Wu Feng, Tan Wenxin, Liu Panpan, Qiao Weiguang, Xing Tongyin
Department of Critical Care Medicine, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Front Oncol. 2025 May 30;15:1534922. doi: 10.3389/fonc.2025.1534922. eCollection 2025.
Colorectal cancer (CRC), a leading global malignancy, underscores the need for precise endoscopic diagnosis. Blue Laser Imaging (BLI), a novel endoscopic technology enhancing mucosal surface visualization, combined with the Japan NBI Expert Team (JNET) classification, has shown promise in characterizing colorectal lesions. However, its diagnostic performance in Chinese populations and the impact of endoscopist experience remain underexplored.
In this multicenter, retrospective study, 131 colorectal sessile lesions were enrolled. The lesions' characteristics were assessed by both expert and trainee endoscopists, utilizing magnified BLI in combination with the JNET classification system to establish diagnostic predictions. This approach allowed for a comparative evaluation of diagnostic accuracy between experienced and less experienced practitioners.
Pathological diagnoses confirmed 2 hyperplastic/sessile serrated lesions (HP/SSL), and 70 low-grade dysplasia (LGD) among the 131 lesions. There were 36 high-grade dysplasia (HGD), 16 superficial submucosal invasive cancers (m-SMs), and 7 deep submucosal invasive cancers (SM-d) demonstrated. The performance metrics for expert and trainee endoscopists in evaluating JNET type 2A(LGD) were as follows: expert endoscopists demonstrated a sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of 93%, 93.3%, 94.3%, 91.8%, and 93.1%, respectively; trainee endoscopists showed a sensitivity, specificity, PPV, NPV, and accuracy of 64.6%, 63.5%, 72.9%, 54.1%, and 64.1%, respectively(p<0.01). For JNET type 2B(HGD/m-SMs), expert endoscopists exhibited a sensitivity, specificity, PPV, NPV, and accuracy of 88.2%, 91.3%, 86.5%, 92.4%, and 90.1%, respectively; trainee endoscopists showed a sensitivity, specificity, PPV, NPV, and accuracy of 59.6%, 73.4%, 73.4%, and 67.9%, respectively(p<0.01).
BLI-JNET provides high diagnostic accuracy for colorectal sessile lesions in expert endoscopists, validating its clinical utility. However, trainee endoscopists exhibited significantly low accuracy, underscoring the need for structured training. The proportion of HGD/m-SMs in JNET type 2B lesions within the Chinese cohort (88.2%) was significantly higher than that reported in Japanese data (Kobayashi et al., 2019), highlighting the need to optimize classification systems by incorporating region-specific characteristics.
结直肠癌(CRC)是全球主要的恶性肿瘤,凸显了精确内镜诊断的必要性。蓝色激光成像(BLI)是一种新型内镜技术,可增强黏膜表面可视化,与日本窄带成像专家团队(JNET)分类相结合,在结直肠病变特征描述方面显示出前景。然而,其在中国人群中的诊断性能以及内镜医师经验的影响仍未得到充分探索。
在这项多中心回顾性研究中,纳入了131例结直肠无蒂病变。由专家和实习内镜医师利用放大BLI结合JNET分类系统评估病变特征,以建立诊断预测。这种方法允许对经验丰富和经验较少的从业者之间的诊断准确性进行比较评估。
病理诊断证实131例病变中有2例增生性/无蒂锯齿状病变(HP/SSL)和70例低级别异型增生(LGD)。有36例高级别异型增生(HGD)、16例浅表黏膜下浸润癌(m-SMs)和7例深部黏膜下浸润癌(SM-d)。专家和实习内镜医师评估JNET 2A(LGD)类型的性能指标如下:专家内镜医师的敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)和准确性分别为93%、93.3%、94.3%、91.8%和93.1%;实习内镜医师的敏感性、特异性、PPV、NPV和准确性分别为64.6%、63.5%、72.9%、54.1%和64.1%(p<0.01)。对于JNET 2B(HGD/m-SMs)类型,专家内镜医师的敏感性、特异性、PPV、NPV和准确性分别为88.2%、91.3%、86.5%、92.4%和90.1%;实习内镜医师的敏感性、特异性、PPV、NPV和准确性分别为59.6%、73.4%、73.4%和67.9%(p<0.01)。
BLI-JNET为专家内镜医师诊断结直肠无蒂病变提供了高准确性,验证了其临床实用性。然而,实习内镜医师的准确性显著较低,凸显了结构化培训的必要性。中国队列中JNET 2B病变的HGD/m-SMs比例(88.2%)显著高于日本数据(Kobayashi等人,2019年)报道的比例,强调需要通过纳入区域特异性特征来优化分类系统。