Sakamoto Taku, Cho Hourin, Saito Yutaka
Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan.
Clin Endosc. 2021 Jul;54(4):488-493. doi: 10.5946/ce.2021.157. Epub 2021 Jul 14.
Considering its contribution to reducing colorectal cancer morbidity and mortality, the most important task of colonoscopy is to find all existing polyps. Moreover, the accurate detection of existing polyps determines the risk of colorectal cancer morbidity and is an important factor in deciding the appropriate surveillance program for patients. Image-enhanced endoscopy is an easy-to-use modality with improved lesion detection. Linked color imaging (LCI) and blue laser/light imaging (BLI) are useful modalities for improving colonoscopy quality. Each mode has unique optical features; therefore, their intended use differs. LCI contributes to improved polyp detection due to its brightness and high color contrast between the lesion and normal mucosa, while BLI contributes to the characterization of detected polyps by evaluating the vessel and surface patterns of detected lesions. The proper use of these observation modes allows for more efficient endoscopic diagnosis. Moreover, recent developments in artificial intelligence will soon change the clinical practice of colonoscopy and this system will provide an efficient education modality for novice endoscopists.
考虑到结肠镜检查对降低结直肠癌发病率和死亡率的贡献,其最重要的任务是发现所有现存的息肉。此外,准确检测现存息肉可确定结直肠癌发病风险,并且是决定患者适当监测方案的重要因素。图像增强内镜检查是一种易于使用且能改善病变检测的方式。联动成像(LCI)和蓝光激光/光成像(BLI)是提高结肠镜检查质量的有用方式。每种模式都有独特的光学特征;因此,它们的预期用途有所不同。LCI因其亮度以及病变与正常黏膜之间的高颜色对比度而有助于改善息肉检测,而BLI则通过评估检测到的病变的血管和表面模式来有助于对检测到的息肉进行特征描述。正确使用这些观察模式可实现更高效的内镜诊断。此外,人工智能的最新进展将很快改变结肠镜检查的临床实践,并且该系统将为新手内镜医师提供一种高效的教育方式。
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