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Dekeyser C, Hautekeete M, Cambron M, Van Pesch V, Patti F, Kuhle J, Khoury S, Lechner Scott J, Gerlach O, Lugaresi A, Maimone D, Surcinelli A, Grammond P, Kalincik T, Habek M, Willekens B, Macdonell R, Lalive P, Csepany T, Butzkueven H, Boz C, Tomassini V, Foschi M, Sánchez-Menoyo JL, Altintas A, Mrabet S, Iuliano G, Sa MJ, Alroughani R, Karabudak R, Aguera-Morales E, Gray O, de Gans K, van der Walt A, McCombe PA, Deri N, Garber J, Al-Asmi A, Skibina O, Duquette P, Cartechini E, Spitaleri D, Gouider R, Soysal A, Van Hijfte L, Slee M, Amato MP, Buzzard K, Laureys G. Routine CSF parameters as predictors of disease course in multiple sclerosis: an MSBase cohort study. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-333307. [PMID: 38569872 DOI: 10.1136/jnnp-2023-333307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND It remains unclear whether routine cerebrospinal fluid (CSF) parameters can serve as predictors of multiple sclerosis (MS) disease course. METHODS This large-scale cohort study included persons with MS with CSF data documented in the MSBase registry. CSF parameters to predict time to reach confirmed Expanded Disability Status Scale (EDSS) scores 4, 6 and 7 and annualised relapse rate in the first 2 years after diagnosis (ARR2) were assessed using (cox) regression analysis. RESULTS In total, 11 245 participants were included of which 93.7% (n=10 533) were persons with relapsing-remitting MS (RRMS). In RRMS, the presence of CSF oligoclonal bands (OCBs) was associated with shorter time to disability milestones EDSS 4 (adjusted HR=1.272 (95% CI, 1.089 to 1.485), p=0.002), EDSS 6 (HR=1.314 (95% CI, 1.062 to 1.626), p=0.012) and EDSS 7 (HR=1.686 (95% CI, 1.111 to 2.558), p=0.014). On the other hand, the presence of CSF pleocytosis (≥5 cells/µL) increased time to moderate disability (EDSS 4) in RRMS (HR=0.774 (95% CI, 0.632 to 0.948), p=0.013). None of the CSF variables were associated with time to disability milestones in persons with primary progressive MS (PPMS). The presence of CSF pleocytosis increased ARR2 in RRMS (adjusted R2=0.036, p=0.015). CONCLUSIONS In RRMS, the presence of CSF OCBs predicts shorter time to disability milestones, whereas CSF pleocytosis could be protective. This could however not be found in PPMS. CSF pleocytosis is associated with short-term inflammatory disease activity in RRMS. CSF analysis provides prognostic information which could aid in clinical and therapeutic decision-making.
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Affiliation(s)
| | | | - Melissa Cambron
- Neurology, Sint-Jan Bruges Hospital, Bruges, Belgium
- University of Ghent, Ghent, Belgium
| | - Vincent Van Pesch
- Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
- Université Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium
| | - Francesco Patti
- Neuroscience, University of Catania Department of Surgical and Medical Sciences and Advanced Technologies 'G.F. Ingrassia', Catania, Italy
- Multiple Sclerosis Unit, AOU Policlinico G Rodolico-San Marco, Catania, Italy
| | - Jens Kuhle
- Neurology, University Hospital Basel, Basel, Switzerland
- Biomedicine and Clinical Research, Multiple Sclerosis Centre and Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), Basel, Switzerland
| | - Samia Khoury
- Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon
| | - Jeanette Lechner Scott
- Hunter Medical Research Institute, The University of Newcastle, Newcastle, New South Wales, Australia
- Hunter New England Health, John Hunter Hospital, New Lambton Heights, New South Wales, Australia
| | - Oliver Gerlach
- Neurology, Zuyderland Medical Centre, Sittard-Geleen, The Netherlands
- Neurology, Universiteit Maastricht School for Mental Health and Neuroscience, Maastricht, The Netherlands
| | - Alessandra Lugaresi
- UOSI Riabilitazione Sclerosi Multipla, IRCCS Istituto Delle Scienze Neurologiche di Bologna, Bologna, Italy
- Dipartimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy
| | - Davide Maimone
- Centro Sclerosi Multipla, UOC Neurologia, Azienda Ospedaliera Cannizzaro, Catania, Italy
| | - Andrea Surcinelli
- Department of Neuroscience, MS Center, S Maria delle Croci Hospital, Ravenna, Italy
