Advancements and limitations of image-enhanced endoscopy in colorectal lesion diagnosis and treatment selection: A narrative review

IF 1.4 Q4 GASTROENTEROLOGY & HEPATOLOGY
DEN open Pub Date : 2025-05-08 DOI:10.1002/deo2.70141
Taku Sakamoto, Shintaro Akiyama, Toshiaki Narasaka, Kiichiro Tuchiya
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引用次数: 0

Abstract

Colorectal cancer (CRC) is a leading cause of cancer-related mortality, highlighting the need for early detection and accurate lesion characterization. Traditional white-light imaging has limitations in detecting lesions, particularly those with flat morphology or minimal color contrast with the surrounding mucosa. It also struggles to distinguish neoplastic from non-neoplastic lesions. These limitations led to the development of image-enhanced endoscopy (IEE). Image-enhanced endoscopy modalities such as narrow-band imaging, blue laser imaging, linked color imaging, and texture and color enhancement imaging enhance mucosal surface and vascular pattern visualization, thereby improving lesion detection and characterization.

In contrast, red dichromatic imaging is primarily designed to enhance the visibility of deep blood vessels, making it particularly useful during therapeutic endoscopies, such as identifying bleeding sources and monitoring post-treatment hemostasis. Although IEE enhances lesion detection and characterization, it remains limited in assessing submucosal invasion depth, which is a key factor in treatment decisions. Endoscopic submucosal dissection requires accurate prediction of invasion depth; however, IEE mainly reflects superficial features. Endoscopic ultrasound and artificial intelligence-assisted diagnostics have emerged as complementary techniques for improving depth assessment and lesion classification. Additionally, IEE plays a critical role in detecting ulcerative colitis-associated neoplasia (UCAN), which often presents with a flat morphology and indistinct borders. High-definition chromoendoscopy and IEE modalities enhance detection; however, inflammation-related changes limit diagnostic accuracy. Artificial intelligence and molecular biomarkers may improve UCAN diagnosis. This review examines the role of IEE in lesion detection and treatment selection, its limitations, and complementary techniques such as endoscopic ultrasound and artificial intelligence. We also explored pit pattern diagnosis using crystal violet staining and discussed emerging strategies to refine colorectal cancer screening and management.

Abstract Image

图像增强内窥镜在结直肠病变诊断和治疗选择中的进展和局限性:叙述性综述
结直肠癌(CRC)是癌症相关死亡的主要原因,强调了早期发现和准确病变特征的必要性。传统的白光成像在检测病变方面有局限性,特别是那些形态平坦或与周围粘膜颜色对比最小的病变。它也很难区分肿瘤和非肿瘤病变。这些限制导致了图像增强内窥镜(IEE)的发展。图像增强内镜方式,如窄带成像、蓝色激光成像、链接彩色成像、纹理和彩色增强成像,增强了粘膜表面和血管模式的可视化,从而提高了病变的检测和表征。相比之下,红色二色成像主要用于增强深血管的可见性,使其在治疗性内窥镜检查中特别有用,例如识别出血来源和监测治疗后止血。虽然IEE增强了病变的检测和表征,但它在评估粘膜下浸润深度方面仍然有限,而这是决定治疗的关键因素。内镜下粘膜剥离需要准确预测浸润深度;然而,IEE主要反映的是表面特征。内镜超声和人工智能辅助诊断已经成为改善深度评估和病变分类的补充技术。此外,IEE在检测溃疡性结肠炎相关肿瘤(UCAN)中起着关键作用,UCAN通常表现为平坦的形态和模糊的边界。高清彩色内窥镜和IEE模式增强检测;然而,炎症相关的改变限制了诊断的准确性。人工智能和分子生物标志物可能会改善UCAN的诊断。本文综述了IEE在病变检测和治疗选择中的作用,其局限性,以及内镜超声和人工智能等辅助技术。我们还探讨了用结晶紫染色诊断窝型,并讨论了改进结直肠癌筛查和管理的新策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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