ArticleBiosensors2017
Raman Spectroscopy of Head and Neck Cancer: Separation of Malignant and Healthy Tissue Using Signatures Outside the "Fingerprint" Region.
Article in Biosensors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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.
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Who cites it
3 citing papers in PubMed.
- Assessment and interpretation of the status of surgical margins following resective surgery for head and neck squamous cancer: a narrative review.World journal of surgical oncology · 2025Review
- Fused Raman spectroscopic analysis of blood and saliva delivers high accuracy for head and neck cancer diagnostics.Scientific reports · 2022Article
- Qualitative and Quantitative Diagnosis in Head and Neck Cancer.Diagnostics (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability to rapidly and accurately discriminate between healthy and malignant tissue offers surgeons a tool for in vivo analysis that would potentially reduce operating time, facilitate quicker recovery, and improve patient outcomes. To this end, we investigate discrimination between diseased tissue and adjacent healthy controls from patients with head and neck cancer using near-infrared Raman spectroscopy. Our results indicate previously unreported peaks in the Raman spectra that lie outside the conventional "fingerprint" region (400 cm-1-1800 cm -1) played an important role in our analysis and in discriminating between the tissue classes. Preliminary multivariate statistical analyses of the Raman spectra indicate that discrimination between diseased and healthy tissue is possible based on these peaks.
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