| | - Pierre Grammond
- CISSS Chaudière-Appalaches Research Center, Levis, Quebec, Canada
| | - Tomas Kalincik
- Department of Medicine, University of Melbourne, Melbourne, Victoria, Australia
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Mario Habek
- University Hospital Centre Zagreb Department of Neurology, Zagreb, Croatia
- University of Zagreb School of Medicine, Zagreb, Zagreb, Croatia
| | - Barbara Willekens
- Neurology, Universitair Ziekenhuis Antwerpen, Edegem, Belgium
- Laboratory of Experimental Hematology, Universiteit Antwerpen Faculteit geneeskunde en gezondheidswetenschappen, Wilrijk, Belgium
| | | | - Patrice Lalive
- Clinical Neurosciences, Division of Neurology, Unit of Neuroimmunology, Geneva University Hospitals Department of Medicine, Geneve, Switzerland
| | - Tunde Csepany
- Department of Neurology, University of Debrecen, Debrecen, Hungary
| | - Helmut Butzkueven
- Department of Neuroscience, Monash University Central Clinical School, Melbourne, Victoria, Australia
- Neurology, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Cavit Boz
- Neurology, Karadeniz Technical University, Medical Faculty, Trabzon, Turkey
| | - Valentina Tomassini
- Istituto di Tecnologie Avanzate Biomediche (ITAB), Dipartimento di Neuroscienze e Imaging e Scienze Cliniche; Centro Sclerosi Multipla, Clinica Neurologica, Ospedale SS Annunziata, Università degli Studi Gabriele d'Annunzio Chieti Pescara, Chieti, Italy
- University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Matteo Foschi
- Department of Neuroscience, MS Center, Neurology Unit, S. Maria delle Croci Hospital, Ravenna, Italy
- Department of Biotechnological and Applied Clinical Sciences (DISCAB), University of L'Aquila, L'Aquila, Italy
| | - José Luis Sánchez-Menoyo
- Neurology, Galdakao-Usansolo University Hospital, Osakidetza-Basque Health Service, Galdakao, Spain
- Biocruces Bizkaia Health Research Institute, Barakaldo, Spain
| | - Ayse Altintas
- Neurology, Koc University School of Medicine and Koc University Research Center for Translational Medicine (KUTTAM), Istanbul, Turkey
| | - Saloua Mrabet
- Neurology, Razi University Hospital, Clinical Investigation Centre Neurosciences and Mental Health, Tunis, Tunisia
- University of Tunis El Manar Faculty of Medicine of Tunis, Tunis, Tunisia
| | | | - Maria Jose Sa
- Neurology, Centro Hospitalar de São João, Porto, Portugal
- Fernando Pessoa University Faculty of Health Sciences, Porto, Portugal
| | | | - Rana Karabudak
- Neurological Sciences, Yeditepe Universitesi, Istanbul, Turkey
- Neuroimmunology, Koşuyolu Hospitals, Istanbul, Turkey
| | - Eduardo Aguera-Morales
- Neurology, Hospital Universitario Reina Sofia, Cordoba, Spain
- GC28 Neuroplasticity and Oxidative Stress, IMIBIC, Cordoba, Spain
| | - Orla Gray
- South Eastern HSC Trust, Belfast, UK
| | | | - Anneke van der Walt
- Monash University Central Clinical School, Melbourne, Victoria, Australia
- Alfred Hospital, Melbourne, Victoria, Australia
| | - Pamela A McCombe
- UQCCR, Royal Brisbane and Woman's Hospital Health Service District, Herston, Queensland, Australia
- The University of Queensland, Brisbane, Queensland, Australia
| | - Norma Deri
- Hospital Fernandez, Buenos Aires, Argentina
| | - Justin Garber
- Westmead Hospital, Sydney, New South Wales, Australia
| | - Abdullah Al-Asmi
- Sultan Qaboos University College of Medicine and Health Science, Muscat, Muscat Governorate, Oman
| | - Olga Skibina
- Neurosciences, The Alfred, Melbourne, Victoria, Australia
- Neurology, Box Hill Hospital, Box Hill, Victoria, Australia
| | | | | | - Daniele Spitaleri
- Neurology, Azienda Ospedaliera di Rilievo Nazionale e di Alta Specialità San Giuseppe Moscati Neurologia e Stroke Unit, Avellino, Italy
| | - Riadh Gouider
- University of Tunis El Manar Faculty of Medicine of Tunis, Tunis, Tunisia
- Department of Neurology, Razi Hospital, Faculty of Medicine of Tunis, University Tunis el Manar, Tunisia, Manouba, Tunisia
| | - Aysun Soysal
- Bakirkoy Education and Research Hospital for Psychiatric and Neurological Diseases, Istanbul, Turkey
| | | | - Mark Slee
- Neurology, Flinders Medical Centre, Adelaide, South Australia, Australia
| | - Maria Pia Amato
