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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
OBJECTIVES: To 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. METHODS: Systematic literature review (SLR) (2017–202...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450079/ https://www.ncbi.nlm.nih.gov/pubmed/37620113 http://dx.doi.org/10.1136/rmdopen-2023-003379 |
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author | Bosch, Philipp Bond, Milena Dejaco, Christian Ponte, Cristina Mackie, Sarah Louise Falzon, Louise Schmidt, Wolfgang A Ramiro, Sofia |
author_facet | Bosch, Philipp Bond, Milena Dejaco, Christian Ponte, Cristina Mackie, Sarah Louise Falzon, Louise Schmidt, Wolfgang A Ramiro, Sofia |
author_sort | Bosch, Philipp |
collection | PubMed |
description | OBJECTIVES: To 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. METHODS: Systematic 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. RESULTS: The 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. CONCLUSION: Ultrasound, 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. |
format | Online Article Text |
id | pubmed-10450079 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-104500792023-08-26 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 Bosch, Philipp Bond, Milena Dejaco, Christian Ponte, Cristina Mackie, Sarah Louise Falzon, Louise Schmidt, Wolfgang A Ramiro, Sofia RMD Open Imaging OBJECTIVES: To 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. METHODS: Systematic 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. RESULTS: The 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. CONCLUSION: Ultrasound, 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. BMJ Publishing Group 2023-08-24 /pmc/articles/PMC10450079/ /pubmed/37620113 http://dx.doi.org/10.1136/rmdopen-2023-003379 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Imaging Bosch, Philipp Bond, Milena Dejaco, Christian Ponte, Cristina Mackie, Sarah Louise Falzon, Louise Schmidt, Wolfgang A Ramiro, Sofia 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10450079/ https://www.ncbi.nlm.nih.gov/pubmed/37620113 http://dx.doi.org/10.1136/rmdopen-2023-003379 |
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