scholarly journals Enlarged folds on endoscopic gastritis as a predictor for submucosal invasion of gastric cancers

2021 ◽  
Vol 13 (9) ◽  
pp. 426-436
Author(s):  
Osamu Toyoshima ◽  
Shuntaro Yoshida ◽  
Toshihiro Nishizawa ◽  
Akira Toyoshima ◽  
Kosuke Sakitani ◽  
...  
Keyword(s):  
Submucosal Invasion ◽  
Gastric Cancers

scholarly journals Multiple Early Gastric Cancers with Diffuse Cystic Malformation Mimicking Submucosal Invasion on Endoscopic Ultrasonography: Report of a Case

2011 ◽  
Vol 60 (1/2) ◽  
pp. 17-22
Author(s):  
Tamami NAKAMURA ◽  
Takaaki TSUSHIMI ◽  
Toshiki TANAKA ◽  
Yoshihiro TAKEMOTO ◽  
Eijiro HARADA ◽  
...  
Keyword(s):  
Endoscopic Ultrasonography ◽  
Submucosal Invasion ◽  
Gastric Cancers

scholarly journals CLINICOPATHOLOGICAL STUDY OF ERALY GASTRIC CANCERS WITH SUBMUCOSAL INVASION

1987 ◽  
Vol 48 (5) ◽  
pp. 584-588
Author(s):  
Yukio MIYAMOTO ◽  
Susumu OHWADA ◽  
Yoshibumi TANAHASHI ◽  
Tadakazu KAWAI ◽  
Masaru IZUO
Keyword(s):  
Submucosal Invasion ◽  
Gastric Cancers ◽  
Clinicopathological Study

scholarly journals Clinicopathological studies on the early gastric cancers. Especially on the degree of their submucosal invasion.

1989 ◽  
Vol 22 (3) ◽  
pp. 767-773
Author(s):  
Hiromi TANEMURA ◽  
Kuniyasu SHIMOKAWA ◽  
Shigetoyo SAJI ◽  
Tomohiko FURUTA ◽  
Shuji AZUMA ◽  
...  
Keyword(s):  
Submucosal Invasion ◽  
Gastric Cancers

Risk Factors for Lymph Node Metastasis from Gastric Cancers with Submucosal Invasion

2010 ◽  
Vol 17 (6) ◽  
pp. 1597-1604 ◽  
Author(s):  
Yusuke Tajima ◽  
Masahiko Murakami ◽  
Kimiyasu Yamazaki ◽  
Yuki Masuda ◽  
Shigeo Aoki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Submucosal Invasion ◽  
Gastric Cancers ◽  
Node Metastasis

scholarly journals Prediction of Submucosal Invasion for Gastric Neoplasms in Endoscopic Images Using Deep-Learning

2020 ◽  
Vol 9 (6) ◽  
pp. 1858
Author(s):  
Bum-Joo Cho ◽  
Chang Seok Bang ◽  
Jae Jun Lee ◽  
Chang Won Seo ◽  
Ju Han Kim
Keyword(s):  
Deep Learning ◽  
Endoscopic Resection ◽  
Area Under The Curve ◽  
Submucosal Invasion ◽  
Gastric Neoplasms ◽  
Invasion Depth ◽  
Gastric Cancers ◽  
Endoscopic Images ◽  
The Mean ◽  
External Test

Endoscopic resection is recommended for gastric neoplasms confined to mucosa or superficial submucosa. The determination of invasion depth is based on gross morphology assessed in endoscopic images, or on endoscopic ultrasound. These methods have limited accuracy and pose an inter-observer variability. Several studies developed deep-learning (DL) algorithms classifying invasion depth of gastric cancers. Nevertheless, these algorithms are intended to be used after definite diagnosis of gastric cancers, which is not always feasible in various gastric neoplasms. This study aimed to establish a DL algorithm for accurately predicting submucosal invasion in endoscopic images of gastric neoplasms. Pre-trained convolutional neural network models were fine-tuned with 2899 white-light endoscopic images. The prediction models were subsequently validated with an external dataset of 206 images. In the internal test, the mean area under the curve discriminating submucosal invasion was 0.887 (95% confidence interval: 0.849–0.924) by DenseNet−161 network. In the external test, the mean area under the curve reached 0.887 (0.863–0.910). Clinical simulation showed that 6.7% of patients who underwent gastrectomy in the external test were accurately qualified by the established algorithm for potential endoscopic resection, avoiding unnecessary operation. The established DL algorithm proves useful for the prediction of submucosal invasion in endoscopic images of gastric neoplasms.

scholarly journals Distinct Clinic-Pathological Features of Early Differentiated-Type Gastric Cancers afterHelicobacter pyloriEradication

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Noriyuki Horiguchi ◽  
Tomomitsu Tahara ◽  
Tomohiko Kawamura ◽  
Masaaki Okubo ◽  
Takamitsu Ishizuka ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Endoscopic Biopsy ◽  
Submucosal Invasion ◽  
Histological Diagnosis ◽  
Control Group ◽  
Pathological Features ◽  
Cancerous Tissue ◽  
Gastric Cancers ◽  
History Of ◽  
H Pylori

Background. Gastric cancer is discovered even after successful eradication ofH. pylori. We investigated clinic pathological features of early gastric cancers afterH. pylorieradication.Methods. 51 early gastric cancers (EGCs) from 44 patients diagnosed after successfulH. pylorieradication were included as eradication group. The clinic-pathological features were compared with that of 131 EGCs from 120 patients who did not have a history ofH. pylorieradication (control group).Results. Compared with control group, clinic-pathological features of eradication group were characterized as depressed (p<0.0001), reddish (p=0.0001), and smaller (p=0.0095) lesions, which was also confirmed in the comparison of six metachronous lesions diagnosed after initial ESD and subsequent successfulH. pylorieradication. Prevalence of both SM2 (submucosal invasion greater than 500 μm) and unexpected SM2 cases tended to be higher in eradication group (p=0.077, 0.0867, resp.). Prevalence of inconclusive diagnosis of gastric cancer during pretreatment biopsy was also higher in the same group (26.0% versus 1.6%,p<0.0001).Conclusions. Informative clinic pathological features of EGC afterH. pylorieradication are depressed, reddish appearances, which should be treated as a caution because histological diagnosis of cancerous tissue is sometimes difficult by endoscopic biopsy.

Microsatellite Instability and K-ras Mutations in Gastric Adenomas, with Reference to Associated Gastric Cancers

1999 ◽  
Vol 23 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Jun Isogaki ◽  
Kazuya Shinmura ◽  
Wang Yin ◽  
Tomio Arai ◽  
Kenji Koda ◽  
...  
Keyword(s):  
Microsatellite Instability ◽  
Ras Mutations ◽  
Gastric Cancers

Diagnosis of Gastric Cancers: Comparison of Conventional Radiography and Digital Radiography with a 4 Million-Pixel Charge-coupled Device

Radiology ◽  
2000 ◽  
Vol 214 (2) ◽  
pp. 497-502 ◽  
Author(s):  
Gen Iinuma ◽  
Kyosuke Ushio ◽  
Tsutomu Ishikawa ◽  
Shigeru Nawano ◽  
Ryuzou Sekiguchi ◽  
...  
Keyword(s):  
Digital Radiography ◽  
Conventional Radiography ◽  
Charge Coupled Device ◽  
Gastric Cancers
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