Zusammenfassung
Hintergrund
Ein individualisiertes chirurgisches Vorgehen ist in der Hirntumorchirurgie zum Erreichen einer maximal sicheren Resektion essenziell. Die Radikalität der Resektion ist maßgeblich abhängig von der histologischen Diagnose. Die stimulierte Raman-Histologie (SRH), eine laserbasierte optische Bildgebung, bietet die Möglichkeit der Erhebung einer intraoperativen Diagnose in wenigen Minuten.
Ziel der Arbeit
Überblick über die Anwendung von SRH in der Neurochirurgie und Übertragung der Technik auf weitere chirurgische Disziplinen.
Methoden
Beschreibung der Technik und Zusammenfassung der aktuellen Literatur zu SRH.
Ergebnisse
SRH konnte erfolgreich bei multiplen neuroonkologischen Tumorentitäten angewendet werden. Erste Pilotprojekte zeigen Potenzial zur Analyse extrazerebraler Tumoren auf.
Zusammenfassung
SRH ermöglicht eine Echtzeitdiagnose mit hoher diagnostischer Genauigkeit und bietet weiteres Entwicklungspotenzial zur Verbesserung der personalisierten Tumorchirurgie.
Abstract
Background
In brain tumor surgery a personalized surgical approach is crucial to achieve a maximum safe tumor resection. The extent of resection decisively depends on the histological diagnosis. Stimulated Raman histology (SRH), a fiber laser-based optical imaging method, offers the possibility for evaluation of an intraoperative diagnosis in a few minutes.
Objective
To provide an overview on the applications of SRH in neurosurgery and transference of the technique to other surgical disciplines.
Methods
Description of the technique and review of the current literature on SRH.
Results
The SRH technique was successfully used in multiple neuro-oncological tumor entities. Initial pilot projects showed the potential for analysis of extracranial tumors.
Conclusion
The use of SRH provides a near real-time diagnosis with high diagnostic accuracy and provides further developmental potential to improve personalized tumor surgery.
Literatur
daCosta DJ, Htwe YM, Murthy V (2022) Rapid evaluation of bronchoscopic biopsies using stimulated raman histology. In: A109. The odyssey, no longer a tragedy: the continuum of lung cancer. American Thoracic Society, S S A5562–A5562
Di L, Eichberg DG, Park YJ et al (2021) Rapid intraoperative diagnosis of meningiomas using stimulated raman histology. World Neurosurg 150:e108–e116. https://doi.org/10.1016/j.wneu.2021.02.097
Eichberg DG, Shah AH, Di L et al (2019) Stimulated Raman histology for rapid and accurate intraoperative diagnosis of CNS tumors: prospective blinded study. J Neurosurg 134:137–143. https://doi.org/10.3171/2019.9.JNS192075
Einstein EH, Ablyazova F, Rosenberg A et al (2022) Stimulated Raman histology facilitates accurate diagnosis in neurosurgical patients: a one-to-one noninferiority study. J Neurooncol 159:369–375. https://doi.org/10.1007/s11060-022-04071-y
Freudiger CW, Min W, Saar BG et al (2008) Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy. Science 322:1857–1861. https://doi.org/10.1126/science.1165758
Fürtjes G, Reinecke D, Von Spreckelsen N et al (2023) Intraoperative microscopic autofluorescence detection and characterization in brain tumors using stimulated Raman histology and two-photon fluorescence https://doi.org/10.3389/fonc.2023.1146031
Hollon T, Jiang C, Chowdury A et al (2022) AI-based molecular classification of diffuse gliomas using rapid, label-free optical imaging https://doi.org/10.21203/rs.3.rs-1930236/v1
Hollon TC, Lewis S, Pandian B et al (2018) Rapid intraoperative diagnosis of pediatric brain tumors using stimulated raman histology. Cancer Res 78:278–289. https://doi.org/10.1158/0008-5472.CAN-17-1974
Hollon TC, Orringer DA (2020) An automated tissue-to-diagnosis pipeline using intraoperative stimulated Raman histology and deep learning. Mol Cell Oncol 7:1736742. https://doi.org/10.1080/23723556.2020.1736742
