Objectives

This study review focuses on a deep learning method for the detection of colorectal lesions in colonoscopy and AI support for detecting colorectal neoplasia, especially in flat lesions.

Data sources

We performed a systematic electric search with PubMed by using “colonoscopy”, “artificial intelligence”, and “detection”. Finally, nine articles about development and validation study and eight clinical trials met the review criteria.

Results

Development and validation studies showed that trained AI models had high accuracy—approximately 90% or more for detecting lesions. Performance was better in elevated lesions than in superficial lesions in the two studies. Among the eight clinical trials, all but one trial showed a significantly high adenoma detection rate in the CADe group than in the control group. Interestingly, the CADe group detected significantly high flat lesions than the control group in the seven studies.

Conclusion

Flat colorectal neoplasia can be detected by endoscopists who use AI.

中文翻译：

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人工智能检测扁平结直肠肿瘤：系统评价

目标

本研究综述侧重于一种在结肠镜检查中检测结直肠病变的深度学习方法，以及用于检测结直肠肿瘤，尤其是扁平病变的 AI 支持。

数据源

我们使用“结肠镜检查”、“人工智能”和“检测”在 PubMed 上进行了系统的电子搜索。最后，关于开发和验证研究的九篇文章和八项临床试验符合审查标准。

结果

开发和验证研究表明，经过训练的 AI 模型具有很高的准确率——大约 90% 或更多用于检测病变。在两项研究中，隆起病灶的表现优于浅表病灶。在八项临床试验中，除一项试验外，CADe 组的腺瘤检出率显着高于对照组。有趣的是，在七项研究中，CADe 组检测到的扁平病变明显高于对照组。

结论

使用 AI 的内窥镜医师可以检测到扁平结直肠肿瘤。