The development of new image enhancement modalities and improved endoscopic imaging quality have not led to increased adoption of resect-and-discard in routine practice. Studies have shown that endoscopists have the capacity to achieve quality thresholds to perform optical diagnosis, however, this has not led to acceptance of optical diagnosis as a replacement for pathology for diminutive (1-5mm) polyps. In recent years, Artificial Intelligence (AI)-based Computer Assisted Characterisation (CADx) of diminutive polyps has recently emerged as a strategy that could potentially represent a breakthrough technology to enable widespread adoption of resect-and-discard. Recent evidence suggests that pathology-based diagnosis is suboptimal, as polyp non-retrieval, fragmentation, sectioning errors, incorrect diagnosis as 'normal mucosa', and inter-pathologist variability limit the efficacy of pathology for the diagnosis of 1-5mm polyps. New paradigms in performing polyp diagnosis with or without AI have emerged to compete with pathology in terms of efficacy. Strategies, such as Autonomous AI, AI-assisted human diagnosis, AI-unassisted human diagnosis, and combined strategies have been proposed as potential paradigms for resect-and-discard, although further research is still required to determine the optimal strategy. Implementation studies with high patient acceptance, where polyps are truly being discarded without histologic diagnosis are paving the way towards normalizing resect-and-discard in routine clinical practice. Ultimately the largest challenges for CADx remain liability perceptions from endoscopists. The potential benefits of AI-based resect-and-discard are many, with very little potential harm. Real world implementation studies are therefore required to pave the way for the acceptability of such strategies in routine practice.

中文翻译：

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时代的光学诊断或人工智能。


新图像增强模式的开发和内窥镜成像质量的提高并未导致在常规实践中越来越多地采用 resec-and-discard。研究表明，内窥镜医师有能力达到质量阈值进行光学诊断，然而，这并未导致人们接受光学诊断作为微小 （1-5mm） 息肉病理学的替代品。近年来，基于人工智能 （AI） 的计算机辅助表征 （CADx） 的小息肉最近成为一种策略，可能代表一项突破性技术，使切除和丢弃得到广泛采用。最近的证据表明，基于病理学的诊断是次优的，因为息肉未修复、碎裂、切片错误、错误诊断为“正常粘膜”以及病理学家间的差异限制了病理学诊断 1-5 毫米息肉的有效性。在有或没有 AI 的情况下进行息肉诊断的新范式已经出现，以在疗效方面与病理学竞争。自主 AI、AI 辅助人类诊断、AI 非辅助人类诊断和组合策略等策略已被提议作为切除和丢弃的潜在范式，尽管仍需要进一步研究来确定最佳策略。患者接受度高的实施研究，其中息肉在没有组织学诊断的情况下真正被丢弃，这为常规临床实践中切除和丢弃正常化铺平了道路。归根结底，CADx 面临的最大挑战仍然是内窥镜医师的责任认知。基于 AI 的 resec-and-discard 的潜在好处很多，但潜在危害很小。 因此，需要进行真实世界的实施研究，为此类策略在常规实践中的可接受性铺平道路。