Prediction of appropriateness of local endoscopic treatment for high-grade dysplasia and early adenocarcinoma by EUS and histopathologic features

Buskens, Christianne J.; Westerterp, Marinke; Lagarde, Sjoerd M.; Bergman, Jacques J.G.H.M.; Kate, Fiebo J.W. ten; Lanschot, J. Jan B. van

doi:10.1016/s0016-5107(04)02017-6

Cited by 231 publications

(158 citation statements)

References 41 publications

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“…In der CROSS-Studie (CROSS: "chemoradiotherapy for oesophageal cancer followed by Surgery Study Group") wurden 368 Patienten mit resektablen Karzinomen des Ösophagus und des gastroösophagealen Übergangs zwischen einer Gruppe mit präoperativer Radiochemotherapie bis 41 Insgesamt wird aufgrund der besseren lokalen Kontrolle bei Karzinomen des distalen und mittleren Ösophagus ein multimodales Therapieschema mit Operation favorisiert. Bei Plattenepithelkarzinomen des proximalen Drittels wird wegen der höheren chirurgischen Morbidität sowie der postoperativ reduzierten Lebensqualität oft die definitive Radiochemotherapie bevorzugt.…”

Section: Studienresultateunclassified

Multimodale Therapie des Ösophaguskarzinoms

2017

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Section: Studienresultateunclassified

Multimodale Therapie des Ösophaguskarzinoms

2017

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“…If the biopsy results cannot provide effective support, the medical process will be tough for both patients and doctors. The image classification of early gastrointestinal carcinoma is the core of diagnosis [37]. Although noninvasive US tissue characterization could address this issue and reduce the need for repeated biopsies, this method still seems to be limited by its poor quantification capability.…”

Section: Discussionmentioning

confidence: 99%

High-order graph matching kernel for early carcinoma EUS image classification

Bai

Ren

Hancock

2015

Multimed Tools Appl

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Endoscopic ultrasonography (EUS) is limited by variability in the examiner's subjective interpretation to differentiate between normal, leiomyoma of esophagus and early esophageal carcinoma. By using information otherwise discarded by conventional EUS systems, quantitative spectral analysis of the raw pixels (picture elements) underlying EUS image enables lesions to be characterized more objectively. In this paper, we propose to represent texture features of early esophageal carcinoma in EUS images as a graph by expressing pixels as nodes and similarity between the gray-level or local features of the EUS image as edges. Then, similarity measurements such as a high-order graph matching kernel can be constructed so as to provide an objective quantification of the properties of the texture features of early esophageal carcinoma in EUS images. This is in terms of the topology and connectivity of the analyzed graphs. Because such properties are directly related to the structure of early esophageal carcinoma lesions in EUS images, they can be used as features for characterizing and classifying early esophageal carcinoma. Finally, we use a refined SVM model based on the new high-order graph matching kernel, resulting an optimal prediction of the types of esophageal lesions. A 10-fold cross validation strategy is employed to evaluate the classification performance. After multiple computer runs of the new kernel SVM model, the overall accuracy for the diagnosis between normal, leiomyoma of esophagus and early esophageal carcinoma was 93%. Moreover, for the diagnosis of early esophageal carcinoma, the average accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 89.4%, 94%, 95%, 89%, 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 2 Zhang et al.and 97% respectively. The area under all the three ROC curves were close to 1.

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“…The guidelines about lesions suitable for EMR, described above for HGD, also apply for superficial EAC [Ell et al 2000;Takeshita et al 1997]. Histological evaluation of EMR specimens provides information about the depth of invasion of the tumor, which may predict local lymph node metastases [Buskens et al 2004].…”

Section: Management Of Barrett's Esophagus With Intramucosal Carcinomamentioning

confidence: 99%

Review: Diagnosis and management of Barrett’s esophagus for the endoscopist

Garud

Keilin

Cai

et al. 2010

Therap Adv Gastroenterol

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In Barrett's esophagus, the stratified squamous epithelium lining the esophagus is replaced by specialized intestinal-type columnar epithelium. The prevalence of Barrett's esophagus has ranged from 0.9% to 4.5%. The rate of progression from Barrett's esophagus to esophageal adenocarcinoma is 0.5% per patient-year. Proton-pump inhibitors are the mainstay of symptom control in Barrett's patients. Nondysplastic Barrett's and Barrett's with low-grade dysplasia (LGD) are typically managed by periodic surveillance. Radiofrequency ablation is being evaluated as a modality for managing nondysplastic Barrett's and Barrett's with LGD. The options for the management of Barrett's patients with high-grade dysplasia (HGD) include endoscopic therapy, surgery, and intensive surveillance until biopsy reveals adenocarcinoma. Endoscopic therapy involves endoscopic mucosal resection (EMR) and ablation. More aggressive techniques such as endoscopic submucosal dissection and larger segment endoscopic mucosal resection are under study. In this review, we discuss the diagnosis and management of Barrett's esophagus. The recommendations from the major gastroenterologic societies and the current and investigational endoscopic modalities for the management of Barrett's esophagus with and without dysplasia are reviewed.

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Prediction of appropriateness of local endoscopic treatment for high-grade dysplasia and early adenocarcinoma by EUS and histopathologic features

Cited by 231 publications

References 41 publications

Multimodale Therapie des Ösophaguskarzinoms

Multimodale Therapie des Ösophaguskarzinoms

High-order graph matching kernel for early carcinoma EUS image classification

Review: Diagnosis and management of Barrett’s esophagus for the endoscopist

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