- Department NEUROFARBA, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Katherine Buzzard
- Department of Neurology, Box Hill Hospital, Melbourne, Victoria, Australia
- Eastern Health Clinical School, Monash University, Box Hill, Victoria, Australia
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Frater JL. Neonatal cerebrospinal fluid cytology: Preanalytical and analytical phase considerations. J Family Med Prim Care 2024; 13:1134-1135. [PMID: 38736836 PMCID: PMC11086794 DOI: 10.4103/jfmpc.jfmpc_1519_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/22/2023] [Indexed: 05/14/2024] Open
Affiliation(s)
- John L. Frater
- Department of Pathology and Immunology, Washington University, St Louis, MO, USA
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3
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Frater JL. Blast identification in cerebrospinal fluid specimens from patients with acute myeloid leukemia: laboratory perspectives. Leuk Lymphoma 2024; 65:136-137. [PMID: 37921237 DOI: 10.1080/10428194.2023.2273749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 10/15/2023] [Indexed: 11/04/2023]
Affiliation(s)
- John L Frater
- Department of Pathology and Immunology, Washington University, St Louis, MO, USA
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4
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Vlad B, Reichen I, Neidhart S, Hilty M, Lekaditi D, Heuer C, Eisele A, Ziegler M, Reindl M, Lutterotti A, Regeniter A, Jelcic I. Basic CSF parameters and MRZ reaction help in differentiating MOG antibody-associated autoimmune disease versus multiple sclerosis. Front Immunol 2023; 14:1237149. [PMID: 37744325 PMCID: PMC10516557 DOI: 10.3389/fimmu.2023.1237149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/22/2023] [Indexed: 09/26/2023] Open
Abstract
Background Myelin oligodendrocyte glycoprotein antibody-associated autoimmune disease (MOGAD) is a rare monophasic or relapsing inflammatory demyelinating disease of the central nervous system (CNS) and can mimic multiple sclerosis (MS). The variable availability of live cell-based MOG-antibody assays and difficulties in interpreting low-positive antibody titers can complicate diagnosis. Literature on cerebrospinal fluid (CSF) profiles in MOGAD versus MS, one of the most common differential diagnoses, is scarce. We here analyzed the value of basic CSF parameters to i) distinguish different clinical MOGAD manifestations and ii) differentiate MOGAD from MS. Methods This is retrospective, single-center analysis of clinical and laboratory data of 30 adult MOGAD patients and 189 adult patients with relapsing-remitting multiple sclerosis. Basic CSF parameters included CSF white cell count (WCC) and differentiation, CSF/serum albumin ratio (QAlb), intrathecal production of immunoglobulins, CSF-restricted oligoclonal bands (OCB) and MRZ reaction, defined as intrathecal production of IgG reactive against at least 2 of the 3 viruses measles (M), rubella (R) and varicella zoster virus (Z). Results MOGAD patients with myelitis were more likely to have a pleocytosis, a QAlb elevation and a higher WCC than those with optic neuritis, and, after review and combined analysis of our and published cases, they also showed a higher frequency of intrathecal IgM synthesis. Compared to MS, MOGAD patients had significantly more frequently neutrophils in CSF and WCC>30/µl, QAlb>10×10-3, as well as higher mean QAlb values, but significantly less frequently CSF plasma cells and CSF-restricted OCB. A positive MRZ reaction was present in 35.4% of MS patients but absent in all MOGAD patients. Despite these associations, the only CSF parameters with relevant positive likelihood ratios (PLR) indicating MOGAD were QAlb>10×10-3 (PLR 12.60) and absence of CSF-restricted OCB (PLR 14.32), whereas the only relevant negative likelihood ratio (NLR) was absence of positive MRZ reaction (NLR 0.00). Conclusion Basic CSF parameters vary considerably in different clinical phenotypes of MOGAD, but QAlb>10×10-3 and absence of CSF-restricted OCB are highly useful to differentiate MOGAD from MS. A positive MRZ reaction is confirmed as the strongest CSF rule-out parameter in MOGAD and could be useful to complement the recently proposed diagnostic criteria.
