Matsuo Ken, Takedatsu Hidetoshi, Mukasa Michita, Sumie Hiroaki, Yoshida Hikaru, Watanabe Yasutomo, Akiba Jun, Nakahara Keita, Tsuruta Osamu, Torimura Takuji
Ken Matsuo, Hidetoshi Takedatsu, Michita Mukasa, Hiroaki Sumie, Hikaru Yoshida, Yasutomo Watanabe, Keita Nakahara, Osamu Tsuruta, Takuji Torimura, Division of Gastroenterology, Department of Medicine, Kurume University School of Medicine, Fukuoka 830-0011, Japan.
World J Gastroenterol. 2015 Jan 28;21(4):1268-74. doi: 10.3748/wjg.v21.i4.1268.
To determine whether the endoscopic findings of depressed-type early gastric cancers (EGCs) could precisely predict the histological type.
Ninety depressed-type EGCs in 72 patients were macroscopically and histologically identified. We evaluated the microvascular (MV) and mucosal surface (MS) patterns of depressed-type EGCs using magnifying endoscopy (ME) with narrow-band imaging (NBI) (NBI-ME) and ME enhanced by 1.5% acetic acid, respectively. First, depressed-type EGCs were classified according to MV pattern by NBI-ME. Subsequently, EGCs unclassified by MV pattern were classified according to MS pattern by enhanced ME (EME) images obtained from the same angle.
We classified the depressed-type EGCs into the following 2 MV patterns using NBI-ME: a fine-network pattern that indicated differentiated adenocarcinoma (25/25, 100%) and a corkscrew pattern that likely indicated undifferentiated adenocarcinoma (18/23, 78.3%). However, 42 of the 90 (46.7%) lesions could not be classified into MV patterns by NBI-ME. These unclassified lesions were then evaluated for MS patterns using EME, which classified 33 (81.0%) lesions as MS patterns, diagnosed as differentiated adenocarcinoma. As a result, 76 of the 90 (84.4%) lesions were matched with histological diagnoses using a combination of NBI-ME and EME.
A combination of NBI-ME and EME was useful in predicting the histological type of depressed-type EGC.
确定凹陷型早期胃癌（EGC）的内镜检查结果能否准确预测组织学类型。
对72例患者的90处凹陷型EGC进行了宏观和组织学鉴定。我们分别使用带窄带成像的放大内镜（ME）（NBI-ME）和1.5%醋酸增强的ME评估凹陷型EGC的微血管（MV）和黏膜表面（MS）形态。首先，根据NBI-ME的MV形态对凹陷型EGC进行分类。随后，对于未通过MV形态分类的EGC，根据从同一角度获得的增强ME（EME）图像的MS形态进行分类。
我们使用NBI-ME将凹陷型EGC分为以下两种MV形态：提示分化型腺癌的细网状形态（25/25，100%）和可能提示未分化腺癌的螺旋状形态（18/23，78.3%）。然而，90处病变中有42处（46.7%）无法通过NBI-ME分为MV形态。然后使用EME对这些未分类的病变进行MS形态评估，其中33处病变（81.0%）被分类为MS形态，诊断为分化型腺癌。结果，90处病变中有76处（84.4%）通过NBI-ME和EME的联合使用与组织学诊断相匹配。
NBI-ME和EME的联合使用有助于预测凹陷型EGC的组织学类型。
