Browsing by Subject "Esophagus"

Now showing 1 - 3 of 3
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    'Artificial intelligence in Barrett's Esophagus'
    (Sage, 2021-10-12) Hamade, Nour; Sharma, Prateek; Medicine, School of Medicine
    Despite advances in endoscopic imaging modalities, there are still significant miss rates of dysplasia and cancer in Barrett's esophagus. Artificial intelligence (AI) is a promising tool that may potentially be a useful adjunct to the endoscopist in detecting subtle dysplasia and cancer. Studies have shown AI systems have a sensitivity of more than 90% and specificity of more than 80% in detecting Barrett's related dysplasia and cancer. Beyond visual detection and diagnosis, AI may also prove to be useful in quality control, streamlining clinical work, documentation, and lessening the administrative load on physicians. Research in this area is advancing at a rapid rate, and as the field expands, regulations and guidelines will need to be put into place to better regulate the growth and use of AI. This review provides an overview of the present and future role of AI in Barrett's esophagus.
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    Development and Validation of Web-Based Tool to Predict Lamina Propria Fibrosis in Eosinophilic Esophagitis
    (Wolters Kluwer, 2022) Hiremath, Girish; Sun, Lili; Correa, Hernan; Acra, Sari; Collins, Margaret H.; Bonis, Peter; Arva, Nicoleta C.; Capocelli, Kelley E.; Falk, Gary W.; King, Eileen; Gonsalves, Nirmala; Gupta, Sandeep K.; Hirano, Ikuo; Mukkada, Vincent A.; Martin, Lisa J.; Putnam, Philip E.; Spergel, Jonathan M.; Wechsler, Joshua B.; Yang, Guang-Yu; Aceves, Seema S.; Furuta, Glenn T.; Rothenberg, Marc E.; Koyama, Tatsuki; Dellon, Evan S.; Medicine, School of Medicine
    Introduction: Approximately half of esophageal biopsies from patients with eosinophilic esophagitis (EoE) contain inadequate lamina propria, making it impossible to determine the lamina propria fibrosis (LPF). This study aimed to develop and validate a web-based tool to predict LPF in esophageal biopsies with inadequate lamina propria. Methods: Prospectively collected demographic and clinical data and scores for 7 relevant EoE histology scoring system epithelial features from patients with EoE participating in the Consortium of Eosinophilic Gastrointestinal Disease Researchers observational study were used to build the models. Using the least absolute shrinkage and selection operator method, variables strongly associated with LPF were identified. Logistic regression was used to develop models to predict grade and stage of LPF. The grade model was validated using an independent data set. Results: Of 284 patients in the discovery data set, median age (quartiles) was 16 (8-31) years, 68.7% were male patients, and 93.4% were White. Age of the patient, basal zone hyperplasia, dyskeratotic epithelial cells, and surface epithelial alteration were associated with presence of LPF. The area under the receiver operating characteristic curve for the grade model was 0.84 (95% confidence interval: 0.80-0.89) and for stage model was 0.79 (95% confidence interval: 0.74-0.84). Our grade model had 82% accuracy in predicting the presence of LPF in an external validation data set. Discussion: We developed parsimonious models (grade and stage) to predict presence of LPF in esophageal biopsies with inadequate lamina propria and validated our grade model. Our predictive models can be easily used in the clinical setting to include LPF in clinical decisions and determine its effect on treatment outcomes.
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    Mucosal Microbiota Associated With Eosinophilic Esophagitis and Eosinophilic Gastritis
    (Wiley, 2023) Furuta, Glenn T.; Fillon, Sophie A.; Williamson, Kayla M.; Robertson, Charles E.; Stevens, Mark J.; Aceves, Seema S.; Arva, Nicoleta C.; Chehade, Mirna; Collins, Margaret H.; Davis, Carla M.; Dellon, Evan S.; Falk, Gary W.; Gonsalves, Nirmala; Gupta, Sandeep K.; Hirano, Ikuo; Khoury, Paneez; Leung, John; Martin, Lisa J.; Menard-Katcher, Paul; Mukkada, Vincent A.; Peterson, Kathryn; Spergel, Jonathan M.; Wechsler, Joshua B.; Yang, Guang-Yu; Rothenberg, Marc E.; Harris, J. Kirk; Pediatrics, School of Medicine
    Objective: The aim of the study was to determine the mucosal microbiota associated with eosinophilic esophagitis (EoE) and eosinophilic gastritis (EoG) in a geographically diverse cohort of patients compared to controls. Methods: We conducted a prospective study of individuals with eosinophilic gastrointestinal disease (EGID) in the Consortium of Eosinophilic Gastrointestinal Disease Researchers, including pediatric and adult tertiary care centers. Eligible individuals had clinical data, mucosal biopsies, and stool collected. Total bacterial load was determined from mucosal biopsy samples by quantitative polymerase chain reaction (PCR). Community composition was determined by small subunit rRNA gene amplicons. Results: One hundred thirty-nine mucosal biopsies were evaluated corresponding to 93 EoE, 17 EoG, and 29 control specimens (18 esophageal) from 10 sites across the United States. Dominant community members across disease activity differed significantly. When comparing EoE and EoG with controls, the dominant taxa in individuals with EGIDs was increased ( Streptococcus in esophagus; Prevotella in stomach). Specific taxa were associated with active disease for both EoE ( Streptococcus , Gemella ) and EoG ( Leptotrichia ), although highly individualized communities likely impacted statistical testing. Alpha diversity metrics were similar across groups, but with high variability among individuals. Stool analyses did not correlate with bacterial communities found in mucosal biopsy samples and was similar in patients and controls. Conclusions: Dominant community members ( Streptococcus for EoE, Prevotella for EoG) were different in the mucosal biopsies but not stool of individuals with EGIDs compared to controls; taxa associated with EGIDs were highly variable across individuals. Further study is needed to determine if therapeutic interventions contribute to the observed community differences.