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Focused Review Series: Endoscopic Submucosal Dissection for Colorectal Tumors
Estimation of Invasion Depth: The First Key to Successful Colorectal ESD
Bo-In Lee, Takahisa Matsuda
Clin Endosc 2019;52(2):100-106.   Published online March 27, 2019
AbstractAbstract PDFPubReaderePub
Colorectal tumors with superficial submucosal invasion, which cannot be removed by snaring, are one of the most optimal indications for colorectal endoscopic submucosal dissection (ESD). Therefore, estimation of the invasion depth is the first key to successful colorectal ESD. Although estimation of the invasion depth based on the gross morphology may be useful in selected cases, its diagnostic accuracy could not reach the clinical requirement. The Japan Narrow-band Imaging (NBI) Expert Team (JNET) classification of NBI magnifying endoscopy findings is a useful method for histologic prediction and invasion depth estimation. However, magnifying chromoendoscopy is still necessary for JNET type 2B lesions to reach a satisfactory diagnostic accuracy. Endocytoscopy with artificial intelligence is a promising technology in invasion depth estimation; however, more data are needed for its clinical application.


Citations to this article as recorded by  
  • Comparison of two pathological processing methods for large endoscopic submucosal dissection (ESD) specimens
    Zixiang Yu, Dongxian Jiang, Wen Huang, Rongkui Luo, Haixing Wang, Jieakesu Su, Jia Liu, Chen Xu, Yingyong Hou
    Journal of Clinical Pathology.2023; 76(11): 757.     CrossRef
  • Endoscopic submucosal dissection for colorectal polyps: outcome determining factors
    Chi Woo Samuel Chow, Tak Lit Derek Fung, Pak Tat Chan, Kam Hung Kwok
    Surgical Endoscopy.2023; 37(2): 1293.     CrossRef
  • Endoscopic management of patients with high-risk colorectal colitis–associated neoplasia: a Delphi study
    Michiel T.J. Bak, Eduardo Albéniz, James E. East, Nayantara Coelho-Prabhu, Noriko Suzuki, Yutaka Saito, Takayuki Matsumoto, Rupa Banerjee, Michal F. Kaminski, Ralf Kiesslich, Emmanuel Coron, Annemarie C. de Vries, C. Janneke van der Woude, Raf Bisschops,
    Gastrointestinal Endoscopy.2023; 97(4): 767.     CrossRef
  • Detecting colorectal lesions with image-enhanced endoscopy: an updated review from clinical trials
    Mizuki Nagai, Sho Suzuki, Yohei Minato, Fumiaki Ishibashi, Kentaro Mochida, Ken Ohata, Tetsuo Morishita
    Clinical Endoscopy.2023; 56(5): 553.     CrossRef
  • Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer
    Feng Liang, Shu Wang, Kai Zhang, Tong-Jun Liu, Jian-Nan Li
    World Journal of Gastrointestinal Oncology.2022; 14(1): 124.     CrossRef
  • Linear-array EUS improves the accuracy of predicting deep submucosal invasion in non-pedunculated rectal polyps compared with radial EUS: a prospective observational study
