Literature DB >> 29858232

Automated enumeration of lymphoid and plasma cells in bone marrow to establish normal reference ranges.

James Liang1,2, Jacques A J Malherbe1,3, Kathryn A Fuller1,4, Bob Mirzai1,4, Carly George1,5, Tina L Carter4,5, Catherine H Cole1,3,4,5, Belinda B Guo1, Katie Meehan1, Wendy N Erber1,3,4.   

Abstract

AIMS: The number of precursor and mature lymphoid cells and plasma cells in normal bone marrow trephine (BMT) biopsies throughout the human lifespan is unknown. Reference ranges have been established from aspirated marrow, but due to haemodilution errors, these do not accurately reflect the native marrow milieu. We aimed to define age-specific, normal reference ranges for lymphoid and plasma cells in BMT biopsy specimens using a combined immunophenotyping and digital enumeration approach.
METHODS: Morphologically normal BMT biopsy specimens (n=483) were obtained from patients aged 1 month to 90 years of age. Immunohistochemistry was performed to identify lymphoid progenitors , T-lymphocytes (CD3), B-lymphocytes (CD20) and plasma cells (CD138 and MUM1). Positive cells were counted using digital enumeration software, and the percent positivity for each antigen was determined per case. Mean values were generated for specific age groups, and age-defined reference ranges were determined for each antigen using normalised data.
RESULTS: A mean of 16 609 cells (range: 7210-34 097) were counted per biopsy. Infant marrows showed a predominance of immature lymphoid progenitors and B cells. With increasing age, an increase in mean T cell and plasma cell numbers were observed. The results showed the same trends to flow cytometry references for aspirate material although the absolute values differed.
CONCLUSIONS: Combined immunohistochemistry and automated enumeration gives an accurate, reproducible number of antigen-positive cells and has generated normal reference ranges for these cell types in BMT biopsies. The method and ranges we have established have the potential to be applied in routine clinical practice. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  bone marrow trephines; digital pathology; immunohistochemistry; lymphocytes

Mesh:

Year:  2018        PMID: 29858232     DOI: 10.1136/jclinpath-2018-205168

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  2 in total

1.  Deep Learning Accurately Quantifies Plasma Cell Percentages on CD138-Stained Bone Marrow Samples.

Authors:  Fred Fu; Angela Guenther; Ali Sakhdari; Trevor D McKee; Daniel Xia
Journal:  J Pathol Inform       Date:  2022-02-05

2.  Prolonged Impairment of Immunological Memory After Anti-CD20 Treatment in Pediatric Idiopathic Nephrotic Syndrome.

Authors:  Manuela Colucci; Rita Carsetti; Jessica Serafinelli; Salvatore Rocca; Laura Massella; Antonio Gargiulo; Anna Lo Russo; Claudia Capponi; Nicola Cotugno; Ottavia Porzio; Andrea Onetti Muda; Paolo Palma; Francesco Emma; Marina Vivarelli
Journal:  Front Immunol       Date:  2019-07-16       Impact factor: 7.561

  2 in total

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