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用于皮肤癌即时床旁诊断的新兴技术。

Emerging Technologies for Timely Point-of-Care Diagnostics of Skin Cancer.

作者信息

Thomas Jarrod L, Heagerty Adrian H M, Goldberg Oppenheimer Pola

机构信息

Advanced Nanomaterials Structures and Applications Laboratories School of Chemical Engineering College of Engineering and Physical Sciences University of Birmingham Edgbaston Birmingham B15 2TT UK.

Healthcare Technologies Institute Institute of Translational Medicine Mindelsohn Way Birmingham B15 2TH UK.

出版信息

Glob Chall. 2025 Mar 18;9(5):2400274. doi: 10.1002/gch2.202400274. eCollection 2025 May.

DOI:10.1002/gch2.202400274
PMID:40352638
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12065104/
Abstract

Skin cancer is a global health crisis and a leading cause of morbidity and mortality worldwide. A leading factor of malignancy remains the UV radiation, driving various biomolecular changes. With shifting population behaviors, deficiency in screening programs and reliance on self-presentation, climate change and the ageing world populace, global incidents have been surging alarmingly. There is an urgent need for new technologies to achieve timely intervention through rapid and accurate diagnostics of skin cancer. Raman spectroscopy has been emerging as a highly promising analytical technology for diagnostic applications, poised to outpace the current costly, invasive and slow procedures, frequently hindered by varying sensitivity, specificity and lack of portability. Herein, complex and intricate progress are overviewed and consolidated across medical and engineering disciplines with a focus on the latest advances in the traditional and emerging skin cancer diagnostics. Methods detecting structural and chemical responses are categorized along with emerging chemo-biophysical sensing techniques. Particular attention is drawn to Raman spectroscopy, as a non-invasive, rapid and accurate sensing of molecular fingerprints in dermatological matrix with an additional focus on artificial intelligence, as a decision support tool collectively, laying the platform toward development and rapid translation of point-of-care diagnostic technologies for skin cancer to real-world applications.

摘要

皮肤癌是一场全球健康危机,也是全球发病和死亡的主要原因。恶性肿瘤的一个主要因素仍然是紫外线辐射,它会引发各种生物分子变化。随着人群行为的改变、筛查项目的不足、对自我表现的依赖、气候变化以及全球人口老龄化,全球皮肤癌发病率一直在惊人地飙升。迫切需要新技术,通过对皮肤癌进行快速准确的诊断来实现及时干预。拉曼光谱已成为一种极具前景的诊断分析技术,有望超越目前成本高昂、具有侵入性且缓慢的诊断程序,这些程序常常因灵敏度、特异性各异以及缺乏便携性而受到阻碍。在此,我们概述并整合了医学和工程学科的复杂进展,重点关注传统和新兴皮肤癌诊断技术的最新进展。检测结构和化学反应的方法与新兴的化学生物物理传感技术一起进行了分类。特别关注拉曼光谱,它能够对皮肤基质中的分子指纹进行非侵入性、快速且准确的传感,另外还特别关注人工智能,将其作为一种决策支持工具,共同为皮肤癌即时诊断技术的开发和快速转化为实际应用奠定基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/724d0ac89866/GCH2-9-2400274-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/85d0e76825b0/GCH2-9-2400274-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/61458eb8d756/GCH2-9-2400274-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/4dc2677e11c9/GCH2-9-2400274-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/1278fb32ba04/GCH2-9-2400274-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/9e48ea532a60/GCH2-9-2400274-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/c0cdb05b57c6/GCH2-9-2400274-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/1db0732557a8/GCH2-9-2400274-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/724d0ac89866/GCH2-9-2400274-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/85d0e76825b0/GCH2-9-2400274-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/61458eb8d756/GCH2-9-2400274-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/4dc2677e11c9/GCH2-9-2400274-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/1278fb32ba04/GCH2-9-2400274-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/9e48ea532a60/GCH2-9-2400274-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/c0cdb05b57c6/GCH2-9-2400274-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/1db0732557a8/GCH2-9-2400274-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d79/12065104/724d0ac89866/GCH2-9-2400274-g003.jpg

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本文引用的文献

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Validation of optimised intracranial spectroscopic probe for instantaneous in-situ monitoring and classification of traumatic brain injury.优化颅内光谱探头的验证,用于创伤性脑损伤的即时现场监测和分类。
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Improving skin cancer detection by Raman spectroscopy using convolutional neural networks and data augmentation.
利用卷积神经网络和数据增强技术通过拉曼光谱改善皮肤癌检测
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