ArticleCancers2021
Glioma
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 2 syntheses or guidelines pooled it, 88 citations in OpenAlex.
- Illuminating glioma surgery: A meta-analysis of Raman spectroscopy for intraoperative decision-making.Neurosurgical review · 2025Pooled it
- Metabolic Imaging as Future Technology and Innovation in Brain-Tumour Surgery: A Systematic Review.Current oncology (Toronto, Ont.) · 2025Pooled it
- Qualitative and quantitative assessment ofBiomedical optics express · 2026Article
- Circulating Tumor Cells in Glioblastoma.Cancers · 2025Review
- Challenges and opportunities for new intraoperative optical techniques in the surgical treatment of pituitary adenomas: a review.Journal of biomedical optics · 2025Review
- Fluorescence Guided Raman Spectroscopy enables the training of robust support vector machines for the detection of tumour marker proteins.Scientific reports · 2025Article
- Deep neural network modeling for brain tumor classification using magnetic resonance spectroscopic imaging.PLOS digital health · 2025Article
- Review
- Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma.Neuro-oncology · 2024Article
- A Single-Cell Metabolic Profiling Characterizes Human Aging via SlipChip-SERS.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Current Applications of Raman Spectroscopy in Intraoperative Neurosurgery.Biomedicines · 2024Review
- 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
- Computational Assessment of Spectral Heterogeneity within Fresh Glioblastoma Tissue Using Raman Spectroscopy and Machine Learning Algorithms.Molecules (Basel, Switzerland) · 2024Article
- Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation.BMC cancer · 2024Article
- Perspective: Raman spectroscopy for detection and management of diseases affecting the nervous system.Frontiers in veterinary science · 2024Article
- A review of clinical use of surface-enhanced Raman scattering-based biosensing for glioma.Frontiers in neurology · 2024Review
- Extended Analysis of Raman Spectra Using Artificial Intelligence Techniques for Colorectal Abnormality Classification.Journal of imaging · 2023Article
- An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis.Scientific reports · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
Abstract
Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.
Indexed as
Identifiers
What OpenQuestion holds
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.