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

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 anal...

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Bibliographic Details
Published in:PloS one Vol. 14; no. 3; p. e0208366
Main Authors: Holmström, Oscar, Linder, Nina, Moilanen, Hannu, Suutala, Antti, Nordling, Stig, Ståhls, Anders, Lundin, Mikael, Diwan, Vinod, Lundin, Johan
Format: Journal Article
Language:English
Published: United States Public Library of Science 19.03.2019
Public Library of Science (PLoS)
Subjects:
Biology and Life Sciences
Biopsy
Breast cancer
Breast Neoplasms - pathology
Cancer
Cancer diagnosis
Cancer metastasis
Cancer patients
Cancer surgery
Care and treatment
Cost analysis
Diagnosis
Digital imaging
Digitization
Engineering and Technology
Female
Frozen Sections
Frozen sections (Histology)
Ground truth
Health sciences
Histopathology
Hospitals
Humans
Image acquisition
Image detection
Image quality
Laboratories
Light microscopy
Low cost
Lymph node biopsy
Lymph nodes
Lymph Nodes - pathology
Lymphatic Metastasis - diagnostic imaging
Lymphatic Metastasis - pathology
Lymphatic system
Maternal & child health
Medical diagnosis
Medical imaging
Medical prognosis
Medicine
Medicine and Health Sciences
Metastases
Metastasis
Methods
Microscopy
Microscopy - economics
Microscopy - instrumentation
Miniaturization
Onsite
Pathology
Point-of-Care Systems - economics
Prognosis
Public health
Research and Analysis Methods
Retrospective Studies
Scanners
Sensitivity and Specificity
Smartphones
Studies
Surgery
Womens health
Workflow
Workflow software
Sweden
Finland
ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Description
Summary: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. 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. 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. 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. 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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Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: Johan Lundin and Mikael Lundin are founders and co-owners of Fimmic Oy, Helsinki, Finland. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0208366