Sysmex XN-Based Evaluation of the Diagnostic Performance of High-Fluorescent Cells From CSF as a Supportive Diagnostic Criterion in Neurological Diseases.

Benedict Schwarz, Christopher Hardt, Katharina Friedrich, Monika Prpic, Anja Osterloh, Frank L Heppner, Klemens Ruprecht, Kai Kappert, Amir Jahic
{"title":"Sysmex XN-Based Evaluation of the Diagnostic Performance of High-Fluorescent Cells From CSF as a Supportive Diagnostic Criterion in Neurological Diseases.","authors":"Benedict Schwarz, Christopher Hardt, Katharina Friedrich, Monika Prpic, Anja Osterloh, Frank L Heppner, Klemens Ruprecht, Kai Kappert, Amir Jahic","doi":"10.1111/ijlh.14466","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Automatic cytological analysis of cerebrospinal fluid (CSF) by Sysmex XN-Series represents a convenient laboratory platform for quantitative examination of nucleated CSF cells (monomorphonuclear (MN), polymorphonuclear (PMN), high-fluorescent (HF)). HF cells (HFC), a research laboratory parameter so far, seem to be associated with certain clinical patterns. Hence, we aimed to determine the diagnostic HFC value for different clinical categories in neurological settings.</p><p><strong>Methods: </strong>Morphological classification of automatically detected HFC was carried out using manual light microscopy. Automatic method precision for cell differentiation was evaluated in comparison. In 284 cases, multiple correlation strategies and mathematical disease modellings enabled an explorative analysis of HFC suitability for case stratification into the categories Hemorrhage, Inflammation, Neoplasia, other, and unknown.</p><p><strong>Results: </strong>Manual microscopic reevaluation revealed plasma cells, macrophages, and malignant cells being HFC correlates in 80% of automatically detected HFC. Method correlation for automatic and manual CSF cell differentiation approaches was 95%, yielding a negative bias of 4.3% for MN and positive bias of 0.4% and 3.9% for PMN and HF, respectively. When HFC were used as a \"stand-alone\" predicting tool, diagnostic accuracy, specificity, and sensitivity depended on the clinical condition, ranging from > 0.5 up to > 0.7 for Hemorrhage, Inflammation, and Neoplasia. However, multiparametric correlation analyses combining laboratory CSF diagnostics and mathematical methods defined HFC as a relevant laboratory parameter for adequate clinical case stratification. With an expected random distribution of 25% for four clinical categories, almost 70% of cases were correctly classified when the HFC-based mathematical algorithm was applied.</p><p><strong>Conclusion: </strong>HFC has significant diagnostic and/or predictive value for neurological diseases.</p>","PeriodicalId":94050,"journal":{"name":"International journal of laboratory hematology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of laboratory hematology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/ijlh.14466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Automatic cytological analysis of cerebrospinal fluid (CSF) by Sysmex XN-Series represents a convenient laboratory platform for quantitative examination of nucleated CSF cells (monomorphonuclear (MN), polymorphonuclear (PMN), high-fluorescent (HF)). HF cells (HFC), a research laboratory parameter so far, seem to be associated with certain clinical patterns. Hence, we aimed to determine the diagnostic HFC value for different clinical categories in neurological settings.

Methods: Morphological classification of automatically detected HFC was carried out using manual light microscopy. Automatic method precision for cell differentiation was evaluated in comparison. In 284 cases, multiple correlation strategies and mathematical disease modellings enabled an explorative analysis of HFC suitability for case stratification into the categories Hemorrhage, Inflammation, Neoplasia, other, and unknown.

Results: Manual microscopic reevaluation revealed plasma cells, macrophages, and malignant cells being HFC correlates in 80% of automatically detected HFC. Method correlation for automatic and manual CSF cell differentiation approaches was 95%, yielding a negative bias of 4.3% for MN and positive bias of 0.4% and 3.9% for PMN and HF, respectively. When HFC were used as a "stand-alone" predicting tool, diagnostic accuracy, specificity, and sensitivity depended on the clinical condition, ranging from > 0.5 up to > 0.7 for Hemorrhage, Inflammation, and Neoplasia. However, multiparametric correlation analyses combining laboratory CSF diagnostics and mathematical methods defined HFC as a relevant laboratory parameter for adequate clinical case stratification. With an expected random distribution of 25% for four clinical categories, almost 70% of cases were correctly classified when the HFC-based mathematical algorithm was applied.

Conclusion: HFC has significant diagnostic and/or predictive value for neurological diseases.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Patient Moving Average for Continuous Real-Time QC; Real-World Application Illustrated. Sysmex XN-Based Evaluation of the Diagnostic Performance of High-Fluorescent Cells From CSF as a Supportive Diagnostic Criterion in Neurological Diseases. Mast Cell Blast Crisis in a Patient of Chronic Myeloid Leukemia With Concurrent BCR::ABL1 and RUNX1::RUNX1T1 Rearrangement or Should We Call It Myelomastocytic Leukemia? A Diagnostic Challenge With Nomenclature Dilemma. Germline Variants in Idiopathic Erythrocytosis Identified by Multigene Panel Sequencing. Towards Sensitive and Cost-Effective Chimerism Assays Using FABCASE: A Fast Approach for Estimating Assay Informativity.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1