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

Year: 2025

Authors: Ricci P., Bonaudo C., Ezhov I., Toaha A., Nardini D., Camelia M., Lucidi F., Nozzoli F., Mach T., Tachtsidis I., Rueckert D., Della Puppa A., Giannoni L., Pavone F.S.

Autors Affiliation: Univ Florence, Dept Phys & Astron, Sesto Fiorentino, Italy; European Lab Nonlinear Spect, Sesto Fiorentino, Italy; Univ Florence, Azienda Osped Univ Careggi, Dept Neurosci Psychol Pharmacol & Child Hlth, Neurosurg, Florence, Italy; Tech Univ Munich, Klinikum Rechts Isar, Munich, Germany; Careggi Univ Hosp, Histopathol & Mol Diagnost, Florence, Italy; UCL, Dept Med Phys & Biomed Engn, London, England; Imperial Coll London, Dept Comp, London, England; Munich Ctr Machine Learning MCML, Munich, Germany; CNR, Natl Inst Opt, Sesto Fiorentino, Italy.

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.

Journal/Review: JOURNAL OF BIOPHOTONICS

More Information: This work was supported by HORIZON EUROPE European Innovation Council and innovation program under grant agreement No 101071040-Project HyperProbe. I.T. from UCL is supported by the UK Research and Innovation (UKRI) (Grant No. 10048387). This research has also been supported by the Italian Ministry for University and Research in the framework of the Advanced Light Microscopy Italian Node of Euro-Bioimaging ERIC.
KeyWords: Hyperspectral Imaging; Meningiomas; Tumor Grade Discrimination
DOI: 10.1002/jbio.202500374