Goyal Hemant, Mann Rupinder, Gandhi Zainab, Perisetti Abhilash, Ali Aman, Aman Ali Khizar, Sharma Neil, Saligram Shreyas, Tharian Benjamin, Inamdar Sumant
Department of Internal Medicine, The Wright Center for Graduate Medical Education, Scranton, PA 18505, USA.
Saint Agnes Medical Center, Fresno, CA 93720, USA.
J Clin Med. 2020 Oct 15;9(10):3313. doi: 10.3390/jcm9103313.
Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a "second look" for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization.
在全球范围内，结直肠癌是第三大最常被诊断出的恶性肿瘤。它导致了显著的死亡率和发病率，而通过有效的筛查测试进行早期诊断可以降低这些情况。将人工智能（AI）和计算机辅助检测（CAD）与筛查方法相结合已显示出结直肠癌筛查的良好结果。人工智能可以为内镜医师提供“二次检查”，以降低结肠镜检查期间息肉漏诊率。它还可以通过与结肠镜检查以及各种先进的内镜检查方式（如放大窄带成像、内镜细胞检查、共聚焦内镜显微镜检查、激光诱导荧光光谱检查和放大色素内镜检查）相结合，改善息肉的检测和特征描述。本描述性综述讨论了人工智能和计算机辅助检测在结直肠癌筛查、息肉检测和特征描述中的各种应用。
