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INTRODUCTION: The risk of progression to esophageal adenocarcinoma in Barrett's esophagus (BE) increases with advancing degrees of dysplasia. There is a critical need to improve the diagnosis of BE dysplasia, given substantial interobserver variability and overcalls of dysplasia during manual community pathologist reads. We aimed to externally validate a previously cross-validated BE dysplasia diagnosis deep learning model (BEDDLM) that predicts dysplasia grade on whole slide images (WSIs). METHODS: We digitized nondysplastic BE (NDBE), low-grade (LGD), and high-grade dysplasia (HGD) histology slides from 3 external academic centers. A consensus read by 2 expert study pathologists was used as the criterion standard. Slide stain characteristics were normalized using cycle-generative adversarial networks. WSIs were assessed by BEDDLM using an ensemble approach, combining a “You Only Look Once” model followed by a ResNet101 classifier model. RESULTS: We included 489 WSIs. Consensus histopathology revealed 232 NDBE, 117 LGD, and 140 HGD WSIs. The mean age (SD) was 66.9 (11.4) years; 413 (84.7%) were men. Using the BEDDLM ensemble model, sensitivity and specificity for NDBE were 73.3% (95% confidence interval [CI]: 67.09%–78.85%) and 93.4% (95% CI: 89.62%–96.10%); for LGD, 84.6% (95% CI: 76.78%–90.62%) and 80.6% (95% CI: 76.26%–84.54%); and for HGD, 80.7% (95% CI: 73.19%–86.89%) and 94.8% (95% CI: 91.97%–96.91%), respectively. The F1 score was 0.81, 0 0.69, and 0.83 for NDBE, LGD, and HGD, respectively. DISCUSSION: Our externally validated deep learning model demonstrates substantial accuracy for the diagnosis of BE dysplasia grade on WSIs.

Goals: Develop quality indicators for ineffective esophageal motility (IEM). Background: IEM is identified in up to 20% of patients undergoing esophageal high-resolution manometry (HRM) based on the Chicago Classification. The clinical significance of this pattern is not established and management remains challenging. Study: Using RAND/University of California, Los Angeles Appropriateness Methods, we employed a modified-Delphi approach for quality indicator statement development. Quality indicators were proposed based on prior literature. Experts independently and blindly scored proposed quality statements on importance, scientific acceptability, usability, and feasibility in a 3-round iterative process. Results: All 10 of the invited esophageal experts in the management of esophageal diseases invited to participate rated 12 proposed quality indicator statements. In round 1, 7 quality indicators were rated with mixed agreement, on the majority of categories. Statements were modified based on panel suggestion, modified further following round 2’s virtual discussion, and in round 3 voting identified 2 quality indicators with comprehensive agreement, 4 with partial agreement, and 1 without any agreement. The panel agreed on the concept of determining if IEM is clinically relevant to the patient’s presentation and managing gastroesophageal reflux disease rather than the IEM pattern; they disagreed in all 4 domains on the use of promotility agents in IEM; and had mixed agreement on the value of a finding of IEM during anti-reflux surgical planning. Conclusion: Using a robust methodology, 2 IEM quality indicators were identified. These quality indicators can track performance when physicians identify this manometric pattern on HRM. This study further highlights the challenges met with IEM and the need for additional research to better understand the clinical importance of this manometric pattern.

