Evidence map›Paper›PMID 38846278›Full record

ArticleQuantitative imaging in medicine and surgery2024

Assessment of the sacroiliac joint in patients with axial spondyloarthritis via three-dimensional ultrashort echo time magnetic resonance imaging.

Cui Ren, Qiao Zhu, Qing Li, Stefan Sommer, Xianchang Zhang, Huishu Yuan

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Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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5 · Who and what money

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6 authors.

Cui Ren *Department of Radiology, Peking University Third Hospital, Beijing, China.
Qiao Zhu *Department of Radiology, Peking University Third Hospital, Beijing, China.
Qing LiMR Collaborations, Siemens Healthineers Ltd., Shanghai, China.
Stefan SommerSiemens Healthcare, Zurich, Switzerland.
Xianchang ZhangMR Collaborations, Siemens Healthineers Ltd., Beijing, China.
Huishu YuanDepartment of Radiology, Peking University Third Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bone erosion in the sacroiliac joint (SIJ) is highly specific for the diagnosis of axial spondyloarthritis (axSpA) and may indicate early disease progression. The 3D ultrashort echo time (3D-UTE) technique excels in providing clear contrast between the articular cartilage and the bone cortex interface. Additionally, it is emerging as a promising quantitative tool for detecting early cartilage changes. Therefore, this study aimed to evaluate the diagnostic performance of 3D-UTE sequences in identifying bone erosion in the SIJ of patients with axSpA and to clarify the potential of cartilage T2* values as a quantitative biomarker for axSpA. Methods: This prospective study employed convenience and consecutive sampling methods to recruit patients diagnosed with axSpA in Peking University Third Hospital who met the Assessment of Spondyloarthritis International Society (ASAS) criteria and also an equal number of healthy volunteers. After providing informed consent, all participants underwent 3D-UTE sequences and conventional T2* mapping of the SIJs. Two radiologists separately interpreted the bone erosion of each SIJ on 3D-UTE sequences. Erosion detection of SIJs via computed tomography (CT) served as the standard of reference. The T2* values of the cartilage were measured and compared, and the diagnostic efficacy of the T2* value for axSpA diagnosis was evaluated. Results: A total of 32 patients and 32 healthy volunteers were included. The 3D-UTE sequence, as separately assessed by two reviewers in terms of its ability to detect erosions, exhibited a notable level of accuracy. For the two reviewers, the respective diagnostic sensitivities were 94.7% and 92.9%, the specificities were 97.4% and 96.5%, positive predictive values were 96.7% and 95.4%, the negative predictive values were 95.9% and 94.5%, the accuracies were 96.2% and 94.9%, and the areas under the curve (AUCs) were 96.1% and 94.7%. For the detection of erosions, the interreader κ value was 0.949. The T2* values of the SIJ cartilage were significantly higher in patients with axSpA than in healthy volunteers. The intraobserver intraclass correlation coefficients (ICCs) for T2* measurements ranged between 80.5% and 82.2%. Meanwhile, the interobserver ICCs for UTE-T2* and gradient echo T2* measurements were 81.5% and 80.8%, respectively. The AUCs of the UTE-T2* values for discriminating patients with axSpA from the healthy volunteers of the two readers were 73.3% and 71.6%, respectively. Conclusions: 3D-UTE sequences can be used as a reliable morphological imaging technique for detecting bone erosion in the SIJ. Additionally, UTE-T2* values of the cartilage may offer a quantitative method for identifying patients with axSpA.

Indexed as

Axial spondyloarthritis (axSpA)cartilagesacroiliac joint (SIJ)T2* relaxation timeultrashort echo time (UTE)

Identifiers

PMID38846278
PMCPMC11151252

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.