ArticleThe Laryngoscope2017
The color of cancer: Margin guidance for oral cancer resection using elastic scattering spectroscopy.
Article in The Laryngoscope, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 30 citations in OpenAlex.
- 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
- Review
- Digital localization of intraoperative samples enhances margin analysis precision in oral squamous cell carcinoma.Frontiers in medicine · 2025Article
- The Diagnostic Potential of Non-Invasive Tools for Oral Cancer and Precancer: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- A Systematic Review of Oral Biopsies, Sample Types, and Detection Techniques Applied in Relation to Oral Cancer Detection.Biotech (Basel (Switzerland)) · 2022Review
- Artificial Intelligence-Based Assessment of Colorectal Polyp Histology by Elastic-Scattering Spectroscopy.Digestive diseases and sciences · 2022Article
- Article
- Article
- Frozen Section Analysis and Real-Time Magnetic Resonance Imaging of Surgical Specimen Oriented on 3D Printed Tongue Model to Assess Surgical Margins in Oral Tongue Carcinoma: Preliminary Results.Frontiers in oncology · 2021Article
- Advanced endoscopic imaging for detecting and guiding therapy of early neoplasias of the esophagus.Annals of the New York Academy of Sciences · 2020Review
- Recent Advances in the Application of Artificial Intelligence in Otorhinolaryngology-Head and Neck Surgery.Clinical and experimental otorhinolaryngology · 2020Review
- Assessment of surgical tumor-free resection margins in fresh squamous-cell carcinoma resection specimens of the tongue using a clinical MRI system.Head & neck · 2020Article
- The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa.Journal of biophotonics · 2020Article
- Two-channel autofluorescence analysis for oral cancer.Journal of biomedical optics · 2018Article
- Big Data in Head and Neck Cancer.Current treatment options in oncology · 2018Review
- Elastic scattering spectroscopy for intraoperative oral cancer mucosal margin guidance: Initial results from a 104 patient cohort.American journal of otolaryngologyArticle
- Non-invasive screening for laryngeal cancer using the oral cavity as a proxy for differentiation of laryngeal cancer versus leukoplakia: A novel application of ESS technology and artificial intelligence supported statistical modeling.American journal of otolaryngologyArticle
- A prospective cohort study testing whether oral cavity mucosal tissue variability influences elastic scattering spectroscopy (ESS) measures.American journal of otolaryngologyArticle
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
objectives/hypothesisTo evaluate the usefulness of elastic scattering spectroscopy (ESS) as a diagnostic adjunct to frozen section analysis in patients with diagnosed squamous cell carcinoma of the oral cavity. STUDY
designProspective analytic study.
methodsSubjects for this single institution, institutional review board-approved study were recruited from among patients undergoing surgical resection for squamous cell cancer of the oral cavity. A portable ESS device with a contact fiberoptic probe was used to obtain spectral signals. Four to 10 spectral readings were obtained on each subject from various sites including gross tumor and normal-appearing mucosa in the surgical margin. Each reading was correlated with the histopathologic findings of biopsies taken from the exact location of the spectral readings. A diagnostic algorithm based on multidimensional pattern recognition/machine learning was developed. Sensitivity and specificity, error rate, and area under the curve were used as performance metrics for tests involving classification between disease and nondisease classes.
resultsThirty-four (34) subjects were enrolled in the study. One hundred seventy-six spectral data point/biopsy specimen pairs were available for analysis. ESS distinguished normal from abnormal tissue, with a sensitivity ranging from 84% to 100% and specificity ranging from 71% to 89%, depending on how the cutoff between normal and abnormal tissue was defined (i.e., mild, moderate, or severe dysplasia). There were statistically significant differences in malignancy scores between histologically normal tissue and invasive cancer and between noninflamed tissue and inflamed tissue.
conclusionsThis is the first study to evaluate the effectiveness of ESS in guiding mucosal resection margins in oral cavity cancer. ESS provides fast, real-time assessment of tissue without the need for pathology expertise. ESS appears to be effective in distinguishing between normal mucosa and invasive cancer and between "normal" tissue (histologically normal and mild dysplasia) and "abnormal" tissue (severe dysplasia and carcinoma in situ) that might require further margin resection. Further studies, however, are needed with a larger sample size to validate these findings and to determine the effectiveness of ESS in distinguishing visibly and histologically normal tissue from visibly normal but histologically abnormal tissue. LEVEL OF EVIDENCE: NA Laryngoscope, 127:S1-S9, 2017.
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