Hyperspectral imaging and evaluation of surgical margins: where do we stand?

IF 1.9 4区 医学 Q2 OTORHINOLARYNGOLOGY
David Pertzborn, Ayman Bali, Anna Mühlig, Ferdinand von Eggeling, Orlando Guntinas-Lichius
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引用次数: 0

Abstract

Purpose of review: To highlight the recent literature on the use of hyperspectral imaging (HSI) for cancer margin evaluation ex vivo, for head and neck cancer pathology and in vivo during head and neck cancer surgery.

Recent findings: HSI can be used ex vivo on unstained and stained tissue sections to analyze head and neck tissue and tumor cells in combination with machine learning approaches to analyze head and neck cancer cell characteristics and to discriminate the tumor border from normal tissue. Data on in vivo applications during head and neck cancer surgery are preliminary and limited. Even now an accuracy of 80% for tumor versus nonneoplastic tissue classification can be achieved for certain tasks, within the current in vivo settings.

Summary: Significant progress has been made to introduce HSI for ex vivo head and neck cancer pathology evaluation and for an intraoperative use to define the tumor margins. To optimize the accuracy for in vivo use, larger HSI databases with annotations for head and neck cancer are needed.

高光谱成像和手术边缘评估:我们的现状如何?
综述目的:重点介绍高光谱成像(HSI)在头颈部癌症病理学和头颈部癌症手术中用于体外癌症边缘评估的最新文献:高光谱成像技术可用于未染色和染色组织切片的体外分析,结合机器学习方法分析头颈部癌细胞特征,并区分肿瘤边缘和正常组织,从而分析头颈部组织和肿瘤细胞。头颈癌手术中的活体应用数据是初步的,也是有限的。总结:在将 HSI 用于头颈部癌症病理评估和术中确定肿瘤边缘方面取得了重大进展。为了优化体内使用的准确性,需要更大的头颈癌注释人脸图像特征数据库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
96
审稿时长
6-12 weeks
期刊介绍: Current Opinion in Otolaryngology & Head and Neck Surgery is a bimonthly publication offering a unique and wide ranging perspective on the key developments in the field. Each issue features hand-picked review articles from our team of expert editors. With eleven disciplines published across the year – including maxillofacial surgery, head and neck oncology and speech therapy and rehabilitation – every issue also contains annotated references detailing the merits of the most important papers.
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