早期食管鳞状细胞癌浸润深度的放大内镜分类

2020-03-30 com0707 一泓小树林

日本食管学会于2011年提出了一种用于诊断和分期早期食管鳞状细胞癌的ME-NBI分类法。这项研究的目的是比较新分类与传统分类(Inoue分类和Arima的分类)。本项研究为前瞻性单中心研究,选择151

日本食管学会于2011年提出了一种用于诊断和分期早期食管鳞状细胞癌的ME-NBI分类法。这项研究的目的是比较新分类与传统分类(Inoue分类和Arima的分类)。本项研究为前瞻性单中心研究,选择151例经内镜或手术切除的156个早期食管鳞状细胞癌的患者。最初,ME-NBI图像是由三位经验丰富的内镜专家独立选择和审查的。间隔一段时间后分别进行白光成像。评估每种分类的诊断性能和观察者之间的一致性,评估影响新分类诊断的白光内镜结果。与Inoue分类法(0.512 vs. 0.349;P=0.02)和Arima分类法(0.512 vs. 0.279;P<0.01)相比,新分类法将浸润深度分为局限上皮(EP)/固有层(LPM)的特异性更高。与Arima分类法比较,敏感性降低(0.902 vs.1.000;P<0.01)。三个评价者的一致率(κ值)新分类为0.52,Inoue分类为0.50,Arima分类为0.23。在多变量分析中,WLI(白光内镜)的厚度是新分类的诊断准确性的独立因素(OR 3.23;95%CI:1.30~8.03)。在诊断SESCC的特异性方面,新分类优于常规分类。WLI厚度是影响新分类诊断效果的一个不利因素。


图1 白光内镜。内镜专家评估肉眼类型、颜色(红色(A)、白色(B))、颗粒(C)的存在或不存在、结节(D)、边缘隆起(E)和厚度(F)。


图2 日本食管学会提出的早期食管癌放大内镜 B型IPCL诊断标准,包括扩张、蛇形、口径不同及各血管形态不均一。B1:不同直径的扩张和扭曲的血管形成环(a)。B2:不同直径的扩张和扭曲的血管无环形成(b)。B3:直径为B2 3倍以上的异常血管(C)。B1、B2和B3的浸润深度分别为T1a-EP或T1a-LPM、T1a-MM或T1b-SM1和T1b-SM2或以深。

AVA定义为B型血管围绕的无血管区或血管杂乱的区域,按大小分为三组。AVA的大小定义为:0.5 mm以下为“小(D)”,0.5 mm至3.0 mm为“中(E)”,3.0 mm以上为“大(F)”。小中大AVA分别对应浸润深度为T1a-EP或T1a-LPM、T1a-MM或T1b-SM1、T1b-SM2及以上。(注释:AVA:无血管区;EP,上皮;LPM,黏膜固有层;MM,黏膜肌层;SM,黏膜下层)


图3 估计AVA的大小。ME-NBI时,最大放大倍率观察病灶时,屏角长度约为0.5 mm(A),一侧长度约为3 mm(B)。利用这个标准,我们可以估算出AVA的大小。(1比例尺相当于1 mm)。

表1 病例的特点及组织病理学特征

表2 新分类法与以往分类法诊断性能的比较

早期食管鳞状细胞癌的新分类和Inoue分类的比较中,对EP/LPM的敏感性没有显著差异(90.2% vs. 92.2%;P=0.62)。与Inoue分类相比,新分类对EP/LPM的特异性显著提高(51.2% vs. 34.9%;P=0.02)。在比较新分类法和Arima分类法时,新分类对EP/LPM的敏感性显著降低(90.2% vs. 100%;P<0.01),而新分类EP/LPM的特异性显著高于Arima分类(51.2% vs. 27.9%;P<0.01)。

表3 影响早期食管鳞状细胞癌浸润深度准确性的单因素和多因素分析

在多变量分析中,WLI病变厚度是影响新分类诊断性能的独立因素。也就是说WLI发现病变增厚,新的分类有低估浸润深度的倾向。因此,用新的分类方法(ME-NBI)来准确地描述病变的厚度可能是困难的。当我们看到一个病变增厚,应该首先是白光诊断,而不是ME-NBI(新分类)诊断。此外,使用其他方式,如上消化道系列或内镜超声检查,可能是有益的。由于ME-NBI仅观察到极浅的微血管,所以当SCC没有显著增厚时,这样的表现是准确的。另一方面,在厚度明显的情况下,表面微血管的变化可能不能准确地反映黏膜下层的浸润。

研究结论

本研究的结果表明,就早期食管鳞状细胞癌EP/LPM的深度诊断特异性而言,新分类法的诊断性能优于传统分类法。然而,在显示厚度的病变中,新的分类可能低估了早期食管鳞状细胞癌浸润深度。(DOI: 10.1093/dote/dox037)

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    2020-12-01 ms1000000133673730

    受益匪浅

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    2020-09-12 ms8000001853198032

    学习了

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    2020-04-01 zhouqu_8
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    2020-03-31 天地飞扬

    学习了

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