Evidence map›Paper›PMID 37234975›Full record

ArticleFrontiers in oncology2023

Intraoperative microscopic autofluorescence detection and characterization in brain tumors using stimulated Raman histology and two-photon fluorescence.

Gina Fürtjes, David Reinecke, Niklas von Spreckelsen, Anna-Katharina Meißner, Daniel Rueß, Marco Timmer, Christian Freudiger, Adrian Ion-Margineanu, Florian Khalid, Konstantin Watrinet and 5 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
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

17 citing papers in PubMed.

  1. OPTRACE: Optical Imaging-Guided Transplantation and Tracking of Cells in the Mouse Brain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  2. Relevance of light conditions for clinicalFrontiers in oncology · 2026
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  3. Review
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  5. Fluorescence Lifetime Imaging Microscopy Analysis of Isolated Melanosomes.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025
    Article
  6. Review
  7. Mycology · 2025
    Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. 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

15 authors.

Gina FürtjesDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
David ReineckeDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Niklas von SpreckelsenDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Anna-Katharina MeißnerDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Daniel RueßDepartment of Stereotaxy and Functional Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Marco TimmerDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Christian FreudigerInvenio Imaging, Inc., Santa Clara, CA, United States.
Adrian Ion-MargineanuInvenio Imaging, Inc., Santa Clara, CA, United States.
Florian KhalidInvenio Imaging, Inc., Santa Clara, CA, United States.
Konstantin WatrinetMedical Faculty, University Heidelberg, Heidelberg, Germany.
Christian MawrinUniversity Hospital Magdeburg, Institute of Neuropathology, Magdeburg, Germany.
Andriy ChmyrovHelmholtz Zentrum München, Neuherberg, Germany.
Roland GoldbrunnerDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.
Oliver BrunsHelmholtz Zentrum München, Neuherberg, Germany.
Volker NeuschmeltingDepartment of General Neurosurgery, Center of Neurosurgery, University Hospital Cologne, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The intrinsic autofluorescence of biological tissues interferes with the detection of fluorophores administered for fluorescence guidance, an emerging auxiliary technique in oncological surgery. Yet, autofluorescence of the human brain and its neoplasia is sparsely examined. This study aims to assess autofluorescence of the brain and its neoplasia on a microscopic level by stimulated Raman histology (SRH) combined with two-photon fluorescence. Methods: With this experimentally established label-free microscopy technique unprocessed tissue can be imaged and analyzed within minutes and the process is easily incorporated in the surgical workflow. In a prospective observational study, we analyzed 397 SRH and corresponding autofluorescence images of 162 samples from 81 consecutive patients that underwent brain tumor surgery. Small tissue samples were squashed on a slide for imaging. SRH and fluorescence images were acquired with a dual wavelength laser (790 nm and 1020 nm) for excitation. In these images tumor and non-tumor regions were identified by a convolutional neural network that reliably differentiates between tumor, healthy brain tissue and low quality SRH images. The identified areas were used to define regions.of- interests (ROIs) and the mean fluorescence intensity was measured. Results: In healthy brain tissue, we found an increased mean autofluorescence signal in the gray (11.86, Discussion: In conclusion we found that autofluorescence in the brain varies depending on the tissue type and localization and differs significantly among various brain tumors. This needs to be considered for interpreting photon signal during fluorescence-guided brain tumor surgery.

Indexed as

artificial intelligenceautofluorescencebrain tumorfluorescence-guided surgery (FGS)stimulated Raman histology

Identifiers

PMID37234975
PMCPMC10207900

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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.