Hollon TC, Pandian B, Adapa AR et al (2020) Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nat Med 26:52–58. https://doi.org/10.1038/s41591-019-0715-9
Hollon TC, Pandian B, Urias E et al (2021) Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks. Neuro Oncol 23:144–155. https://doi.org/10.1093/neuonc/noaa162
Ji M, Lewis S, Camelo-Piragua S et al (2015) Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy. Sci Transl Med 7:309ra163. https://doi.org/10.1126/scitranslmed.aab0195
Jiang C, Bhattacharya A, Linzey JR et al (2022) Rapid automated analysis of skull base tumor specimens using intraoperative optical imaging and artificial intelligence. Neurosurgery 90:758–767. https://doi.org/10.1227/neu.0000000000001929
Liu Z, Su W, Ao J et al (2022) Instant diagnosis of gastroscopic biopsy via deep-learned single-shot femtosecond stimulated Raman histology. Nat Commun 13:4050. https://doi.org/10.1038/s41467-022-31339-8
Mannas MP, Deng F‑M, Belanger EC et al (2023) Stimulated Raman histology as a method to determine the adequacy of renal mass biopsy and identify malignant subtypes of renal cell carcinoma. Urol Oncol 41(328):e9–328.e13. https://doi.org/10.1016/j.urolonc.2023.04.008
Mannas MP, Jones D, Deng F‑M et al (2023) Stimulated Raman histology, a novel method to allow for rapid pathologic examination of unprocessed, fresh prostate biopsies. Prostate 83:1060–1067. https://doi.org/10.1002/pros.24547
Neidert N, Straehle J, Erny D et al (2022) Stimulated Raman histology in the neurosurgical workflow of a major European neurosurgical center—part A. Neurosurg Rev 45:1731–1739. https://doi.org/10.1007/s10143-021-01712-0
Orringer DA, Pandian B, Niknafs YS et al (2017) Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy. Nat Biomed Eng. https://doi.org/10.1038/s41551-016-0027
Pekmezci M, Morshed RA, Chunduru P et al (2021) Detection of glioma infiltration at the tumor margin using quantitative stimulated Raman scattering histology. Sci Rep 11:12162. https://doi.org/10.1038/s41598-021-91648-8
Reinecke D, Spreckelsen N, Mawrin C et al (2022) Novel rapid intraoperative qualitative tumor detection by a residual convolutional neural network using label-free stimulated Raman scattering microscopy. Acta Neuropathol Commun 10:109. https://doi.org/10.1186/s40478-022-01411-x
Steybe D, Poxleitner P, Metzger MC et al (2023) Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma. Clin Oral Investig 27:4705–4713. https://doi.org/10.1007/s00784-023-05098-9
Straehle J, Erny D, Neidert N et al Neuropathological interpretation of stimulated Raman histology images of brain and spine tumors: part B. 1:3. https://doi.org/10.1007/s10143-021-01711-1
Wadiura LI, Kiesel B, Roetzer-Pejrimovsky T et al Toward digital histopathological assessment in surgery for central nervous system tumors using stimulated Raman histology https://doi.org/10.3171/2022.9.FOCUS22440
Zhang L, Wu Y, Zheng B et al (2019) Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy. Theranostics 9:2541–2554. https://doi.org/10.7150/thno.32655
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A.-K. Meißner, R. Goldbrunner und V. Neuschmelting geben an, dass kein Interessenkonflikt besteht.
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Meißner, AK., Goldbrunner, R. & Neuschmelting, V. Personalisierte Hirntumorchirurgie mittels intraoperativer stimulierter Raman-Histologie. Chirurgie 95, 274–279 (2024). https://doi.org/10.1007/s00104-024-02038-5
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DOI: https://doi.org/10.1007/s00104-024-02038-5
Schlüsselwörter
- Schnellschnittdiagnostik
- Raman-Spektroskopie
- Personalisierte Chirurgie
- Intraoperative Gewebeanalyse
- Künstliche Intelligenz