Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Cagol, A; Cortese, R; Barakovic, M; Schaedelin, S; Ruberte, E; Absinta, M; Barkhof, F; Calabrese, M; Castellaro, M; Ciccarelli, O; Cocozza, S; De, Stefano, N; Enzinger, C; Filippi, M; Jurynczyk, M; Maggi, P; Mahmoudi, N; Messina, S; Montalban, X; Palace, J; Pontillo, G; Pröbstel, AK; Rocca, MA; Ropele, S; Rovira, À; Schoonheim, MM; Sowa, P; Strijbis, E; Wattjes, MP; Sormani, MP; Kappos, L; Granziera, C, , MAGNIMS, Study, Group.
Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis.
JAMA Neurol. 2024; 81(2):143-153
Doi: 10.1001/jamaneurol.2023.4737
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PubMed
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- Co-Autor*innen der Med Uni Graz
- Enzinger Christian
- Ropele Stefan
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- Abstract:
- IMPORTANCE: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. OBJECTIVE: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). EXPOSURES: MS/CIS vs non-MS conditions. MAIN OUTCOMES AND MEASURES: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. RESULTS: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. CONCLUSIONS AND RELEVANCE: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.
- Find related publications in this database (using NLM MeSH Indexing)
- Humans - administration & dosage
- Female - administration & dosage
- Adult - administration & dosage
- Middle Aged - administration & dosage
- Male - administration & dosage
- Multiple Sclerosis - diagnosis
- Retrospective Studies - administration & dosage
- Cross-Sectional Studies - administration & dosage
- Brain - pathology
- Veins - pathology
- Demyelinating Diseases - pathology
- Magnetic Resonance Imaging - methods