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doi:10.22028/D291-47464 | Titel: | Stimulated Raman Spectroscopy for Intraoperative Glioblastoma Diagnosis—A Complementary Tool to Frozen Section? |
| VerfasserIn: | Sippl, Christoph Stark, Felix Schneider, K. Isabel Reyes Medina, Bernardo Schulz-Schaeffer, Walter Brinkmann, Maximilian Neumann, Felix Droop, Ramon Ullmann, Steffen Würthwein, Thomas Hellwig, Tim Hoffmann, Lucas Monfroy, Nathan Khafaji, Fatemeh Saffour, Safwan Gaber, Karim Linsler, Stefan |
| Sprache: | Englisch |
| Titel: | Cancers |
| Bandnummer: | 18 |
| Heft: | 7 |
| Verlag/Plattform: | MDPI |
| Erscheinungsjahr: | 2026 |
| Freie Schlagwörter: | glioblastoma Raman spectroscopy histology |
| DDC-Sachgruppe: | 610 Medizin, Gesundheit |
| Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
| Abstract: | Background: Glioblastoma (GBM) remains the most aggressive primary brain tumor, and intraoperative frozen section analysis is the current standard for rapid histopathological assessment. However, this approach is time-consuming and resource-intensive. Stimulated Raman scattering (SRS) imaging has emerged as a label-free technique enabling near real-time microscopic evaluation of fresh tissue. This study compares the visualization of selected histopathological features in a newly developed intraoperative SRS system with conventional hematoxylin–eosin (HE) staining in confirmed GBM. Methods: Tumor samples from 30 patients with neuropathologically confirmed GBM were analyzed. For each case, both HE-stained frozen sections and SRS-generated virtual HE-like images were prepared from separate portions of the specimen. Twelve neuropathologists with varying levels of experience assessed 60 images according to seven predefined GBM criteria, resulting in 720 image evaluations. Feature detection was analyzed using cluster-adjusted generalized estimating equation models, and interobserver agreement was assessed using Fleiss’ κ. Results: Descriptively, hypercellularity and hypervascularization were identified at similar frequencies in both modalities, whereas pleomorphism, endothelial proliferation, mitotic activity, and necrosis were more often recognized in HE images. In cluster-adjusted analyses, SRS showed significantly lower detection rates for hypercellularity, pleomorphism, endothelial proliferation, and mitotic activity, while no significant difference was observed for hypervascularization, necrosis, or pseudopalisading after false discovery rate correction. Interobserver agreement was feature-dependent and generally higher for HE than SRS, particularly for hypercellularity. Conclusions: In this feature-level analysis of neuropathologically confirmed GBM, SRS imaging provided rapid, label-free morphological information and showed comparable visualization of selected histopathological features, particularly hypervascularization. While conventional HE-stained frozen sections remained superior for certain WHO-defining features, SRS represents a promising intraoperative adjunct that may complement established neuropathological workflows. Further studies including non-tumor tissue and a broader range of glioma grades are needed to determine the full diagnostic accuracy and clinical applicability of this technique. |
| DOI der Erstveröffentlichung: | 10.3390/cancers18071053 |
| URL der Erstveröffentlichung: | https://doi.org/10.3390/cancers18071053 |
| Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-474645 hdl:20.500.11880/41504 http://dx.doi.org/10.22028/D291-47464 |
| ISSN: | 2072-6694 |
| Datum des Eintrags: | 14-Apr-2026 |
| Bezeichnung des in Beziehung stehenden Objekts: | Supplementary Materials |
| In Beziehung stehendes Objekt: | https://www.mdpi.com/article/10.3390/cancers18071053/s1 |
| Fakultät: | M - Medizinische Fakultät |
| Fachrichtung: | M - Neurochirurgie M - Neuropathologie |
| Professur: | M - Prof. Dr. Joachim Oertel M - Prof. Dr. Walter Schulz-Schaeffer |
| Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| cancers-18-01053.pdf | 4,45 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons

