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Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
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Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
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Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations

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Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations
Journal Article

Imaging in diagnosis, monitoring and outcome prediction of large vessel vasculitis: a systematic literature review and meta-analysis informing the 2023 update of the EULAR recommendations

2023
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Overview
ObjectivesTo update the evidence on imaging for diagnosis, monitoring and outcome prediction in large vessel vasculitis (LVV) to inform the 2023 update of the European Alliance of Associations for Rheumatology recommendations on imaging in LVV.MethodsSystematic literature review (SLR) (2017–2022) including prospective cohort and cross-sectional studies (>20 participants) on diagnostic, monitoring, outcome prediction and technical aspects of LVV imaging. Diagnostic accuracy data were meta-analysed in combination with data from an earlier (2017) SLR.ResultsThe update retrieved 38 studies, giving a total of 81 studies when combined with the 2017 SLR. For giant cell arteritis (GCA), and taking clinical diagnosis as a reference standard, low risk of bias (RoB) studies yielded pooled sensitivities and specificities (95% CI) of 88% (82% to 92%) and 96% (95% CI 86% to 99%) for ultrasound (n=8 studies), 81% (95% CI 71% to 89%) and 98% (95% CI 89% to 100%) for MRI (n=3) and 76% (95% CI 67% to 83%) and 95% (95% CI 71% to 99%) for fluorodeoxyglucose positron emission tomography (FDG-PET, n=4), respectively. Compared with studies assessing cranial arteries only, low RoB studies with ultrasound assessing both cranial and extracranial arteries revealed a higher sensitivity (93% (95% CI 88% to 96%) vs 80% (95% CI 71% to 87%)) with comparable specificity (94% (95% CI 83% to 98%) vs 97% (95% CI 71% to 100%)). No new studies on diagnostic imaging for Takayasu arteritis (TAK) were found. Some monitoring studies in GCA or TAK reported associations of imaging with clinical signs of inflammation. No evidence was found to determine whether imaging severity might predict worse clinical outcomes.ConclusionUltrasound, MRI and FDG-PET revealed a good performance for the diagnosis of GCA. Cranial and extracranial vascular ultrasound had a higher pooled sensitivity with similar specificity compared with limited cranial ultrasound.