Systematic assessment with I-SCAN magnification endoscopy and acetic acid improves dysplasia detection in patients with Barrett’s esophagus

Lipman, Gideon; Bisschops, Raf; Sehgal, Vinay; Ortiz-Fernández-Sordo, Jacobo; Sweis, Rami; Esteban, José M.; Hamoudi, Rifat; Banks, Matthew; Ragunath, Krish; Lovat, Laurence; Haidry, Rehan

doi:10.1055/s-0043-113441

Cited by 25 publications

(31 citation statements)

References 28 publications

(25 reference statements)

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“…Our results in terms of diagnostic performance, with sensitivity of 90%, specificity 83% and NPV 71%, in identifying HGD or more advanced histology are slightly lower compared to the previously reported for other virtual chromoendoscopy modalities. NBI has been widely assessed and there are results available from a previous metaanalysis (16) and the recently published systematic review and meta-analysis by the ASGE Technology Committee (17). They reported a sensitivity ranging from 91% to 94%, specificity between 95% and 97.5% and NPV 94% for NBI discriminating lesions with HGD (16,17).…”

Section: Discussionmentioning

confidence: 99%

“…There are limited data on other electronic chromoendoscopy techniques such as I-SCAN or FICE, which have been only evaluated in a few small studies (17)(18)(19) and their results were not included in the recent meta-analysis carried out by the ASGE Technology Committee. A recently published international multicenter study leaded by University College London reported an accuracy of 83% analyzing the dysplasia detection with I-SCAN magnification and acetic acid (17).…”

Section: Discussionmentioning

confidence: 99%

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Evaluation of a novel infra-red endoscopy system in the assessment of early neoplasia in Barretts esophagus: pilot study from a single center

Ortiz-Fernández-Sordo

Sami

Mansilla-Vivar

et al. 2017

Diseases of the Esophagus

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Infrared endoscopy (IRE) has been shown to be useful in detecting submucosal (SM) invasion in early gastric cancer. Its role in the endoscopic assessment of Barrett's neoplasia has not been reported to date. We aimed in this study to evaluate the role of IRE in the detection and characterization of early neoplastic lesions within Barrett's esophagus (BE). The secondary aim was to explore its usefulness for the assessment of the presence of submucosal invasion in these early neoplastic Barrett's lesions. We included in the study patients with dysplastic BE who were referred to our institution for endoscopic therapy of a previously diagnosed early Barrett's neoplasia. An examination with white light high resolution endoscopy (HRE) and near IRE after intravenous injection of indocyanine green was performed for all patients using an infrared endoscope prototype. Staining on IRE and correlation with final histological staging by endoscopic mucosal resection/surgery or histological diagnosis on mapping biopsies was analyzed. A total of 23 patients were enrolled in our study: 17 of them with 19 visible lesions and 6 patients with flat BE and no lesions. Staining on IRE was noted in 18 cases: 17 (94%) had at least high grade dysplasia (HGD). No stain was noted in 7 cases: final histology was

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Evaluation of a novel infra-red endoscopy system in the assessment of early neoplasia in Barretts esophagus: pilot study from a single center

Ortiz-Fernández-Sordo

Sami

Mansilla-Vivar

et al. 2017

Diseases of the Esophagus

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“…BOOST (ISRCTN 58235785) was a case-control study undertaken in four European hospitals (two in the UK in London and Nottingham, one in Leuven, Belgium, and one in Madrid, Spain), with patients recruited in 2013-15, that used enhanced endoscopic techniques to target highrisk lesions that occur in patients with Barrett's oesophagus. 22 Clinical and demographic data were collected. Controls were patients referred by their primary care physician with suspected oesophageal cancer who had neither Barrett's oesophagus nor oesophageal adenocarcinoma and were analogous to those in BEST2.…”

