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。

IF 2.3
Tianyi Hang, Danfeng Fan, Ansheng Jie, Zhengyuan Chen, Xiaoqing Yue, Wei Zhang
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引用次数: 0

摘要

由于头颈部鳞状细胞癌(HNSCC)和角棘瘤(KA)的形态重叠,对它们进行准确、无标记、非破坏性的区分仍然具有挑战性。我们将实时端到端高光谱成像(HSI)工作流程应用于80个福尔马林固定的石蜡包埋切片,每个切片使用5个50 × 50像素的roi进行采样,并在400-1000 nm范围内捕获,以产生128波段的反射立方体。经过反射率校准、Savitzky-Golay平滑和一阶导数预处理,紧凑的一维卷积神经网络在hold -out测试集上获得了87%的准确率、93%的灵敏度、77%的特异性和0.85的AUC。光谱差异分析显示血红蛋白q波段(630 nm)和O波段(917.5 nm)的关键生物标志物对应于血管和细胞外基质的变化。这种资源高效的光子平台可以实现快速、自动化的“光学活检”,无需外源性染色,提供可扩展的辅助诊断和明确的术中组织分类途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 OH 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.

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