    Zhixian Lan, Kangyue Sun, Yuchen Luo, Haiyan Hu, Wei Zhu, Wen Guo, Jing Wen, Wenting Mi, Junsheng Chen, Xiang Chen, Venkata Akshintala, Ying Huang, Side Liu, Yue Li
    Surgical Endoscopy.2021; 35(4): 1734.     CrossRef
  • Deep learning analysis for the detection of pancreatic cancer on endosonographic images: a pilot study
    Ryosuke Tonozuka, Takao Itoi, Naoyoshi Nagata, Hiroyuki Kojima, Atsushi Sofuni, Takayoshi Tsuchiya, Kentaro Ishii, Reina Tanaka, Yuichi Nagakawa, Shuntaro Mukai
    Journal of Hepato-Biliary-Pancreatic Sciences.2021; 28(1): 95.     CrossRef
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    Eun Hye Oh, Nayoung Kim, Sung Wook Hwang, Sang Hyoung Park, Dong-Hoon Yang, Byong Duk Ye, Seung-Jae Myung, Suk-Kyun Yang, Chang Sik Yu, Jin Cheon Kim, Jeong-Sik Byeon
    Gastrointestinal Endoscopy.2021; 94(2): 394.     CrossRef
  • The impact of transanal local excision of early rectal cancer on completion rectal resection without neoadjuvant chemoradiotherapy: a systematic review
    R. Zinicola, R. Nascimbeni, R. Cirocchi, G. Gagliardi, N. Cracco, M. Giuffrida, G. Pedrazzi, G. A. Binda
    Techniques in Coloproctology.2021; 25(9): 997.     CrossRef
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  • Artificial intelligence in gastrointestinal endoscopy: general overview
    Ahmad El Hajjar, Jean-François Rey
    Chinese Medical Journal.2020; 133(3): 326.     CrossRef
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    Evelien Dekker, Britt B. S. L. Houwen, Ignasi Puig, Marco Bustamante-Balén, Emmanuel Coron, Daniela E. Dobru, Roman Kuvaev, Helmut Neumann, Gavin Johnson, Pedro Pimentel-Nunes, David S. Sanders, Mario Dinis-Ribeiro, Marianna Arvanitakis, Thierry Ponchon,
    Endoscopy.2020;[Epub]     CrossRef
  • Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped
    Emanuele Sinagra, Matteo Badalamenti, Marcello Maida, Marco Spadaccini, Roberta Maselli, Francesca Rossi, Giuseppe Conoscenti, Dario Raimondo, Socrate Pallio, Alessandro Repici, Andrea Anderloni
    World Journal of Gastroenterology.2020; 26(39): 5911.     CrossRef
  • The Role of Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Disorders
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    Diagnostics.2020; 11(1): 18.     CrossRef
  • Endoscopic imaging techniques for detecting early colorectal cancer
    Ignasi Puig, Carlos Mármol, Marco Bustamante
    Current Opinion in Gastroenterology.2019; 35(5): 432.     CrossRef
  • 7,506 View
  • 335 Download
  • 18 Web of Science
  • 18 Crossref
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Original Article
Diagnostic Accuracy and Interobserver Agreement in Predicting the Submucosal Invasion of Colorectal Tumors Using Gross Findings, Pit Patterns, and Microvasculatures
Hye Jung Choi, Bo-In Lee, Hwang Choi, Kyu Yong Choi, Sang-Woo Kim, Joo Yong Song, Jeong Seon Ji, Byung-Wook Kim
Clin Endosc 2013;46(2):168-171.   Published online March 31, 2013
AbstractAbstract PDFPubReaderePub

