Endoscopic acanthosis nigricans appearance: A novel specific marker for diagnosis of low‐grade intraepithelial neoplasia

Abstract

Background and AimAt present, there is no recognized diagnostic criteria for gastric low‐grade intraepithelial neoplasia (LGIN). The purpose of this study was to determine whether an “endoscopic acanthosis nigricans appearance (EANA)” could be a useful endoscopic marker for distinguishing LGIN lesions from peripheral non‐neoplastic tissues.MethodsA retrospective study was conducted on 638 cases of suspected superficial lesions with endoscopic images from white light endoscopy and magnifying endoscopy combined with narrow band imaging. According to the pathological results of accurate biopsies, those lesions were divided into three groups: a control group, an LGIN group, and an early gastric cancer (EGC) group.ResultsAccording to the presence of EANAs, the sensitivity, specificity, positive predictive value, and negative predictive value for differentiating between the LGIN and control groups were 24.8%, 97.3%, 78.3%, and 76.6%, respectively. The sensitivity (84.1%) and negative predictive value (92.4%) were significantly improved by combining EANA with types IV–VI pit pattern. The intervening part and mean gray value of glands, representing microsurface features and microvascular variation, were significantly larger or higher in EANA lesions than in the surrounding non‐neoplastic mucosa. LGIN with EANA was more likely to be present in lesions of type 0‐IIa. In addition, the prevalence of EANAs in EGC was 16.7%.ConclusionAn EANA could be used as an auxiliary indicator for a diagnosis of LGIN in suspected lesions. It could also play a potential assistive role in the diagnosis of EGC lesions.

Diagnosis and segmentation effect of the ME-NBI-based deep learning model on gastric neoplasms in patients with suspected superficial lesions - a multicenter study

“…To address this problem, a semantic segmentation-based CNN2 was developed to depict of the margins of GNLs. A preliminary endoscopic diagnosis of suspicious lesions was performed based on the characteristics of LGIN and EGC under ME-NBI as described in previous studies (6,(8)(9)(10)(11) and endoscopic experts labelled the extent of the lesions based on the pathology data. Combining the feature extraction network VGG-16 with the improved UNet structure, CNN2 can effectively extract the vascular and texture details of the shallow feature layers and the colour details of the deep feature layers from the lesion images, which can perform better in lesion segmentation.…”

“…In the ME-NBI images, the following two criteria should be met for labelling superficial gastric lesions as LGIN: (1) there are DLs that can be identified under ME-NBI; (2) the presence of EANA or types IV–VI pit pattern of the Sakaki classification or regular white opaque substance (WOS) or dense-type crypt opening ( 8 – 11 ). The following criteria should be met for labelling superficial gastric lesions as EGC: (1) an irregular MV pattern with DL and (or) (2) an irregular MS pattern with DL ( 6 ).…”

“…Previous studies have shown that MS and MV are often regular in LGIN lesions, while DL sometimes exists because of the differences in VS morphology between lesion mucosa and background mucosa ( 7 ). In our previous study, an auxiliary index with a high accuracy of identifying LGIN under ME-NBI was proposed – endoscopic acanthosis nigricans appearance (EANA) ( 8 ). For LGIN lesions of type 0-IIa, studies have shown that the morphological characteristics of dense-type crypt opening or regular white opaque substance (WOS) under ME-NBI can be helpful in distinguishing them from carcinomas ( 9 , 10 ).…”