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Affiliation(s)
- Benjamin Vlad
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Ina Reichen
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Stephan Neidhart
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Marc Hilty
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Dimitra Lekaditi
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Christine Heuer
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Amanda Eisele
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Mario Ziegler
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Markus Reindl
- Clinical Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Andreas Lutterotti
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Axel Regeniter
- Infectious Disease Serology and Immunology, Medica Medizinische Laboratorien Dr. F. Kaeppeli AG, Zurich, Switzerland
| | - Ilijas Jelcic
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
- Neuroimmunology and Multiple Sclerosis Research Section, Department of Neurology, University Hospital Zurich, Zurich, Switzerland
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5
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Schweizer L, Seegerer P, Kim HY, Saitenmacher R, Muench A, Barnick L, Osterloh A, Dittmayer C, Jödicke R, Pehl D, Reinhardt A, Ruprecht K, Stenzel W, Wefers AK, Harter PN, Schüller U, Heppner FL, Alber M, Müller KR, Klauschen F. Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights. Neuropathol Appl Neurobiol 2023; 49:e12866. [PMID: 36519297 DOI: 10.1111/nan.12866] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/14/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
AIM Analysis of cerebrospinal fluid (CSF) is essential for diagnostic workup of patients with neurological diseases and includes differential cell typing. The current gold standard is based on microscopic examination by specialised technicians and neuropathologists, which is time-consuming, labour-intensive and subjective. METHODS We, therefore, developed an image analysis approach based on expert annotations of 123,181 digitised CSF objects from 78 patients corresponding to 15 clinically relevant categories and trained a multiclass convolutional neural network (CNN). RESULTS The CNN classified the 15 categories with high accuracy (mean AUC 97.3%). By using explainable artificial intelligence (XAI), we demonstrate that the CNN identified meaningful cellular substructures in CSF cells recapitulating human pattern recognition. Based on the evaluation of 511 cells selected from 12 different CSF samples, we validated the CNN by comparing it with seven board-certified neuropathologists blinded for clinical information. Inter-rater agreement between the CNN and the ground truth was non-inferior (Krippendorff's alpha 0.79) compared with the agreement of seven human raters and the ground truth (mean Krippendorff's alpha 0.72, range 0.56-0.81). The CNN assigned the correct diagnostic label (inflammatory, haemorrhagic or neoplastic) in 10 out of 11 clinical samples, compared with 7-11 out of 11 by human raters. CONCLUSIONS Our approach provides the basis to overcome current limitations in automated cell classification for routine diagnostics and demonstrates how a visual explanation framework can connect machine decision-making with cell properties and thus provide a novel versatile and quantitative method for investigating CSF manifestations of various neurological diseases.
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Affiliation(s)
- Leonille Schweizer
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp Seegerer
- Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.,Aignostics GmbH, Berlin, Germany
| | - Hee-Yeong Kim
- Systems Medicine of Infectious Disease, Robert Koch Institute, Berlin, Germany
| | - René Saitenmacher
- Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany
| | - Amos Muench
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Liane Barnick
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Anja Osterloh
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Carsten Dittmayer
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Ruben Jödicke
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Debora Pehl
- Department of Pathology, Vivantes Hospitals Berlin, Berlin, Germany
| | | | - Klemens Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Werner Stenzel
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Annika K Wefers
- Institute of NeuropathologyUniversity Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Patrick N Harter
- Neurological Institute (Edinger Institute), Goethe University, Frankfurt am Main, Germany.,Frankfurt Cancer Institute, Goethe University, Frankfurt am Main, Germany.,German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ulrich Schüller
- Institute of NeuropathologyUniversity Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Pediatric Hematology and Oncology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Research Institute Children's Cancer Center Hamburg, Hamburg, Germany
| | - Frank L Heppner
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Berlin, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Cluster of Excellence, NeuroCure, Berlin, Germany.,German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
| | - Maximilian Alber
- Aignostics GmbH, Berlin, Germany.,Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Klaus-Robert Müller
- Machine-Learning Group, Department of Software Engineering and Theoretical Computer Science, Technische Universität Berlin, Berlin, Germany.,Max Planck Institut für Informatik, Saarbrücken, Germany.,Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany.,Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Frederick Klauschen
- Berlin Institute for the Foundations of Learning and Data (BIFOLD), Berlin, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Institute of Pathology, Ludwig-Maximilians-Universität München, Munich, Germany
