====== Raman spectroscopy ====== {{rss>https://pubmed.ncbi.nlm.nih.gov/rss/search/1Hme278Y-6cb3hD8cxeqdd6qyLsGneMCBNjQV5I5b-A3gZagTz/?limit=15&utm_campaign=pubmed-2&fc=20240829054034}} {{ ::ramanspectroscopy.jpg?400|}} [[Raman]] [[spectroscopy]] named after Indian physicist Sir C. V. Raman is a spectroscopic technique used to observe vibrational, rotational, and other low-frequency modes in a system. Raman spectroscopy is commonly used in chemistry to provide a structural fingerprint by which molecules can be identified. ---- Navigation-guided brain biopsies are the standard of care for diagnosis of several brain pathologies. However, imprecise targeting and tissue heterogeneity often hinder obtaining high-quality tissue samples, resulting in poor diagnostic yield. ===== Indications ===== Metabolic changes and their mechanisms during cancer development in recent years have been the subject of investigation by researchers from all over the world. To precisely monitor these changes modern and noninvasive tools are needed. One of these approaches is Raman spectroscopy which gives very precise, unambiguous results, allowing the detection of even the smallest changes occurring inside a single cell during disease states ((Cutshaw G, Uthaman S, Hassan N, Kothadiya S, Wen X, Bardhan R. The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine. Chem Rev. 2023 Jul 12;123(13):8297-8346. doi: 10.1021/acs.chemrev.2c00897. Epub 2023 Jun 15. PMID: 37318957; PMCID: PMC10626597.)) ((Hill IE, Boyd M, Milligan K, Jenkins CA, Sorensen A, Jirasek A, Graham D, Faulds K. Understanding radiation response and cell cycle variation in brain tumour cells using Raman spectroscopy. Analyst. 2023 May 30;148(11):2594-2608. doi: 10.1039/d3an00121k. PMID: 37166147; PMCID: PMC10228487.)) ((Milligan, K. et al. Raman spectroscopy and group and basis-restricted non negative matrix factorisation identifies radiation induced metabolic changes in human cancer cells. Sci Rep. 11(1), 1–11. https://doi.org/10.1038/s41598-021-83343-5 (2021).)) ---- Spectroscopy was successfully integrated into existing neurosurgical workflows, and in situ spectroscopic data could be classified based on ex vivo data. RS confirmed its ability to detect brain tumors, while [[Near-infrared autofluorescence]] (AF) emerged as a competitive method for intraoperative tumor delineation ((Uckermann O, Ziegler J, Meinhardt M, Richter S, Schackert G, Eyüpoglu IY, Hijazi MM, Krex D, Juratli TA, Sobottka SB, Galli R. Raman and autofluorescence spectroscopy for in situ identification of neoplastic tissue during surgical treatment of brain tumors. J Neurooncol. 2024 Aug 28. doi: 10.1007/s11060-024-04809-w. Epub ahead of print. PMID: 39196481.)) ---- Raman histology has potential for detecting viable tumor in biopsied tissue and for identifying tumor infiltration in vivo ((Hollon T, Stummer W, Orringer D, Suero Molina E. Surgical Adjuncts to Increase the Extent of Resection: Intraoperative MRI, Fluorescence, and Raman Histology. Neurosurg Clin N Am. 2019 Jan;30(1):65-74. doi: 10.1016/j.nec.2018.08.012. Review. PubMed PMID: 30470406. )). Desroches et al., from the [[Montreal Neurological Institute and Hospital]], report the development and first clinical testing of a [[navigation]]-guided [[fiberoptic]] Raman probe that allows surgeons to interrogate [[brain tissue]] in situ at the tip of the [[biopsy needle]], prior to [[tissue]] [[removal]]. The 900μm diameter probe can detect high spectral quality Raman signals in both the fingerprint and high wavenumber spectral regions with minimal disruption to the neurosurgical workflow. The probe was tested in 3 brain tumor patients, and the acquired spectra in both normal brain and tumor tissue demonstrated the expected spectral features, indicating the quality of the data. As a proof-of-concept, they also demonstrate the consistency of the acquired Raman signal with different systems and experimental settings. Additional clinical development is planned to further evaluate the performance of the system and develop a statistical model for real-time tissue classification during the [[biopsy]] [[procedure]] ((Desroches J, Lemoine É, Pinto M, Marple E, Urmey K, Diaz R, Guiot MC, Wilson BC, Petrecca K, Leblond F. Development and first in-human use of a Raman spectroscopy guidance system integrated with a brain biopsy needle. J Biophotonics. 2019 Jan 12. doi: 10.1002/jbio.201800396. [Epub ahead of print] PubMed PMID: 30636032. )). ---- The aim of a study was to use Raman spectroscopy to analyze the biochemical composition of [[medulloblastoma]] and normal tissues from the safety margin of the CNS and to find specific Raman biomarkers capable of differentiating between tumorous and normal tissues. The tissue samples consisted of medulloblastoma (grade IV) (n = 11). The tissues from the negative margins were used as normal controls. Raman images were generated by a confocal Raman microscope-WITec alpha 300 RSA. Raman vibrational signatures can predict which tissue has tumorous biochemistry and can identify medulloblastoma. The Raman technique makes use of the fact that tumors contain large amounts of protein and far less lipids (fatty compounds), while healthy tissue is rich in both. The ability of Raman spectroscopy and imaging to detect medulloblastoma tumors fills the niche in diagnostics. These powerful analytical techniques are capable of monitoring tissue morphology and biochemistry. The results demonstrate that RS can be used to discriminate between normal and medulloblastoma tissues ((Polis B, Imiela A, Polis L, Abramczyk H. Raman spectroscopy for medulloblastoma. Childs Nerv Syst. 2018 Jul 12. doi: 10.1007/s00381-018-3906-7. [Epub ahead of print] PubMed PMID: 30003328; PubMed Central PMCID: PMC6224026. )). ===== Raman spectroscopy for glioma ===== see [[Raman spectroscopy for glioma]]. ===== Raman spectroscopy for meningioma ===== [[Raman spectroscopy for meningioma]]. ===== References =====