Colorectal cancer remains a leading cause of cancer-related morbidity and mortality worldwide, despite the widespread uptake of population surveillance strategies. This is in part due to the persistent development of ‘interval colorectal cancers’, where patients develop colorectal cancer despite appropriate surveillance intervals, implying pre-malignant polyps were not resected at a prior colonoscopy. Multiple techniques have been developed to improve the sensitivity and accuracy of lesion detection and characterisation in an effort to improve the efficacy of colorectal cancer screening, thereby reducing the incidence of interval colorectal cancers. This article presents a comprehensive review of the transformative role of artificial intelligence (AI), which has recently emerged as one such solution for improving the quality of screening and surveillance colonoscopy. Firstly, AI-driven algorithms demonstrate remarkable potential in addressing the challenge of overlooked polyps, particularly polyp subtypes infamous for escaping human detection because of their inconspicuous appearance. Secondly, AI empowers gastroenterologists without exhaustive training in advanced mucosal imaging to characterise polyps with accuracy similar to that of expert interventionalists, reducing the dependence on pathologic evaluation and guiding appropriate resection techniques or referrals for more complex resections. AI in colonoscopy holds the potential to advance the detection and characterisation of polyps, addressing current limitations and improving patient outcomes. The integration of AI technologies into routine colonoscopy represents a promising step towards more effective colorectal cancer screening and prevention.
尽管人群监测策略已广泛应用，结直肠癌仍是全球癌症相关发病率和死亡率的主要原因之一。部分原因在于"间期结直肠癌"的持续发生，即患者在适当的监测间隔期内仍罹患结直肠癌，这意味着癌前息肉在既往结肠镜检查中未被切除。为提高结直肠癌筛查效能、降低间期癌发生率，多种提升病灶检测与特征识别灵敏度及准确性的技术应运而生。本文系统综述了人工智能在结肠镜检查中的变革性作用——这项新兴技术已成为提升筛查与监测结肠镜质量的有效解决方案。首先，人工智能算法在解决息肉漏诊难题方面展现出显著潜力，尤其针对因形态不典型而易于被肉眼忽略的特殊息肉亚型。其次，人工智能使未经高级黏膜成像系统培训的消化科医生能够实现与介入专家相当的息肉特征识别准确度，减少对病理评估的依赖，并指导采取恰当的切除技术或转诊进行复杂切除。人工智能结肠镜技术有望推动息肉检测与特征识别能力的进步，突破现有技术局限，改善患者预后。将人工智能技术整合到常规结肠镜检查中，标志着我们向更有效的结直肠癌筛查与预防迈出了关键一步。
肿瘤(癌症)患者之家