Evidence map›Paper›PMID 41397700›Full record

ArticleJournal of biophotonics2026

A Label-Free Hyperspectral Imaging Device for Ex Vivo Characterization and Grading of Meningioma Tissues.

Pietro Ricci, Camilla Bonaudo, Ivan Ezhov, Anam Toaha, Dorotea Nardini, Manuel Camelia, Federica Lucidi, Filippo Nozzoli, Tim Mach, Ilias Tachtsidis and 4 more

Abstract read
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In one paragraph

Article in Journal of biophotonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Pietro RicciDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy.
Camilla BonaudoNeurosurgery, Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Ivan EzhovKlinikum Rechts der Isar, Technischen Universität München, Munich, Germany.
Anam ToahaDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy.
Dorotea NardiniDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy.
Manuel CameliaNeurosurgery, Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Federica LucidiNeurosurgery, Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Filippo NozzoliHistopathology and Molecular Diagnostics, Careggi University Hospital, Florence, Italy.ORCID 0000-0002-0201-1227
Tim MachKlinikum Rechts der Isar, Technischen Universität München, Munich, Germany.
Ilias TachtsidisDepartment of Medical Physics and Biomedical Engineering, University College London, London, UK.
Daniel RueckertKlinikum Rechts der Isar, Technischen Universität München, Munich, Germany.
Alessandro Della PuppaNeurosurgery, Department of Neuroscience, Psychology, Pharmacology and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Luca GiannoniDepartment of Medical Physics and Biomedical Engineering, University College London, London, UK.
Francesco S PavoneDepartment of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy.

Funding

European Innovation Council - Horizon Europe 101071040Italian Ministry for University and Research - Euro-Bioimaging ERICUK Research and Innovation (UKRI) 10048387
6 · The paper itself

Abstract

Histopathology remains the gold standard for definitive tumor diagnosis after surgical resection; however, its lengthy processing time can delay critical postoperative care. Hyperspectral imaging (HSI) is emerging as a promising label-free technique for rapid biochemical tissue assessment. Here, we present HyperProbe1.1 (HP1.1), an HSI system designed for noninvasive analysis of fresh brain tumor biopsies. In this proof-of-concept study, we applied the HP1.1 system to freshly excised meningioma specimens-the most common primary intracranial tumors. The platform enabled rapid, label-free mapping of metabolic activity and vascular heterogeneity, while spectral unmixing further allowed the quantification of endogenous biomarkers such as cytochrome c oxidase (CCO), hemoglobin derivatives, and lipids, revealing molecular patterns consistent with histopathological tumor grading according to the 2021 WHO classification. These results highlight the feasibility of HSI for rapid biochemical tissue assessment and its potential integration into intraoperative decision-making.

Indexed as

Hyperspectral ImagingMeningeal NeoplasmsMeningiomaHumansNeoplasm GradingHyperspectral ImagingMeningiomasTumor Grade Discrimination

Identifiers

PMID41397700
PMCPMC12977303

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Registered trials

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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.