Evidence map›Paper›PMID 36509907›Full record

ArticleJournal of neuro-oncology2023

A new approach for clinical translation of infrared spectroscopy: exploitation of the signature of glioblastoma for general brain tumor recognition.

Gerald Steiner, Roberta Galli, Grit Preusse, Susanne Michen, Matthias Meinhardt, Achim Temme, Stephan B Sobottka, Tareq A Juratli, Edmund Koch, Gabriele Schackert and 2 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neuro-oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

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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

12 authors at 3 institutions in 1 country.

Gerald SteinerClinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany.
Roberta GalliMedical Physics and Biomedical Engineering, Faculty of Medicine, TU Dresden, Dresden, Germany.
Grit PreusseClinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany.
Susanne MichenDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Matthias MeinhardtDepartment of Pathology (Neuropathology), University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
Achim TemmeDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Stephan B SobottkaDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Tareq A JuratliDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Edmund KochClinical Sensoring and Monitoring, Department of Anesthesiology and Intensive Care Medicine, Faculty of Medicine, TU Dresden, Dresden, Germany.
Gabriele SchackertDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany.
Matthias KirschAsklepios Kliniken Schildautal Seesen, Seesen, Germany.
Ortrud UckermannDepartment of Neurosurgery, University Hospital Carl Gustav Carus, TU, Dresden, Germany. ortrud.uckermann@uniklinikum-dresden.de.
TU Dresden · DEUniversity Hospital Carl Gustav Carus · DEAsklepios Kliniken Schildautal · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeInfrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore, we propose the exploitation of these common spectral changes for brain tumor recognition.

methodsAttenuated total reflection IR spectroscopy was performed on fresh specimens of 790 patients within minutes after resection. Using principal component analysis and linear discriminant analysis, a classification model was developed on a subset of glioblastoma (n = 135) and non-neoplastic brain (n = 27) specimens, and then applied to classify the IR spectra of several types of brain tumors.

resultsThe model correctly classified 82% (517/628) of specimens as "tumor" or "non-tumor", respectively. While the sensitivity was limited for infiltrative glioma, this approach recognized GBM (86%), other types of primary brain tumors (92%) and brain metastases (92%) with high accuracy and all non-tumor samples were correctly identified.

conclusionThe concept of differentiation of brain tumors from non-tumor brain based on a common spectroscopic tumor signature will accelerate clinical translation of infrared spectroscopy and related technologies. The surgeon could use a single instrument to detect a variety of brain tumor types intraoperatively in future clinical settings. Our data suggests that this would be associated with some risk of missing infiltrative regions or tumors, but not with the risk of removing non-tumor brain.

Indexed as

Brain NeoplasmsGlioblastomaGliomaBrainHumansSpectrophotometry, InfraredSpectroscopy, Fourier Transform InfraredBrain tumorDelineationInfrared spectroscopyIntraoperative

Identifiers

PMID36509907
PMCPMC9886632
OpenAlexW4311181727

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.