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6
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Frater JL, Shirai CL, Brestoff JR. Technological features of blast identification in the cerebrospinal fluid: A systematic review of flow cytometry and laboratory haematology methods. Int J Lab Hematol 2022; 44 Suppl 1:45-53. [PMID: 35785436 PMCID: PMC9463081 DOI: 10.1111/ijlh.13869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Accepted: 04/22/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Involvement of the central nervous system (CNS) by acute leukemias (ALs) has important implications for risk stratification and disease outcome. The clinical laboratory plays an essential role in assessment of cerebrospinal fluid (CSF) specimens from patients with ALs at initial diagnosis, at the end of treatment, and when CNS involvement is clinically suspected. The two challenges for the laboratory are 1) to accurately provide a cell count of the CSF and 2) to successfully distinguish blasts from other cell types. These tasks are classically performed using manual techniques, which suffer from suboptimal turnaround time, imprecision, and inconsistent inter-operator performance. Technological innovations in flow cytometry and hematology analyzer technology have provided useful complements and/or alternatives to conventional manual techniques. AIMS We performed a PRISMA-compliant systematic review to address the medical literature regarding the development and current state of the art of CSF blast identification using flow cytometry and laboratory hematology technologies. MATERIALS AND METHODS We searched the peer reviewed medical literature using MEDLINE (PubMed interface), Web of Science, and Embase using the keywords "CSF or cerebrospinal" AND "blasts(s)". RESULTS 108 articles were suitable for inclusion in our systematic review. These articles covered 1) clinical rationale for CSF blast identification; 2) morphology-based CSF blast identification; 3) the role of flow cytometry; 4) use of hematology analyzers for CSF blast identification; and 5) quality issues. 9 /L, which is much lower than the original machine count and platelet transfusion was warranted. DISCUSSION 1) Clinical laboratory testing plays a central role in risk stratification and clinical management of patients with acute leukemias, most clearly in pediatric ALs; 2) studies focused on other patient populations, including adults and patients with AML are less prevalent in the literature; 3) improvements in instrumentation may provide better performance for the classification of CSF specimens. CONCLUSION Current challenges include: 1) more precisely characterizing the natural history of AL involvement of the CNS, 2) improvements in automated cell count technology of low cellularity specimens, 3) defining the role of flow MRD testing of CSF specimens and 4) improved recognition of specimen quality by clinicians and laboratory personnel.
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Affiliation(s)
- John L Frater
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Cara Lunn Shirai
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Jonathan R Brestoff
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, USA
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7
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Otto F, Harrer C, Pilz G, Wipfler P, Harrer A. Role and Relevance of Cerebrospinal Fluid Cells in Diagnostics and Research: State-of-the-Art and Underutilized Opportunities. Diagnostics (Basel) 2021; 12:diagnostics12010079. [PMID: 35054246 PMCID: PMC8774636 DOI: 10.3390/diagnostics12010079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 12/07/2021] [Accepted: 12/28/2021] [Indexed: 01/15/2023] Open
Abstract
Cerebrospinal fluid (CSF) has recently experienced a revival in diagnostics and research. However, little progress has been made regarding CSF cell analysis. For almost a century, CSF cell count and cytomorphological examination have been central diagnostic parameters, with CSF pleocytosis as a hallmark finding of neuroinflammation and cytology offering valuable clues regarding infectious, autoimmune, and malignant aetiologies. A great deal of information, however, remains unattended as modern immune phenotyping technologies have not yet been broadly incorporated into routine CSF analysis. This is a serious deficit considering the central role of CSF cells as effectors in central nervous system (CNS) immune defence and autoimmune CNS processes, and the diagnostic challenges posed by clinically overlapping infectious and immune-mediated CNS diseases. Here, we summarize historical, specimen-intrinsic, methodological, and technical issues determining the state-of-the-art diagnostics of CSF cells and outline future perspectives for this underutilized window into meningeal and CNS immunity.
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Affiliation(s)
- Ferdinand Otto
- Department of Neurology, Paracelsus Medical University, Christian-Doppler-Klinik, 5020 Salzburg, Austria; (F.O.); (C.H.); (G.P.); (P.W.)
| | - Christine Harrer
- Department of Neurology, Paracelsus Medical University, Christian-Doppler-Klinik, 5020 Salzburg, Austria; (F.O.); (C.H.); (G.P.); (P.W.)
| | - Georg Pilz
- Department of Neurology, Paracelsus Medical University, Christian-Doppler-Klinik, 5020 Salzburg, Austria; (F.O.); (C.H.); (G.P.); (P.W.)
| | - Peter Wipfler
- Department of Neurology, Paracelsus Medical University, Christian-Doppler-Klinik, 5020 Salzburg, Austria; (F.O.); (C.H.); (G.P.); (P.W.)
| | - Andrea Harrer
- Department of Neurology, Paracelsus Medical University, Christian-Doppler-Klinik, 5020 Salzburg, Austria; (F.O.); (C.H.); (G.P.); (P.W.)
- Department of Dermatology and Allergology, Paracelsus Medical University, Landeskrankenhaus, 5020 Salzburg, Austria
- Correspondence:
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