Section: Implications Of All the Available Evidencementioning

confidence: 99%

Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach

Rosenfeld

Graham

Jevons

et al. 2020

The Lancet Digital Health

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Background Screening for Barrett's oesophagus relies on endoscopy, which is invasive and few who undergo the procedure are found to have the condition. We aimed to use machine learning techniques to develop and externally validate a simple risk prediction panel to screen individuals for Barrett's oesophagus. MethodsIn this prospective study, machine learning risk prediction in Barrett's oesophagus (MARK-BE), we used data from two case-control studies, BEST2 and BOOST, to compile training and validation datasets. From the BEST2 study, we analysed questionnaires from 1299 patients, of whom 880 (67·7%) had Barrett's oesophagus, including 40 with invasive oesophageal adenocarcinoma, and 419 (32·3%) were controls. We randomly split (6:4) the cohort using a computer algorithm into a training dataset of 776 patients and a testing dataset of 523 patients. We compiled an external validation cohort from the BOOST study, which included 398 patients, comprising 198 patients with Barrett's oesophagus (23 with oesophageal adenocarcinoma) and 200 controls. We identified independently important diagnostic features of Barrett's oesophagus using the machine learning techniques information gain and correlationbased feature selection. We assessed multiple classification tools to create a multivariable risk prediction model. Internal validation of the model using the BEST2 testing dataset was followed by external validation using the BOOST external validation dataset. From these data we created a prediction panel to identify at-risk individuals.Findings The BEST2 study included 40 diagnostic features. Of these, 19 added information gain but after correlationbased feature selection only eight showed independent diagnostic value including age, sex, cigarette smoking, waist circumference, frequency of stomach pain, duration of heartburn and acidic taste, and taking antireflux medication, of which all were associated with increased risk of Barrett's oesophagus, except frequency of stomach pain, with was inversely associated in a case-control population. Logistic regression offered the highest prediction quality with an area under the receiver-operator curve (AUC) of 0·87 (95% CI 0·84-0·90; sensitivity set at 90%; specificity of 68%). In the testing dataset, AUC was 0·86 (0·83-0·89; sensitivity set at 90%; specificity of 65%). In the external validation dataset, the AUC was 0·81 (0·74-0·84; sensitivity set at 90%; specificity of 58%). Interpretation Our diagnostic model offers valid predictions of diagnosis of Barrett's oesophagus in patients withsymptomatic gastro-oesophageal reflux disease, assisting in identifying who should go forward to invasive confirmatory testing. Our predictive panel suggests that overweight men who have been taking antireflux medication for a long time might merit particular consideration for further testing. Our risk prediction panel is quick and simple to administer but will need further calibration and validation in a prospective study in primary care.

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“…abnormalities [11][12][13] . However, most studies to date have validated these classification systems in expert endoscopists working in high-volume Barrett's referral centers; as such they may not be a true reflection of a general population of endoscopists in smaller centers performing routine Barrett's surveillance.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Virtual chromoendoscopy by using optical enhancement improves the detection of Barrett’s esophagus–associated neoplasia

Everson

Lovat

Graham

et al. 2019

Gastrointestinal Endoscopy

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Background and Aims The Seattle protocol for endoscopic Barrett's esophagus surveillance samples a small proportion of the mucosal surface area-risking a potentially high miss rate of early neoplastic lesions. We assess if the new iScan Optical Enhancement system (OE, Pentax) improves the detection of early BE associated neoplasia compared with high definition white light endoscopy (HD-WLE) in both expert and trainee endoscopists to target sampling of suspicious areas. Such a system may both improve early neoplasia detection and reduce the need for random biopsies. Methods 41 patients undergoing endoscopic BE surveillance from Jan 2016-Nov 2017 were recruited from 3 international referral centers. Matched still images in both HD-WLE (n=130) and iScan OE (n=132) were obtained from endoscopic examinations. Two experts, unblinded to the videos and histology, delineated known neoplasia, forming a consensus criterion standard. 7 expert and 7 trainee endoscopists marked one position per image where they would expect a target biopsy to identify dysplastic tissue. The same expert panel then reviewed magnification images and using a previously validated classification system attempted to classify mucosa as dysplastic or non-dysplastic based on the mucosal and vascular patterns observed on magnification endoscopy. Diagnostic accuracy, sensitivity, specificity, NPV, and PPV were calculated. Improvements in dysplasia detection in HD-WLE vs OE and interobserver agreement (IA) were assessed by multilevel logistic regression analysis and Krippendorff's alpha, respectively. Improvements in diagnostic performance were expressed as an odds ratio between the odds of an improvement in OE, compared with the odds of an improvement in WLE Results

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Systematic assessment with I-SCAN magnification endoscopy and acetic acid improves dysplasia detection in patients with Barrett’s esophagus

Cited by 25 publications

References 28 publications

Evaluation of a novel infra-red endoscopy system in the assessment of early neoplasia in Barretts esophagus: pilot study from a single center

Evaluation of a novel infra-red endoscopy system in the assessment of early neoplasia in Barretts esophagus: pilot study from a single center

Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach

Virtual chromoendoscopy by using optical enhancement improves the detection of Barrett’s esophagus–associated neoplasia

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