Feng Yunlu, Chang Xiaoyan, Zhao Yu, Wu Dong, Meng Zhilan, Wu Xi, Guo Tao, Jiang Qingwei, Zhang Shengyu, Wang Qiang, Yang Aiming
Department of Gastroenterology, Peking Union Medical College Hospital, Beijing, China.
Department of Pathology, Peking Union Medical College Hospital, Beijing, China.
Endosc Ultrasound. 2021 May-Jun;10(3):200-206. doi: 10.4103/eus.eus_35_20.
The diagnosis of malignant pancreatic cystic lesions (PCLs) remains challenging. Needle-based confocal laser endomicroscopy (nCLE) is an emerging promising imaging technique capable of real-time in vivo microscopic imaging of the cyst wall. We aimed to develop and validate a new nCLE diagnostic criteria for malignant mucinous cystic lesions (MLs).
Patients referred for EUS-FNA of indeterminate PCLs with at least one worrisome features according to Fukouka consensus were consecutively prospectively enrolled from July 2016 to July 2018. The final diagnosis was based on surgical histology, cytopathology, or committee consensus. Five investigators nonblindly reviewed nCLE features and identified potential diagnostic feature for malignant MLs, which was also reviewed in histology imaging accordingly. Furthermore, the nCLE diagnostic feature was evaluated with an independent nCLE dataset by two investigators in a double-blind manner.
A nCLE pattern of dark aggregates of neoplastic cells was identified as diagnostic for MLs, which was consistent with histological findings of irregular branching and budding in malignant MLs. An independent validation revealed that the accuracy, sensitivity, and specificity of this feature for the diagnosis of malignant MLs were 94%, 75%, and 100%, respectively.
The new nCLE criterion is promising for diagnosis of malignant MLs which warrants further confirmation in large cohort.
胰腺恶性囊性病变（PCLs）的诊断仍然具有挑战性。基于针的共聚焦激光内镜检查（nCLE）是一种新兴的有前景的成像技术，能够对囊肿壁进行实时体内显微成像。我们旨在开发并验证一种针对恶性黏液性囊性病变（MLs）的新的nCLE诊断标准。
2016年7月至2018年7月，连续前瞻性纳入因超声内镜引导下细针穿刺活检（EUS-FNA）而转诊的PCLs患者，这些患者根据福冈共识至少具有一项令人担忧的特征。最终诊断基于手术组织学、细胞病理学或委员会共识。五名研究人员非盲法审查nCLE特征，并确定恶性MLs的潜在诊断特征，同时在组织学成像中进行相应审查。此外，两名研究人员以双盲方式使用独立的nCLE数据集对nCLE诊断特征进行评估。
肿瘤细胞的暗聚集nCLE模式被确定为MLs的诊断特征，这与恶性MLs中不规则分支和芽生的组织学发现一致。独立验证显示，该特征诊断恶性MLs的准确性、敏感性和特异性分别为94%、75%和100%。
新的nCLE标准在诊断恶性MLs方面具有前景，需要在大型队列中进一步证实。
