistency with contrast enhanced ultrasound in the display of pannus in hyperplastic synovium of RA patients. SMI technology, based on the high-resolution Doppler technology, can identify the noise generated by blood flow and tissue movement, separate low-speed blood flow signals from filtered clutter signals, and display the real blood flow information.[18,19] However, the relationship between SMI and PDI remains unclear. At present, there is a lack of multi center and large sample research in this aspect. In this meta-analysis, we compared SMI and PDI in detecting pannus synovius. The pooled summary OR was 2.12 with statistical significance, which strongly suggest that SMI ultrasound is more sensitive than conventional PDI in detecting synovitis in RA patients.
However, several limitations still existed. First, the included studies were mainly performed in China, which may lead to selection bias due to ethnicity factors. Although existing systematic reviews have suggested that the inclusion of articles published in Chinese mainly would not affect the overall effect direction, the exclusion of publications in other languages may reduce the precision of the summary effect estimates. Second, many of the studies did not address whether the grades of SMI and PDI interacted with blinding. Empirical evidence suggests that lack of blinding tends to cause overestimation of the treatment effect. This indicates that even if bias is introduced by the lack of blinding, the true OR would be even smaller than the results generated by this meta-analysis. Thirdly, obvious heterogeneity may be due to differences sample size, examination position, mean of disease activity score of 28 joints. Furthermore, meta-analyses are retrospective studies, which may lead to subject selection bias. In future studies, large, multicenter, prospective, double-blind control studies are required to validate these findings.
In conclusion, our meta-analysis suggests that SMI is more sensitive than PDI in detecting pannus synovius in RA patients. However, due to the limitations mentioned above, further detailed studies are still required to confirm our findings.
Conceptualization: Cong Wang.
Data curation: MingXin Lin.
Methodology: Cong Wang.
Writing – original draft: MingXin Lin.
Writing – review & editing: Cong Wang.
. Forien M, Ottaviani S. Ultrasound and follow-up of rheumatoid arthritis
. Joint Bone Spine 2017;84:5316.
. Mourgues C, Blanquet M, Gerbaud L, et al. Economic analysis of a nurse-led programme for comorbidities management of rheumatoid arthritis
patients. Joint Bone Spine 2018;85:5736.
. Abdel Ghafar MT, Abdel Haleem S, Shahba A, et al. Diagnostic value of the serum Midkine in patients with rheumatoid arthritis
. J Investig Med 2020;68:3744.
. Rhodes LA, Tan AL, Tanner SF, et al. Regional variation and differential response to therapy for knee synovitis adjacent to the cartilage-pannus junction and suprapatellar pouch in inflammatory arthritis: implications for pathogenesis and treatment. Arthritis Rheum 2004;50:242832.
. Dale J, Purves D, McConnachie A, et al. ightening up? Impact of musculoskeletal ultrasound disease activity assessment on early rheumatoid arthritis
patients treated using a treat to target strategy. Arthritis Care Res 2014;66:1926.
. Lee GY, Kim S, Choi ST, et al. The superb microvascular imaging
is more sensitive than conventional power Doppler imaging
in detection of active synovitis in patients with rheumatoid arthritis
. Clin Rheumatol 2019;38:261320.
. Peters JL, Sutton AJ, Jones DR, et al. Comparison of two methods to detect publication bias in meta-analysis. JAMA 2006;295:67680.
. Peng JJ, Lu HX, Yao JD, et al. Study on the application of ultramicro flow imaging and power Doppler ultrasound in the clinical remission period of rheumatoid arthritis
. J Clin Ultrasound Med 2020;22:1720.
. Liu HY, Du JW, Wang H, et al. Comparison of three ultrasonic examination methods for pannus of knee joint in RA patients. Chin J Ultrasound Med 2019;35:668.
. Qi QH, Wang JK, Zhou YY, et al. Assessment of active rheumatoid arthritis
by color microvascular imaging. Chin J Clin Imaging 2018;29:8936.
. Du JW, Liu HY, Wang H, et al. Study on the detection effect of SMI on pannus microflow of knee joint. Hebei Med J 2019;25:31921.
. Yu XL, Wu JB, Li Z, et al. Application value of color mode ultramicro flow imaging technology in active rheumatoid arthritis
wrist joint. Chin J Clin Imaging 2018;29:5235.
. Li L, Ye YQ, Zhang JS, et al. The application value of microvscular imaging in the wrist joint of patients with rheumatoid arthritis
. Chin J Ultrasound Med 2016;32:10046.
. Sun H, Lu RG, Li S, et al. Application of ultra micro angiography in pannus of rheumatoid arthritis
. Chin J Med Ultrasound 2016;13:2547.
. Liu F, Zhu JA, Wei XY, et al. Evaluation of subclinical arthritis of fingers in patients with rheumatoid arthritis
by superb microvscular imaging. Chin Med Imaging Technol 2016;32:6636.
. Wei XY, Zhu JA, Chen Z, et al. Application value of microvascular imaging in rheumatoid arthritis
. Chin J Ultrasound Med 2015;31:81820.
. Yu XL, Li Z, Ren M, et al. Superb microvascular imaging
(SMI) for evaluating hand joint lesions in patients with rheumatoid arthritis
in clinical remission. Rheumatol Int 2018;38:188590.
. Jin XL, Li FJ, Wang H, et al. Application of ultrasound microvascular imaging in pannus of rheumatoid arthritis
. Chin Clin Res 2019;32:17036.
. Hata T, Koyanagi A, Yamanishi T, et al. Superb microvascular imaging
with Doppler luminance using an 18-MHz probe to visualize fetal intra-abdominal blood vessels and organ microvasculature. J Perinat Med 2020;48:1848.
. Morrison A, Polisena J, Husereau D, et al. The effect of english-language restriction on systematic review-based meta-analyses: a systematic review of empirical studies. Int J Technol Assess Health Care 2012;28:13844.
. Savović J, Jones HE, Altman DG, et al. Influence of reported study design characteristics on intervention effect estimates from randomized, controlled trials. Ann Intern Med 2012;157:42938.