Depth of invasion is one of the most important factors for establishing treatment strategy for colorectal tumors.


Three blinded experts reviewed electronic photos and video clips of 33 early colorectal cancer-like lesions. They estimated the depth of invasion based on conventional white light endoscopy (CWE), magnifying chromoendoscopy (MCE), and magnifying narrow band imaging endoscopy (MNE).


The lesions included nine mucosal low-grade neoplasias, 16 mucosal high grade neoplasias, and eight carcinomas with invasion to the submucosal layer or beyond. The diagnostic accuracy for submucosal invasion by CWE ranged from 67% to 82%, while those by MCE and MNE ranged from 85% to 88% and 85% to 88%, respectively. The diagnostic accuracy significantly differed between CWE and MCE (p=0.034) and between CWE and MNE (p=0.039). The kappa values for CWE, MCE, and MNE among the endoscopists were 0.564, 0.673, and 0.673, respectively.


The estimation of submucosal invasion for early colorectal cancer-like lesions based on MCE or MNE is more accurate than CWE. MCE and MNE were demonstrated to have substantial agreement for predicting submucosal invasion.


Citations to this article as recorded by  
  • Estimation of Invasion Depth: The First Key to Successful Colorectal ESD
    Bo-In Lee, Takahisa Matsuda
    Clinical Endoscopy.2019; 52(2): 100.     CrossRef
  • Comparison of endoscopic ultrasonography and magnifying endoscopy for assessment of the invasion depth of shallow gastrointestinal neoplasms: a systematic review and meta-analysis
    Zhang Tao, Chen Yan, He Zhao, Jiawei Tsauo, Xiaowu Zhang, Bing Qiu, Yanqing Zhao, Xiao Li
    Surgical Endoscopy.2017; 31(12): 4923.     CrossRef
  • Use of confocal laser endomicroscopy with a fluorescently labeled fatty acid to diagnose colorectal neoplasms
    Feihong Deng, Yuan Fang, Zhiyong Shen, Wei Gong, Tao Liu, Jing Wen, Wanling Zhang, Xianjun Zhu, Hui Zhong, Tong Wang, Fachao Zhi, Biao Nie
    Oncotarget.2017; 8(35): 58934.     CrossRef
  • Higher net change of index of hemoglobin values between colon polyp and nonpolyp mucosa correlates with the presence of an advanced colon adenoma
    Wei‐Chun Cheng, Hsiu‐Chi Cheng, Po‐Jun Chen, Jui‐Wen Kang, Er‐Hsiang Yang, Bor‐Shyang Sheu, Wei‐Ying Chen
    Advances in Digestive Medicine.2016; 3(4): 161.     CrossRef
  • Brief Education on Microvasculature and Pit Pattern for Trainees Significantly Improves Estimation of the Invasion Depth of Colorectal Tumors
    Joon Sung Kim, Bo-In Lee, Hwang Choi, Bong Koo Kang, Jong In Kim, Hae Mi Lee, Eun-Joo Im, Byung-Wook Kim, Sang-Woo Kim, Myung-Gyu Choi, Kyu Yong Choi
    Gastroenterology Research and Practice.2014; 2014: 1.     CrossRef
  • Clinical Usefulness of Magnifying Chromoendoscopy and Magnifying Narrow Band Imaging Endoscopy for Predicting the Submucosal Invasion of Early Colorectal Cancers
    Kwang An Kwon, Yang Suh Ku
    Clinical Endoscopy.2013; 46(2): 113.     CrossRef
  • 7,206 View
  • 44 Download
  • 6 Crossref
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Diagnostic Accuracy of Computed Tomography for the Lymph Node Staging of Endoscopically Resectable Early Gastric Cancer
Tae-Hoon Oh, M.D., Ban-Suck Lee, M.D., Min-Geun Kim, M.D., Jeong Soo Ahn, M.D., Tae Joo Jeon, M.D., Dong Dae Seo, M.D., Won Choong Choi, M.D., Won Chang Shin, M.D., Myeong-Ja Jeong, M.D.* and Hyun-Jung Kim, M.D.
Korean J Gastrointest Endosc 2008;37(2):90-96.   Published online August 30, 2008
AbstractAbstract PDF
Background/Aims: Accurate staging of the lymph nodes (LNs) before endoscopic mucosal resection (EMR) is important. We evaluated the accuracy of CT for LN staging in patients the endoscopically resectable early gastric cancer (EGC). Methods: The medical records of 155 EGCs patients who had undergone an operation were analyzed. The pre-operatively performed multidetector CT scans and the post-operative histopathologic findings were reviewed for comparing the LN staging with that using the Japanese classification system. Endoscopically resectable EGC was defined as EGC without LN metastasis and also the EGC that satisfied the EMR criteria according to the Japanese guideline. Results: The diagnostic efficacy of CT for LN staging of all the enrolled EGC patients was as follow: accuracy 65.2%, overstaging rate 29.7%, understaging rate 5.2%. The overall accuracy and the overstaging rate of CT for LN staging of endoscopically resectable EGC were as follows: EGC without LN metastasis [69.8% (97/139), 30.2% (42/139)], EGC satisfying extended criteria [72.5% (58/80), 27.5% (22/80)] and EGC satisfying limited criteria [79.2% (19/24), 20.8% (5/24)]. The accuracy of the EMR criteria for predicting node negative EGC were as follows: the extended criteria 98.8% (79/80), the limited criteria 100% (24/24). Conclusions: Our study showed that prediction of LN metastasis before EMR according to CT staging had limited value due to the tendency of overestimation. Therefore, we should preferentially consider the treatment strategy according to the EMR criteria. (Korean J Gastrointest Endosc 2008;37:90-96)
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  • 8 Download
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