ArticleClinical oral investigations2023
Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma.
Article in Clinical oral investigations, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Article
- Separability of histopathology foundation model embeddings of stimulated Raman histology images for lung carcinoma subtyping.Journal of Cancer · 2026Article
- Detection of malignant lung tumors using stimulated Raman histology and convolutional neural networks.Journal of thoracic disease · 2025Article
- 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
- H&E Style Translation Using CycleGAN for Deep Ultraviolet-Excitation Fluorescence Images of Pancreatic Endoscopic Ultrasound-Fine Needle Aspiration/Biopsy Toward Slide-Free Rapid Pathology.Acta histochemica et cytochemica · 2025Article
- Artificial Intelligence-Assisted Stimulated Raman Histology: New Frontiers in Vibrational Tissue Imaging.Cancers · 2024Review
- Virtual Staining of Nonfixed Tissue Histology.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2024Review
- [Intraoperative stimulated Raman histology for personalized brain tumor surgery].Chirurgie (Heidelberg, Germany) · 2024Review
- Article
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12 authors.
Funding
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Abstract
objectivesTo investigate whether in patients undergoing surgery for oral squamous cell carcinoma, stimulated Raman histology (SRH), in comparison with H&E-stained frozen sections, can provide accurate diagnoses regarding neoplastic tissue and sub-classification of non-neoplastic tissues. MATERIALS AND
methodsSRH, a technology based on Raman scattering, was applied to generate digital histopathologic images of 80 tissue samples obtained from 8 oral squamous cell carcinoma (OSCC) patients. Conventional H&E-stained frozen sections were then obtained from all 80 samples. All images/sections (SRH and H&E) were analyzed for squamous cell carcinoma, normal mucosa, connective tissue, muscle tissue, adipose tissue, salivary gland tissue, lymphatic tissue, and inflammatory cells. Agreement between SRH and H&E was evaluated by calculating Cohen's kappa. Accuracy of SRH compared to H&E was quantified by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) as well as area under the receiver operating characteristic curve (AUC).
resultsThirty-six of 80 samples were classified as OSCC by H&E-based diagnosis. Regarding the differentiation between neoplastic and non-neoplastic tissue, high agreement between H&E and SRH (kappa: 0.880) and high accuracy of SRH (sensitivity: 100%; specificity: 90.91%; PPV: 90.00%, NPV: 100%; AUC: 0.954) were demonstrated. For sub-classification of non-neoplastic tissues, SRH performance was dependent on the type of tissue, with high agreement and accuracy for normal mucosa, muscle tissue, and salivary glands.
conclusionSRH provides high accuracy in discriminating neoplastic and non-neoplastic tissues. Regarding sub-classification of non-neoplastic tissues in OSCC patients, accuracy varies depending on the type of tissue examined. CLINICAL RELEVANCE: This study demonstrates the potential of SRH for intraoperative imaging of fresh, unprocessed tissue specimens from OSCC patients without the need for sectioning or staining.
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