PLoS ONE (Jan 2019)

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

  • Oscar Holmström,
  • Nina Linder,
  • Hannu Moilanen,
  • Antti Suutala,
  • Stig Nordling,
  • Anders Ståhls,
  • Mikael Lundin,
  • Vinod Diwan,
  • Johan Lundin

DOI
https://doi.org/10.1371/journal.pone.0208366
Journal volume & issue
Vol. 14, no. 3
p. e0208366

Abstract

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BackgroundDetection 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.ObjectiveTo 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.MethodsLymph 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.ResultsDetection 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.ConclusionAccuracy 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.