Dataset Information

A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus.

ABSTRACT: Barrett's esophagus (BE) patients are routinely screened for high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) through endoscopic screening, during which multiple esophageal tissue samples are removed for histological analysis. We propose a computational method called the multistage clonal expansion for EAC (MSCE-EAC) screening model that is used for screening BE patients in silico to evaluate the effects of biopsy sampling, diagnostic sensitivity, and treatment on disease burden. Our framework seamlessly integrates relevant cell-level processes during EAC development with a spatial screening process to provide a clinically relevant model for detecting dysplastic and malignant clones within the crypt-structured BE tissue. With this computational approach, we retain spatio-temporal information about small, unobserved tissue lesions in BE that may remain undetected during biopsy-based screening but could be detected with high-resolution imaging. This allows evaluation of the efficacy and sensitivity of current screening protocols to detect neoplasia (dysplasia and early preclinical EAC) in the esophageal lining. We demonstrate the clinical utility of this model by predicting three important clinical outcomes: (1) the probability that small cancers are missed during biopsy-based screening, (2) the potential gains in neoplasia detection probabilities if screening occurred via high-resolution tomographic imaging, and (3) the efficacy of ablative treatments that result in the curative depletion of metaplastic and neoplastic cell populations in BE in terms of the long-term impact on reducing EAC incidence.

SUBMITTER: Curtius K

PROVIDER: S-EPMC4441439 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus.

Curtius Kit K Hazelton William D WD Jeon Jihyoun J Luebeck E Georg EG

PLoS computational biology 20150522 5

Barrett's esophagus (BE) patients are routinely screened for high grade dysplasia (HGD) and esophageal adenocarcinoma (EAC) through endoscopic screening, during which multiple esophageal tissue samples are removed for histological analysis. We propose a computational method called the multistage clonal expansion for EAC (MSCE-EAC) screening model that is used for screening BE patients in silico to evaluate the effects of biopsy sampling, diagnostic sensitivity, and treatment on disease burden. O ...[more]

PMID: 26001209

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Project description:Early detection of esophageal neoplasia enables curative endoscopic therapy, but the current diagnostic standard of care has low sensitivity because early neoplasia is often inconspicuous with conventional white-light endoscopy. Here, we hypothesized that spectral endoscopy could enhance contrast for neoplasia in surveillance of patients with Barrett's esophagus. A custom spectral endoscope was deployed in a pilot clinical study of 20 patients to capture 715 in vivo tissue spectra matched with gold standard diagnosis from histopathology. Spectral endoscopy was sensitive to changes in neovascularization during the progression of disease; both non-dysplastic and neoplastic Barrett's esophagus showed higher blood volume relative to healthy squamous tissue (P = 0.001 and 0.02, respectively), and vessel radius appeared larger in neoplasia relative to non-dysplastic Barrett's esophagus (P = 0.06). We further developed a deep learning algorithm capable of classifying spectra of neoplasia versus non-dysplastic Barrett's esophagus with high accuracy (84.8% accuracy, 83.7% sensitivity, 85.5% specificity, 78.3% positive predictive value, and 89.4% negative predictive value). Exploiting the newly acquired library of labeled spectra to model custom color filter sets identified a potential 12-fold enhancement in contrast between neoplasia and non-dysplastic Barrett's esophagus using application-specific color filters compared with standard-of-care white-light imaging (perceptible color difference = 32.4 and 2.7, respectively). This work demonstrates the potential of endoscopic spectral imaging to extract vascular properties in Barrett's esophagus, to classify disease stages using deep learning, and to enable high-contrast endoscopy. SIGNIFICANCE: The results of this pilot first-in-human clinical trial demonstrate the potential of spectral endoscopy to reveal disease-associated vascular changes and to provide high-contrast delineation of neoplasia in the esophagus. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/81/12/3415/F1.large.jpg.

