Djinbachian Roupen, Dubé Anne-Julie, von Renteln Daniel
Faculty of Medicine, University of Montreal, Montreal, Canada.
Montreal University Hospital Research Center (CRCHUM), Montreal, Canada.
Curr Treat Options Gastroenterol. 2019 Mar;17(1):99-114. doi: 10.1007/s11938-019-00220-x.
Optical diagnosis of diminutive colorectal polyps has been recently proposed as an alternative to histopathologic diagnosis. Recent developments in imaging techniques, new classification systems, and the use of artificial intelligence have allowed for increased viability of optical diagnosis. This review provides an up-to-date overview of optical diagnosis recommendations, classifications, outcomes, and recent developments.
There are currently seven major classification systems and three major society recommendations for quality benchmarks for optical diagnosis of diminutive polyps. The NICE classification has been extensively studied and meets quality benchmarks for most imaging techniques but does not allow for the diagnosis of sessile serrated polyps (SSPs). The SIMPLE classification has met quality benchmarks for NBI and i-Scan and allows for the diagnosis of SSPs. Other classification systems need to be further studied to validate effectiveness. Computer-assisted diagnosis of colorectal polyps is a very promising recent development with first studies showing that society-recommended quality benchmarks for real-time colonoscopies on patients are being met. Limitations include a non-negligible percentage of failure to diagnose, low specificity, and low number of real-time diagnostic studies. More research needs to be performed to further understand the value of artificial intelligence for optical polyp diagnosis. Optical diagnosis of diminutive colorectal polyps is currently a viable strategy for experienced endoscopists using validated classifications and imaging-enhanced endoscopy. Artificial intelligence-based diagnosis could make optical diagnosis widely applicable but is currently in its early developmental stage.
近期有人提出将微小结直肠息肉的光学诊断作为组织病理学诊断的替代方法。成像技术、新分类系统以及人工智能的应用等方面的最新进展,提高了光学诊断的可行性。本综述提供了光学诊断建议、分类、结果及最新进展的最新概述。
目前有七种主要的分类系统以及三项主要学会关于微小息肉光学诊断质量基准的建议。NICE分类已得到广泛研究,符合大多数成像技术的质量基准,但无法诊断无蒂锯齿状息肉(SSP)。SIMPLE分类符合窄带成像(NBI)和智能电子分光技术(i-Scan)的质量基准,且能诊断SSP。其他分类系统有待进一步研究以验证其有效性。结直肠息肉的计算机辅助诊断是一项非常有前景的最新进展,初步研究表明已达到学会推荐的对患者进行实时结肠镜检查的质量基准。其局限性包括不可忽视的漏诊率、低特异性以及实时诊断研究数量较少。需要开展更多研究以进一步了解人工智能在光学息肉诊断中的价值。对于经验丰富的内镜医师而言,使用经过验证的分类方法和成像增强内镜技术,微小结直肠息肉的光学诊断目前是一种可行的策略。基于人工智能的诊断可能会使光学诊断得到广泛应用,但目前尚处于早期发展阶段。