Background Methods: The question prompt list content was derived through a modified Delphi process consisting of 3 rounds. In round 1, experts provided 5 answers to the prompts “What general questions should patients ask when given a new diagnosis of Barrett’s esophagus” and “What questions do I not hear patients asking, but given my expertise, I believe they should be asking?” Questions were reviewed and categorized into themes. In round 2, experts rated questions on a 5-point Likert scale. In round 3, experts rerated questions modified or reduced after the previous rounds. Only questions rated as “essential” or “important” were included in Barrett’s esophagus question prompt list (BE-QPL). To improve usability, questions were reduced to minimize redundancy and simplified to use language at an eighth-grade level (Fig. 1). Results: Twenty-one esophageal medical and surgical experts participated in both rounds (91% males; median age 52 years). The expert panel comprised of 33% esophagologists, 24% foregut surgeons, and 24% advanced endoscopists, with a median of 15 years in clinical practice. Most (81%), worked in an academic tertiary referral hospital. In this 3-round Delphi technique, 220 questions were proposed in round 1, 122 (55.5%) were accepted into the BE-QPL and reduced down to 76 questions (round 2), and 67 questions (round 3). These 67 questions reached a Flesch Reading Ease of 68.8, interpreted as easily understood by 13 to 15 years olds. Conclusions: With multidisciplinary input, we have developed a physician-derived BE-QPL to optimize patient-physician communication. Future directions will seek patient feedback to distill the questions further to a smaller number and then assess their usability.

AbstractBackgroundThe management of achalasia has improved due to diagnostic and therapeutic innovations. However, variability in care delivery remains and no established measures defining quality of care for this population exist. We aimed to use formal methodology to establish quality indicators for achalasia patients.MethodsQuality indicator concepts were identified from the literature, consensus guidelines and clinical experts. Using RAND/University of California, Los Angeles (UCLA) Appropriateness Method, experts in achalasia independently ranked proposed concepts in a two‐round modified Delphi process based on 1) importance, 2) scientific acceptability, 3) usability, and 4) feasibility. Highly valid measures required strict agreement (≧ 80% of panelists) in the range of 7–9 for across all four categories.Key ResultsThere were 17 experts who rated 26 proposed quality indicator topics. In round one, 2 (8%) quality measures were rated valid. In round two, 19 measures were modified based on panel suggestions, and experts rated 10 (53%) of these measures as valid, resulting in a total of 12 quality indicators. Two measures pertained to patient education and five to diagnosis, including discussing treatment options with risk and benefits and using the most recent version of the Chicago Classification to define achalasia phenotypes, respectively. Other indicators pertained to treatment options, such as the use of botulinum toxin for those not considered surgical candidates and management of reflux following achalasia treatment.Conclusions & InferencesUsing a robust methodology, achalasia quality indicators were identified, which can form the basis for establishing quality gaps and generating fully specified quality measures.

AbstractBackground and AimVolumetric laser endomicroscopy (VLE) is used to identify Barrett's esophagus (BE) dysplasia. Selection of a dysplastic region of interest (ROI) can be challenging due to feature variability across a large amount of data. The degree of agreement among VLE users in selecting a ROI has not been studied.MethodsHigh‐definition videos that divided a VLE scan from 18 patients with biopsy‐proven BE dysplasia into 1‐cm segments were reviewed using a four‐quadrant grid superimposed for systematic interpretation. VLE scans were selected based on image quality and appropriate visualization of BE epithelium. Four experienced VLE users rated each quadrant as dysplastic or non‐dysplastic. For quadrants rated as dysplastic, reviewers selected a single timeframe with representative features. A high‐degree of agreement among reviewers was defined as ≥75% agreement on the quadrant diagnosis and ≥50% agreement on selected timeframe (±2 s).ResultsThirty‐one videos, each 32 s in length, comprising 124 quadrants were reviewed. There was high‐agreement among reviewers in 99 (80%) quadrants, of which 68 (69%) were rated as dysplastic. Compared with quadrants rated as non‐dysplastic, ROIs of quadrants rated as dysplastic contained a higher number of epithelial glands (12.7 vs 1.2, P < 0.001) with atypical architecture (54 vs 1, P < 0.001). A statistically significant difference was observed between the signal intensity profiles of quadrants rated as dysplastic and quadrants rated as non‐dysplastic (P = 0.004).ConclusionThis study highlights that experienced VLE users can identify ROIs with high‐degree of agreement. Selected ROIs contained VLE features associated with BE dysplasia.