Literature DB >> 29222848

Digital image analysis agrees with visual estimates of adult bone marrow trephine biopsy cellularity.

A S Hagiya1, A Etman2, I N Siddiqi1, S Cen3, G R Matcuk3, R K Brynes1, M E Salama2.   

Abstract

INTRODUCTION: Evaluation of cellularity is an essential component of bone marrow trephine biopsy examination. The standard practice is to report the results as visual estimates (VE). Digital image analysis (DIA) offers the promise of more objective measurements of cellularity.
METHODS: Adult bone marrow trephine biopsy sections were assessed for cellularity by VE. Sections were scanned using an Aperio AT2 Scanscope and analyzed using a Cytonuclear (version 1.4) algorithm on halo software. Intraclass correlation (ICC) was used to assess relatedness between VE and DIA, and between MRI and DIA for a separate subset of patients. Trephine biopsy sections from a subset of patients with bone marrow biopsies uninvolved by malignancy were assessed for age-related changes.
RESULTS: Interobserver VE agreement was good to excellent. The ICC value was 0.81 for VE and DIA, and 0.50 for MRI and DIA. Linearity studies showed no statistically significant trend for age-related changes in cellularity in our cohort (r = -.29, P = .06).
CONCLUSIONS: Agreement was good between VE and DIA. It may be possible to use DIA or VE to measure cellularity in the appropriate clinical scenario. The limited sample size precludes similar determinations for MRI calculations. Further studies examining healthy donors are necessary before making definitive conclusions regarding age and cellularity.
© 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  bone marrow; cellularity; digital image analysis

Mesh:

Year:  2017        PMID: 29222848     DOI: 10.1111/ijlh.12768

Source DB:  PubMed          Journal:  Int J Lab Hematol        ISSN: 1751-5521            Impact factor:   2.877


  6 in total

1.  Automated recognition of glomerular lesions in the kidneys of mice by using deep learning.

Authors:  Airi Akatsuka; Yasushi Horai; Airi Akatsuka
Journal:  J Pathol Inform       Date:  2022-07-28

2.  Tumor Cell Subtypes Based on the Intracellular Hormonal Activity in KCNJ5-Mutated Aldosterone-Producing Adenoma.

Authors:  Yuto Yamazaki; Kei Omata; Yuta Tezuka; Yoshikiyo Ono; Ryo Morimoto; Yuzu Adachi; Kazue Ise; Yasuhiro Nakamura; Celso E Gomez-Sanchez; Yukiko Shibahara; Takumi Kitamoto; Tetsuo Nishikawa; Sadayoshi Ito; Fumitoshi Satoh; Hironobu Sasano
Journal:  Hypertension       Date:  2018-09       Impact factor: 10.190

Review 3.  Application of Single-Cell Approaches to Study Myeloproliferative Neoplasm Biology.

Authors:  Daniel Royston; Adam J Mead; Bethan Psaila
Journal:  Hematol Oncol Clin North Am       Date:  2021-04       Impact factor: 3.722

4.  Intraoperative fluorescence imaging with aminolevulinic acid detects grossly occult breast cancer: a phase II randomized controlled trial.

Authors:  Kathryn Ottolino-Perry; Anam Shahid; Stephanie DeLuca; Viktor Son; Mayleen Sukhram; Fannong Meng; Zhihui Amy Liu; Sara Rapic; Nayana Thalanki Anantha; Shirley C Wang; Emilie Chamma; Christopher Gibson; Philip J Medeiros; Safa Majeed; Ashley Chu; Olivia Wignall; Alessandra Pizzolato; Cheryl F Rosen; Liis Lindvere Teene; Danielle Starr-Dunham; Iris Kulbatski; Tony Panzarella; Susan J Done; Alexandra M Easson; Wey L Leong; Ralph S DaCosta
Journal:  Breast Cancer Res       Date:  2021-07-12       Impact factor: 6.466

Review 5.  Artificial Intelligence and Digital Microscopy Applications in Diagnostic Hematopathology.

Authors:  Hanadi El Achi; Joseph D Khoury
Journal:  Cancers (Basel)       Date:  2020-03-26       Impact factor: 6.639

6.  Quantification of histopathological findings using a novel image analysis platform.

Authors:  Yasushi Horai; Mao Mizukawa; Hironobu Nishina; Satomi Nishikawa; Yuko Ono; Kana Takemoto; Nobuyuki Baba
Journal:  J Toxicol Pathol       Date:  2019-08-11       Impact factor: 1.628

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.