Value of imaging to guide interventional procedures in rheumatic and musculoskeletal diseases: a systematic literature review informing EULAR points to consider

Objectives: To summarise current data on the value of imaging to guide interventional procedures in patients with rheumatic and musculoskeletal disease (RMDs) informing an European Alliance of Associations for Rheumatology taskforce. Methods: A systematic literature review was conducted to retrieve prospective and retrospective studies published in English and comparing different (imaging) techniques, different settings and procedural protocols to guide interventions in patients with RMDs. MEDLINE, EMBASE, the Cochrane Library and Epistemonikos databases were searched through October 2021. Risk of bias (RoB) was assessed using the Cochrane RoB tool for randomised trials V.2 (ROB2), the RoB tool for Non-Randomised Studies of Interventions and the appraisal tool for cross-sectional studies. Results: Sixty-six studies were included (most with moderate/high RoB); 49 were randomised controlled trials, three prospective cohort studies and 14 retrospective studies. Fifty-one studies compared either one imaging technique with another imaging technique, or with palpation-guided interventions. Ultrasound (US) was most frequently studied (49/51), followed by fluoroscopy (10/51). Higher accuracy was found for US or fluoroscopy compared with palpation-guided interventions. Studies comparing different imaging techniques (12/51) did not endorse one specific method. Different settings/equipment for imaging-guided procedures (eg, automatic vs manual syringes) were investigated in three studies, reporting heterogeneous results. Fifteen studies compared different imaging-guided procedures (eg, intra-articular vs periarticular injections). Conclusion: Higher accuracy of needle positioning at joints and periarticular structures was seen in most studies when using imaging (especially US) guidance as compared with palpation-guided interventions with the limitation of heterogeneity of data and considerable RoB