University of Oulu

Holmström O, Linder N, Moilanen H, Suutala A, Nordling S, Ståhls A, et al. (2019) Detection of breast cancer lymph node metastases in frozen sections with a point-of-care low-cost microscope scanner. PLoS ONE 14(3): e0208366. https://doi.org/10.1371/journal.pone.0208366

Detection of breast cancer lymph node metastases in frozen sections with a point-of-care low-cost microscope scanner

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Author: Holmström, Oscar1; Linder, Nina1,2; Moilanen, Hannu3;
Organizations: 1Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
2Department of Women's and Children's Health, International Maternal and Child health, Uppsala University, Uppsala, Sweden
3Center of Microscopy and Nanotechnology, University of Oulu, Oulu, Finland
4Department of Pathology, University of Helsinki, Helsinki, Finland
5Helsinki University Hospital and HUSLAB Pathology laboratory, Helsinki, Finland
6Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 5.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019091127855
Language: English
Published: Public Library of Science, 2019
Publish Date: 2019-09-11
Description:

Abstract

Background: Detection of lymph node metastases is essential in breast cancer diagnostics and staging, affecting treatment and prognosis. Intraoperative microscopy analysis of sentinel lymph node frozen sections is standard for detection of axillary metastases but requires access to a pathologist for sample analysis. Remote analysis of digitized samples is an alternative solution but is limited by the requirement for high-end slide scanning equipment.

Objective: To determine whether the image quality achievable with a low-cost, miniature digital microscope scanner is sufficient for detection of metastases in breast cancer lymph node frozen sections.

Methods: Lymph node frozen sections from 79 breast cancer patients were digitized using a prototype miniature microscope scanner and a high-end slide scanner. Images were independently reviewed by two pathologists and results compared between devices with conventional light microscopy analysis as ground truth.

Results: Detection of metastases in the images acquired with the miniature scanner yielded an overall sensitivity of 91% and specificity of 99% and showed strong agreement when compared to light microscopy (k = 0.91). Strong agreement was also observed when results were compared to results from the high-end slide scanner (k = 0.94). A majority of discrepant cases were micrometastases and sections of which no anticytokeratin staining was available.

Conclusion: Accuracy of detection of metastatic cells in breast cancer sentinel lymph node frozen sections by visual analysis of samples digitized using low-cost, point-of-care microscopy is comparable to analysis of digital samples scanned using a high-end, whole slide scanner. This technique could potentially provide a workflow for digital diagnostics in resource-limited settings, facilitate sample analysis at the point-of-care and reduce the need for trained experts on-site during surgical procedures.

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Series: PLoS one
ISSN: 1932-6203
ISSN-E: 1932-6203
ISSN-L: 1932-6203
Volume: 14
Issue: 3
Article number: e0208366
DOI: 10.1371/journal.pone.0208366
OADOI: https://oadoi.org/10.1371/journal.pone.0208366
Type of Publication: A1 Journal article – refereed
Field of Science: 217 Medical engineering
3122 Cancers
Subjects:
Funding: This work was supported by grants from the Swedish Research Council, Sigrid Jusélius Foundation, Finska Läkaresällskapet, Biomedicum Foundation, Medicinska Understödsföreningen Liv och Hälsa rf and Tekes – the Finnish Funding Agency for Innovation and University of Helsinki. In addition, this study has received funding from the ‘European Advanced Translational Research Infrastructure in Medicine’ (EATRIS)/Academy of Finland.
Copyright information: © 2019 Holmström et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
  https://creativecommons.org/licenses/by/4.0/