Evidence map›Paper›PMID 35315258›Full record

ArticleJournal of biomedical optics2022

Multiresolution nondestructive 3D pathology of whole lymph nodes for breast cancer staging.

Lindsey A Barner, Adam K Glaser, Chenyi Mao, Etsuo A Susaki, Joshua C Vaughan, Suzanne M Dintzis, Jonathan T C Liu

Open access · greenAbstract read
In one paragraph

Article in Journal of biomedical optics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
0.9field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. An end-to-end workflow for non-destructive 3D pathology.bioRxiv : the preprint server for biology · 2023
    Article
  13. Review
  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Lindsey A BarnerUniversity of Washington, Department of Mechanical Engineering, Seattle, Washington, United States.
Adam K GlaserUniversity of Washington, Department of Mechanical Engineering, Seattle, Washington, United States.
Chenyi MaoUniversity of Washington, Department of Chemistry, Seattle, Washington, United States.
Etsuo A SusakiJuntendo University Graduate School of Medicine, Department of Biochemistry and Systems Biomedicine,, Japan.
Joshua C VaughanUniversity of Washington, Department of Chemistry, Seattle, Washington, United States.
Suzanne M DintzisUniversity of Washington School of Medicine, Department of Laboratory Medicine and Pathology, Seattl, United States.
Jonathan T C LiuUniversity of Washington, Department of Mechanical Engineering, Seattle, Washington, United States.
University of Washington · US

Funding

In vivo dual-axis confocal microscopy of 5-ALA-induced PpIX to guide low-grade glioma resectionsR01CA244170 · NCI · UNIVERSITY OF WASHINGTON · PI LIU, JONATHAN T.C., SANAI, NADER · 2020 to 2024
$2.8M
Instrumentation platform for 3D pathology with open-top light-sheet microscopyR01EB031002 · NIBIB · UNIVERSITY OF WASHINGTON · PI LIU, JONATHAN T.C. · 2021 to 2024
$1.9M
Light-sheet micro-aspiration microscopy for the isolation and analysis of rare tumor cells from intact clinical specimensR00CA240681 · NCI · ALLEN INSTITUTE · PI GLASER, ADAM K · 2021 to 2023
$745k
Light-sheet micro-aspiration microscopy for the isolation and analysis of rare tumor cells from intact clinical specimensK99CA240681 · NCI · UNIVERSITY OF WASHINGTON · PI GLASER, ADAM K · 2019 to 2020
$316k
NCI NIH HHS K99 CA240681NCI NIH HHS R00 CA240681NCI NIH HHS R01 CA244170NIBIB NIH HHS R01 EB031002
6 · The paper itself

Abstract

significanceFor breast cancer patients, the extent of regional lymph node (LN) metastasis influences the decision to remove all axillary LNs. Metastases are currently identified and classified with visual analysis of a few thin tissue sections with conventional histology that may underrepresent the extent of metastases.

aimWe sought to enable nondestructive three-dimensional (3D) pathology of human axillary LNs and to develop a practical workflow for LN staging with our method. We also sought to evaluate whether 3D pathology improves staging accuracy in comparison to two-dimensional (2D) histology. APPROACH: We developed a method to fluorescently stain and optically clear LN specimens for comprehensive imaging with multiresolution open-top light-sheet microscopy. We present an efficient imaging and data-processing workflow for rapid evaluation of H&E-like datasets in 3D, with low-resolution screening to identify potential metastases followed by high-resolution localized imaging to confirm malignancy.

resultsWe simulate LN staging with 3D and 2D pathology datasets from 10 metastatic nodes, showing that 2D pathology consistently underestimates metastasis size, including instances in which 3D pathology would lead to upstaging of the metastasis with important implications on clinical treatment.

conclusionsOur 3D pathology method may improve clinical management for breast cancer patients by improving staging accuracy of LN metastases.

Indexed as

Breast NeoplasmsAxillaFemaleHumansLymphatic MetastasisLymph NodesNeoplasm Stagingbreast cancerlymph node stagingopen-top light-sheet microscopythree-dimensional pathology

Identifiers

PMID35315258
PMCPMC8936940
OpenAlexW4221069568

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.