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Home / Equine Research Bank / Sci Data / Inter-species cell detection – datasets on pulmonary h...
Scientific data2022; 9(1); 269; doi: 10.1038/s41597-022-01389-0

Inter-species cell detection – datasets on pulmonary hemosiderophages in equine, human and feline specimens.

Abstract: Pulmonary hemorrhage (P-Hem) occurs among multiple species and can have various causes. Cytology of bronchoalveolar lavage fluid (BALF) using a 5-tier scoring system of alveolar macrophages based on their hemosiderin content is considered the most sensitive diagnostic method. We introduce a novel, fully annotated multi-species P-Hem dataset, which consists of 74 cytology whole slide images (WSIs) with equine, feline and human samples. To create this high-quality and high-quantity dataset, we developed an annotation pipeline combining human expertise with deep learning and data visualisation techniques. We applied a deep learning-based object detection approach trained on 17 expertly annotated equine WSIs, to the remaining 39 equine, 12 human and 7 feline WSIs. The resulting annotations were semi-automatically screened for errors on multiple types of specialised annotation maps and finally reviewed by a trained pathologist. Our dataset contains a total of 297,383 hemosiderophages classified into five grades. It is one of the largest publicly available WSIs datasets with respect to the number of annotations, the scanned area and the number of species covered.
© 2022. The Author(s).
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Publication Date: 2022-06-03 PubMed ID: 35660753PubMed Central: PMC9166691DOI: 10.1038/s41597-022-01389-0Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research focuses on creating a multi-species dataset for detecting pulmonary hemorrhage, especially in equine, feline, and human species. This detection is based on the hemosiderin content in alveolar macrophages using a 5-tier scoring system.

Research Objective

  • The main objective of this study was to develop a well-curated multi-species dataset to detect pulmonary hemorrhage (P-Hem) in different species.
  • This was achieved by investigating 74 cytology whole slide images (WSIs) of equine, feline, and human samples using a five-tier scoring system of alveolar macrophages based on their hemosiderin content.

Methodology

  • In order to compile the dataset, an annotation pipeline was developed that combined human expertise with deep learning and data visualization techniques.
  • The deep-learning based object detection approach was trained on 17 expertly annotated equine WSIs.
  • This trained model was then utilized on the remaining 39 equine, 12 human and 7 feline WSIs.

Results

  • The semi-automated screening of these annotations was done for errors on multiple types of specialized annotation maps.
  • These results were then reviewed by a pathologist to confirm results accuracy.
  • The final dataset contained a total of 297,383 hemosiderophages classified into five grades.

Significance

  • This research led to one of the largest publicly available WSI datasets with respect to the number of annotations, the scanned area, and the number of species covered.
  • Such a dataset contributes to the understanding and detection of pulmonary hemorrhage in different species and aid in further research on pulmonary diseases.

Cite This Article

APA
Marzahl C, Hill J, Stayt J, Bienzle D, Welker L, Wilm F, Voigt J, Aubreville M, Maier A, Klopfleisch R, Breininger K, Bertram CA. (2022). Inter-species cell detection – datasets on pulmonary hemosiderophages in equine, human and feline specimens. Sci Data, 9(1), 269. https://doi.org/10.1038/s41597-022-01389-0

Publication

Scientific data
ISSN: 2052-4463
NlmUniqueID: 101640192
Country: England
Language: English
Volume: 9
Issue: 1
Pages: 269
PII: 269

Researcher Affiliations

Marzahl, Christian
  • Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. christian.marzahl@gmail.com.
  • Research and Development, EUROIMMUN Medizinische Labordiagnostika AG, Lübeck, Germany. christian.marzahl@gmail.com.
Hill, Jenny
  • VetPath Laboratory Services, Ascot, Western, Australia.
Stayt, Jason
  • VetPath Laboratory Services, Ascot, Western, Australia.
Bienzle, Dorothee
  • Department of Pathobiology, OntarioVeterinary College, University of Guelph, Guelph, ON, Canada.
Welker, Lutz
  • Cytology Laboratory, Lungen Clinic Grosshansdorf, Großhansdorf, Germany.
Wilm, Frauke
  • Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Voigt, Jörn
  • Research and Development, EUROIMMUN Medizinische Labordiagnostika AG, Lübeck, Germany.
Aubreville, Marc
  • Technische Hochschule Ingolstadt, Ingolstadt, Germany.
Maier, Andreas
  • Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Klopfleisch, Robert
  • Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany.
Breininger, Katharina
  • Pattern Recognition Lab, Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
  • Department of Artifical Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
Bertram, Christof A
  • Institute of Veterinary Pathology, Freie Universität Berlin, Berlin, Germany.
  • Institute of Pathology, University of Veterinary Medicine, Vienna, Austria.

MeSH Terms

  • Animals
  • Bronchoalveolar Lavage Fluid / cytology
  • Cats
  • Hemosiderin
  • Horses
  • Humans
  • Macrophages, Alveolar
  • Species Specificity

Conflict of Interest Statement

The authors declare no competing interests.

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Citations

This article has been cited 1 times.
  1. Bertram CA, Marzahl C, Bartel A, Stayt J, Bonsembiante F, Beeler-Marfisi J, Barton AK, Brocca G, Gelain ME, Gläsel A, Preez KD, Weiler K, Weissenbacher-Lang C, Breininger K, Aubreville M, Maier A, Klopfleisch R, Hill J. Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm.. Vet Pathol 2023 Jan;60(1):75-85.
    doi: 10.1177/03009858221137582pubmed: 36384369google scholar: lookup
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