Project description:Background & aimsBarrett's esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC). Endoscopic eradication therapy (EET) can be effective in eradicating BE and related neoplasia and has greater risk of harms and resource use than surveillance endoscopy. This clinical practice guideline aims to inform clinicians and patients by providing evidence-based practice recommendations for the use of EET in BE and related neoplasia.MethodsThe Grading of Recommendations Assessment, Development and Evaluation framework was used to assess evidence and make recommendations. The panel prioritized clinical questions and outcomes according to their importance for clinicians and patients, conducted an evidence review, and used the Evidence-to-Decision Framework to develop recommendations regarding the use of EET in patients with BE under the following scenarios: presence of (1) high-grade dysplasia, (2) low-grade dysplasia, (3) no dysplasia, and (4) choice of stepwise endoscopic mucosal resection (EMR) or focal EMR plus ablation, and (5) endoscopic submucosal dissection vs EMR. Clinical recommendations were based on the balance between desirable and undesirable effects, patient values, costs, and health equity considerations.ResultsThe panel agreed on 5 recommendations for the use of EET in BE and related neoplasia. Based on the available evidence, the panel made a strong recommendation in favor of EET in patients with BE high-grade dysplasia and conditional recommendation against EET in BE without dysplasia. The panel made a conditional recommendation in favor of EET in BE low-grade dysplasia; patients with BE low-grade dysplasia who place a higher value on the potential harms and lower value on the benefits (which are uncertain) regarding reduction of esophageal cancer mortality could reasonably select surveillance endoscopy. In patients with visible lesions, a conditional recommendation was made in favor of focal EMR plus ablation over stepwise EMR. In patients with visible neoplastic lesions undergoing resection, the use of either endoscopic mucosal resection or endoscopic submucosal dissection was suggested based on lesion characteristics.ConclusionsThis document provides a comprehensive outline of the indications for EET in the management of BE and related neoplasia. Guidance is also provided regarding the considerations surrounding implementation of EET. Providers should engage in shared decision making based on patient preferences. Limitations and gaps in the evidence are highlighted to guide future research opportunities.

Project description:Background & aimsGuidelines suggest endoscopic screening of individuals who are at increased risk for Barrett's esophagus (BE) and esophageal adenocarcinoma. Tools based on clinical factors are available for identifying patients at risk, but only some have been validated. We aimed to compare and validate available tools.MethodsWe performed a prospective study of 1241 patients, ages 40 to 79 years, presenting either for their first esophagogastroduodenoscopy (EGD) or their first endoscopic therapy of early neoplastic BE, from April 2015 through June 2018. We calculated risk scores for 6 previously published tools (the Gerson, Locke, Thrift, Michigan BE pREdiction Tool [M-BERET], Nord-Trøndelag Health Study [HUNT], and Kunzmann tools). We also investigated the accuracy of frequency and duration of gastroesophageal reflux disease (GERD), using data from a randomly selected 50% of patients undergoing their first EGD. We compared the ability of all these tools to discriminate patients with BE and early neoplasia from patients without BE, using findings from endoscopy as the reference standard.ResultsBE was detected in 81 of 1152 patients during their first EGD (7.0%). GERD symptoms alone identified patients with BE with an area under the receiver operating characteristic curve (AuROC) of 0.579. All of the tools were more accurate in identifying patients with BE than the frequency and duration of GERD (AuROC for GERD, 0.579 vs range for other tools, 0.660-0.695), and predicted risk correlated well with observed risk (calibration). The AUROCs of the HUNT tool (0.796), the M-BERET (0.773), and the Kunzmann tool (0.763) were comparable in discriminating between patients with early neoplasia (n = 94) vs no BE. Each tool was more accurate in discriminating BE with early neoplasia than GERD frequency and duration alone (AuROC, 0.667; P < .01).ConclusionsThe HUNT, M-BERET, and Kunzmann tools identify patients with BE with AuROC values ranging from 0.665 to 0.695, and discriminate patients with early neoplasia from patients without BE with AuROC values ranging from 0.763 to 0.796. These tools are more accurate than frequency and duration of GERD in identifying individuals at risk for neoplastic BE.

Dataset Information

A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus.

Publications

A Multiscale Model Evaluates Screening for Neoplasia in Barrett's Esophagus.

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