ArticleCancers2021
Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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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.
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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.
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Who cites it
19 citing papers in PubMed.
- Shining a light on brain tumors: a review of Raman spectroscopy in the operating room.Journal of biomedical optics · 2026Review
- Recent Advances in Raman Spectral Classification with Machine Learning.Sensors (Basel, Switzerland) · 2026Review
- Integrating spatial and chemical information enhances differentiation of non-alcoholic steatohepatitis states in Raman imaging.Scientific reports · 2025Article
- Towards Optical Biopsy in Glioma Surgery.International journal of molecular sciences · 2025Review
- Comprehensive multicentre retrospective analysis for predicting isocitrate dehydrogenase-mutant lower-grade gliomas.Annals of clinical and translational neurology · 2025Article
- Review
- Point-of-care mass spectrometry metabolomic analysis enabling intraoperative brain tumor diagnosis.Theranostics · 2025Article
- Accurate and rapid molecular subgrouping of high-grade glioma via deep learning-assisted label-free fiber-optic Raman spectroscopy.PNAS nexus · 2024Article
- Optical Methods for Brain Tumor Detection: A Systematic Review.Journal of clinical medicine · 2024Review
- Raman Spectroscopy as a Research and Diagnostic Tool in Clinical Hematology and Hematooncology.International journal of molecular sciences · 2024Review
- Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation.BMC cancer · 2024Article
- Advances in Diagnostic Tools and Therapeutic Approaches for Gliomas: A Comprehensive Review.Sensors (Basel, Switzerland) · 2023Review
- An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis.Scientific reports · 2023Article
- Molecular Biomarkers and Recent Liquid Biopsy Testing Progress: A Review of the Application of Biosensors for the Diagnosis of Gliomas.Molecules (Basel, Switzerland) · 2023Review
- Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning.Pharmaceutics · 2023Article
- Machine Learning of Raman Spectroscopy Data for Classifying Cancers: A Review of the Recent Literature.Diagnostics (Basel, Switzerland) · 2022Review
- Method for the Intraoperative Detection of IDH Mutation in Gliomas with Differential Mobility Spectrometry.Current oncology (Toronto, Ont.) · 2022Article
- Raman spectroscopy: A prospective intraoperative visualization technique for gliomas.Frontiers in oncology · 2022Review
- From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives.Free neuropathology · 2022Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS's ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.
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Registered trials
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.