Enhancing detection of central nervous system involvement in multiple myeloma: A novel multidimensional dot‐plot based analysis for flow cytometry

Central nervous system (CNS) involvement in multiple myeloma (MM) is a rare but severe complication with a poor prognosis. The identification of malignant plasma cells in cerebrospinal fluid (CSF) is essential for early diagnosis and intervention. However, the sensitivity of traditional diagnostic methods like cytology is low, especially in samples with low-cell counts. This study aimed to develop a multidimensional radar dot-plot analysis using Kaluza software to enhance the sensitivity and specificity of flow cytometry for detecting abnormal plasma cells in CSF. One hundred and twenty-five CSF samples were sent for flow cytometric testing to investigate the central nervous system involvement of MM. Finally, 89 samples from 40 patients were included in our study. Multicolor flow cytometry was performed using an 8-color labeling method, and radar dot-plot analysis was developed using diagnostic bone marrow samples to distinguish normal plasma cells, abnormal plasma cells, and cellular debris. The sensitivity of the novel method was evaluated by diluting myeloma bone marrow cells in pooled CSF samples to simulate low cell counts. Of the 125 CSF specimens, 16 samples from 4 patients showed abnormal plasma cells using both conventional and multidimensional flow cytometry analysis. Discordant results were found in 32 samples (25%), where conventional analysis suggested the presence of abnormal cells, but these were ruled out by multidimensional analysis. Sensitivity testing showed that the multidimensional dot-plot method outperforms conventional two-dimensional dot-plot analysis, as the radar dot plot can be used to identify abnormal cells in samples diluted to 5 WBC/μL, where the cell count of abnormal plasma cells is < 1 cell/μL. Our results showed that the new radar dot-plot analysis can increase the sensitivity and specificity of flow cytometry in MM for the detection of CNS involvement, even in low-cell-count CSF samples, regardless of whether the sample was obtained in a tube containing special reagent or not (TransFix/EDTA CSF Sample Storage tubes). This approach improves diagnostic accuracy, reduces the number of false positive cases caused by antibodies adhering to cell debris, and provides a reliable tool for assessing neurological complications in MM. Further validation is needed in a larger number of cases and testing of the method on different antibody panels.

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Publication Details

Journal
Cytometry Part B Clinical Cytometry
Published
2025-07-01
DOI
https://doi.org/10.1002/cyto.b.22245
Citations
1
Primary Topic
Multiple Myeloma Research and Treatments
Type
article
Field-Weighted Citation Impact
1.77
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article

Enhancing detection of central nervous system involvement in multiple myeloma: A novel multidimensional dot‐plot based analysis for flow cytometry

Zsuzsanna Hevessy, Bettina Kárai, László Váróczy, László Rejtő et al.
1 citations
Cytometry Part B Clinical Cytometry
Multiple Myeloma Research and Treatments
1.77
article

Enhancing detection of central nervous system involvement in multiple myeloma: A novel multidimensional dot‐plot based analysis for flow cytometry

Zsuzsanna Hevessy, Bettina Kárai, László Váróczy, László Rejtő, Bettina Palicskó, Luca Janovák
article en
1 citations

Abstract

Central nervous system (CNS) involvement in multiple myeloma (MM) is a rare but severe complication with a poor prognosis. The identification of malignant plasma cells in cerebrospinal fluid (CSF) is essential for early diagnosis and intervention. However, the sensitivity of traditional diagnostic methods like cytology is low, especially in samples with low-cell counts. This study aimed to develop a multidimensional radar dot-plot analysis using Kaluza software to enhance the sensitivity and specificity of flow cytometry for detecting abnormal plasma cells in CSF. One hundred and twenty-five CSF samples were sent for flow cytometric testing to investigate the central nervous system involvement of MM. Finally, 89 samples from 40 patients were included in our study. Multicolor flow cytometry was performed using an 8-color labeling method, and radar dot-plot analysis was developed using diagnostic bone marrow samples to distinguish normal plasma cells, abnormal plasma cells, and cellular debris. The sensitivity of the novel method was evaluated by diluting myeloma bone marrow cells in pooled CSF samples to simulate low cell counts. Of the 125 CSF specimens, 16 samples from 4 patients showed abnormal plasma cells using both conventional and multidimensional flow cytometry analysis. Discordant results were found in 32 samples (25%), where conventional analysis suggested the presence of abnormal cells, but these were ruled out by multidimensional analysis. Sensitivity testing showed that the multidimensional dot-plot method outperforms conventional two-dimensional dot-plot analysis, as the radar dot plot can be used to identify abnormal cells in samples diluted to 5 WBC/μL, where the cell count of abnormal plasma cells is < 1 cell/μL. Our results showed that the new radar dot-plot analysis can increase the sensitivity and specificity of flow cytometry in MM for the detection of CNS involvement, even in low-cell-count CSF samples, regardless of whether the sample was obtained in a tube containing special reagent or not (TransFix/EDTA CSF Sample Storage tubes). This approach improves diagnostic accuracy, reduces the number of false positive cases caused by antibodies adhering to cell debris, and provides a reliable tool for assessing neurological complications in MM. Further validation is needed in a larger number of cases and testing of the method on different antibody panels.

Cytometry Part B Clinical CytometryVol. 108(4)
University of Debrecen (HU), University of Nyíregyháza (HU)
No poverty
Openalex Percentile: Top 15%
Multiple Myeloma Research and Treatments
1.77
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