ArticleCancer medicine2023
Ex vivo NMR metabolomics approach using cerebrospinal fluid for the diagnosis of primary CNS lymphoma: Correlation with MR imaging characteristics.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Decoding Cerebrospinal Fluid: Integrative Metabolomics Across Multiple Platforms.Methods and protocols · 2026Article
- Use of Nuclear Magnetic Resonance (NMR) to Study Cancer Metabolism.Advances in experimental medicine and biology · 2026Review
- NMR-Based Metabolomic Profiling for Brain Cancer Diagnosis and Treatment Guidance.Metabolites · 2025Review
- Ex vivo NMR metabolomics approach using cerebrospinal fluid for the diagnosis of primary CNS lymphoma: Correlation with MR imaging characteristics.Cancer medicine · 2023Article
- High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers.Frontiers in molecular biosciences · 2023Article
- Cerebrospinal fluid metabolic markers predict prognosis behavior of primary central nervous system lymphoma with high-dose methotrexate-based chemotherapeutic treatment.Neuro-oncology advancesArticle
- Predicting prognosis outcomes of primary central nervous system lymphoma with high-dose methotrexate-based chemotherapeutic treatment using lipidomics.Neuro-oncology advancesArticle
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Authors and funding
6 authors.
Funding
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Abstract
purposePrimary central nervous system lymphoma (PCNSL) is an uncommon extranodal non-Hodgkin's lymphoma. Here, the feasibility of nuclear magnetic resonance (NMR) metabolomics for the diagnosis and prognosis prediction of PCNSL, as well as its correlation with magnetic resonance imaging (MRI) characteristics, was assessed. PATIENTS AND
methodsCerebrospinal fluid (CSF) samples from PCNSL and normal groups (n = 41 for each) were obtained along with MRI data including pre- and postcontrast as well as T1-, T2-, and diffusion-weighted imaging for the treatment-naïve PCNSL patients (n = 24). The CSF samples were analyzed using nuclear magnetic resonance (NMR).
resultsThe CSF NMR metabolomic exhibited clear differences with a diagnostic sensitivity of 100% and a specificity of 97.6%. The citrate level of the leptomeningeal enhancement (LE) (+) group was significantly lower than that of the LE (-) group (p = 0.018). In addition, the MRI apparent diffusion coefficient (ADC) value of the tumor was positively correlated with the glucose level (p = 0.025). However, none of the marker metabolites were significant prognosis predictors in univariate analysis.
conclusionsIn conclusion, the NMR metabolomics could be helpful to diagnose PCNSL, but not for the prognosis, and MRI features (LE or ADC) can reflect the metabolic profiles of PCNSL.
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