{"title":"高光谱成像在头颈部鳞状细胞癌和角棘瘤鉴别诊断中的应用。","authors":"Tianyi Hang, Danfeng Fan, Ansheng Jie, Zhengyuan Chen, Xiaoqing Yue, Wei Zhang","doi":"10.1002/jbio.202500358","DOIUrl":null,"url":null,"abstract":"<p><p>Accurate, label-free, non-destructive discrimination between head and neck squamous cell carcinoma (HNSCC) and keratoacanthoma (KA) remains challenging due to their overlapping morphology. We introduce a real-time, end-to-end hyperspectral imaging (HSI) workflow applied to 80 formalin-fixed, paraffin-embedded sections, each sampled with five 50 × 50-pixel ROIs and captured across 400-1000 nm to produce 128-band reflectance cubes. After reflectance calibration, Savitzky-Golay smoothing, and first-derivative preprocessing, a compact one-dimensional convolutional neural network achieved 87% accuracy, 93% sensitivity, 77% specificity, and AUC = 0.85 on a held-out test set. Spectral difference analysis revealed key biomarkers at the hemoglobin Q-band (630 nm) and OH overtone (917.5 nm), corresponding to vascular and extracellular matrix variations. This resource-efficient photonic platform enables rapid, automated \"optical biopsy\" without exogenous stains, offering scalable adjunctive diagnostics and a clear pathway toward intraoperative tissue classification.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e202500358"},"PeriodicalIF":2.3000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hyperspectral Imaging for the Differential Diagnosis of Squamous Cell Carcinoma and Keratoacanthoma of the Head and Neck.\",\"authors\":\"Tianyi Hang, Danfeng Fan, Ansheng Jie, Zhengyuan Chen, Xiaoqing Yue, Wei Zhang\",\"doi\":\"10.1002/jbio.202500358\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Accurate, label-free, non-destructive discrimination between head and neck squamous cell carcinoma (HNSCC) and keratoacanthoma (KA) remains challenging due to their overlapping morphology. We introduce a real-time, end-to-end hyperspectral imaging (HSI) workflow applied to 80 formalin-fixed, paraffin-embedded sections, each sampled with five 50 × 50-pixel ROIs and captured across 400-1000 nm to produce 128-band reflectance cubes. After reflectance calibration, Savitzky-Golay smoothing, and first-derivative preprocessing, a compact one-dimensional convolutional neural network achieved 87% accuracy, 93% sensitivity, 77% specificity, and AUC = 0.85 on a held-out test set. Spectral difference analysis revealed key biomarkers at the hemoglobin Q-band (630 nm) and OH overtone (917.5 nm), corresponding to vascular and extracellular matrix variations. This resource-efficient photonic platform enables rapid, automated \\\"optical biopsy\\\" without exogenous stains, offering scalable adjunctive diagnostics and a clear pathway toward intraoperative tissue classification.</p>\",\"PeriodicalId\":94068,\"journal\":{\"name\":\"Journal of biophotonics\",\"volume\":\" \",\"pages\":\"e202500358\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of biophotonics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/jbio.202500358\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of biophotonics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/jbio.202500358","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hyperspectral Imaging for the Differential Diagnosis of Squamous Cell Carcinoma and Keratoacanthoma of the Head and Neck.
Accurate, label-free, non-destructive discrimination between head and neck squamous cell carcinoma (HNSCC) and keratoacanthoma (KA) remains challenging due to their overlapping morphology. We introduce a real-time, end-to-end hyperspectral imaging (HSI) workflow applied to 80 formalin-fixed, paraffin-embedded sections, each sampled with five 50 × 50-pixel ROIs and captured across 400-1000 nm to produce 128-band reflectance cubes. After reflectance calibration, Savitzky-Golay smoothing, and first-derivative preprocessing, a compact one-dimensional convolutional neural network achieved 87% accuracy, 93% sensitivity, 77% specificity, and AUC = 0.85 on a held-out test set. Spectral difference analysis revealed key biomarkers at the hemoglobin Q-band (630 nm) and OH overtone (917.5 nm), corresponding to vascular and extracellular matrix variations. This resource-efficient photonic platform enables rapid, automated "optical biopsy" without exogenous stains, offering scalable adjunctive diagnostics and a clear pathway toward intraoperative tissue classification.