Diagnostic efficacy of the Japan NBI Expert Team classification with dual-focus magnification for colorectal tumors
Diagnostic efficacy of the Japan NBI Expert Team classification with dual-focus magnification for colorectal tumors
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日本NBI专家组双焦点放大分类对结直肠肿瘤的诊断效果
DOI：
10.1007/s00464-021-08863-7
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Itoi T
中科院分区：
文献类型：
--
作者：
Koyama Y;Fukuzawa M;Kono S;Madarame A;Morise T;Uchida K;Yamaguchi H;Sugimoto A;Nagata N;Kawai T;Takamaru H;Sekiguchi M;Yamada M;Sakamoto T;Matsuda T;Saito Y;Itoi T
背景和目标日本NBI专家组（JNET）分类是日本第一个使用放大窄带成像（NBI）的结直肠肿瘤统一分类标准。然而，双焦点放大 NBI (DF-JNET) 的 JNET 分类的诊断分层能力仍然不清楚。本研究的目的是在两个日本转诊中心验证 DF-JNET 对结直肠肿瘤的诊断分层能力。方法由三名经验丰富的内窥镜医师（其中包括一名也参与制定诊断标准的 JNET 原始成员）进行多中心回顾性图像评估研究。评估研究中使用了总共两幅图像，即针对 557 个连续病变中的每一个的一幅代表性非放大白光图像和一幅代表性 DF-NBI 图像。根据评估数据计算DF-JNET的诊断价值。结果DF-JNET 1型区分非肿瘤性和肿瘤性病变的敏感性、特异性、阳性和阴性预测值和准确性分别为78.1%、98.6%、89.1%、96.8%和95.9%；用于区分低度不典型增生和其他病变的 2A 型病变的比例分别为 98.0%、76.5%、94.9%、89.7% 和 94.1%；用于区分高度不典型增生和浅粘膜下浸润癌的 2B 型病变的比例分别为 43.5%、99.1%、66.7%、97.6% 和 96.8%；和 3 型病变区分深部粘膜下浸润性癌与其他癌的准确率分别为 83.3%、99.5%、62.5%、99.8% 和 99.3%。 结论 所有 DF-JNET 类型对结直肠肿瘤组织学预测的诊断准确率超过 90%。 DF-JNET 可能有助于适当的治疗选择，例如内窥镜切除或手术，不仅在日本，而且在光学变焦内窥镜的使用受到限制的西方国家也是如此。
Background and aimsThe Japan NBI Expert Team (JNET) classification is the first unified classification criteria for colorectal tumors using magnifying narrow-band imaging (NBI) in Japan. However, the diagnostic stratification ability of the JNET classification with dual-focus magnifying NBI (DF-JNET) has remained obscure. The aim of this study was to validate the diagnostic stratification ability of DF-JNET for colorectal tumors in two Japanese referral centers.MethodsA multicenter retrospective image evaluation study was conducted by three experienced endoscopists, including an original JNET member who was also involved in establishing the diagnostic criteria. A total of two images, namely, one representative non-magnified white light image and one representative DF-NBI image for each of the 557 consecutive lesions were used in the evaluation study. The diagnostic value of DF-JNET was calculated based on the evaluation data.ResultsThe sensitivity, specificity, positive and negative predictive values, and accuracy of DF-JNET Type 1 for differentiating between non-neoplastic and neoplastic lesions were 78.1%, 98.6%, 89.1%, 96.8%, and 95.9%, respectively; of Type 2A lesions for differentiating low-grade dysplasia from others were 98.0%, 76.5%, 94.9%, 89.7%, and 94.1%, respectively; of Type 2B lesions for differentiating high-grade dysplasia and shallow submucosal invasive carcinoma from others were 43.5%, 99.1%, 66.7%, 97.6%, and 96.8%, respectively; and of Type 3 lesions for differentiating deep submucosal invasive carcinoma from others were 83.3%, 99.5%, 62.5%, 99.8%, and 99.3%, respectively.ConclusionsAll DF-JNET types had an over 90% diagnostic accuracy for the histological prediction of colorectal tumors. DF-JNET might contribute to appropriate treatment choices, such as endoscopic resection or surgery, not only in Japan but also in Western countries in which the use of optical zoom endoscopy is limited.
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影响因子：
5.3
作者：
Singh, Rajvinder;Jayanna, Mahesh;Uedo, Noriya
通讯作者：
Uedo, Noriya
影响因子：
7.7
作者：
Sakamoto, Taku;Nakajima, Takeshi;Saito, Yutaka
通讯作者：
Saito, Yutaka
影响因子：
5.3
作者：
Murano, Tatsuro;Ikematsu, Hiroaki;Yano, Tomonori
通讯作者：
Yano, Tomonori
放大结肠镜检查诊断早期结直肠癌浸润深度
影响因子：
4.1
作者：
H. Ikehara;Yutaka Saito;T. Matsuda;T. Uraoka;Y. Murakami
通讯作者：
Y. Murakami
影响因子：
19.7
作者：
Kundel, HL;Polansky, M
通讯作者：
Polansky, M