Wallace, Michael B.

Abstract Background Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. We aimed to identify the top implementation research priorities. Methods An established modified Delphi approach for research priority setting was used. Fifteen international experts, including endoscopists and translational computer scientists/engineers, from nine countries participated in an online survey over 9 months. Questions related to AI implementation in colonoscopy were generated as a long-list in the first round, and then scored in two subsequent rounds to identify the top 10 research questions. Results The top 10 ranked questions were categorized into five themes. Theme 1: clinical trial design/end points (4 questions), related to optimum trial designs for polyp detection and characterization, determining the optimal end points for evaluation of AI, and demonstrating impact on interval cancer rates. Theme 2: technological developments (3 questions), including improving detection of more challenging and advanced lesions, reduction of false-positive rates, and minimizing latency. Theme 3: clinical adoption/integration (1 question), concerning the effective combination of detection and characterization into one workflow. Theme 4: data access/annotation (1 question), concerning more efficient or automated data annotation methods to reduce the burden on human experts. Theme 5: regulatory approval (1 question), related to making regulatory approval processes more efficient. Conclusions This is the first reported international research priority setting exercise for AI in colonoscopy. The study findings should be used as a framework to guide future research with key stakeholders to accelerate the clinical implementation of AI in endoscopy.

Novel artificial intelligence techniques are emerging in all fields of healthcare, including gastroenterology. The aim of this review is to give an overview of artificial intelligence applications in the management of pancreatic diseases. We performed a systematic literature search in PubMed and Medline up to May 2020 to identify relevant articles. Our results showed that the development of machine‐learning based applications is rapidly evolving in the management of pancreatic diseases, guiding precision medicine in clinical, endoscopic and radiologic settings. Before implementation into clinical practice, further research should focus on the external validation of novel techniques, clarifying the accuracy and robustness of these models.

The COVID-19 pandemic has had a profound impact on provision of endoscopy services globally as staff and real estate were repurposed. As we begin to recover from the pandemic, a cohesive international approach is needed, and guidance on how to resume endoscopy services safely to avoid unintended harm from diagnostic delays. The aim of these guidelines is to provide consensus recommendations that clinicians can use to facilitate the swift and safe resumption of endoscopy services. An evidence-based literature review was carried out on the various strategies used globally to manage endoscopy during the COVID-19 pandemic and control infection. A modified Delphi process involving international endoscopy experts was used to agree on the consensus statements. A threshold of 80% agreement was used to establish consensus for each statement. 27 of 30 statements achieved consensus after two rounds of voting by 34 experts. The statements were categorised as pre-endoscopy, during endoscopy and postendoscopy addressing relevant areas of practice, such as screening, personal protective equipment, appropriate environments for endoscopy and infection control precautions, particularly in areas of high disease prevalence. Recommendations for testing of patients and for healthcare workers, appropriate locations of donning and doffing areas and social distancing measures before endoscopy are unique and not dealt with by any other guidelines. This international consensus using a modified Delphi method to produce a series of best practice recommendations to aid the safe resumption of endoscopy services globally in the era of COVID-19.

Abstract Background National guidelines recommend genomic profiling of tumor tissue to guide precision therapy. We compared the specimen adequacy for genomic profiling and yield of DNA between endoscopic ultrasound (EUS)-guided fine-needle biopsy (FNB) and EUS-guided fine-needle aspiration (FNA). Methods In our tandem, randomized controlled trial, consecutive patients undergoing EUS for evaluation of pancreatic masses underwent both conventional EUS-FNA with a 25-gauge needle and paired EUS-FNB (19 or 22-gauge needle), with the order randomized (EUS-FNA first followed by EUS-FNB, or vice versa). A minimum of one pass with each needle was obtained for histology. Second and third passes were performed to collect DNA. Specimens were evaluated by a cytopathologist blinded to the needle type. Specimen adequacy for genomic profiling was calculated based on FoundationOne clinical diagnostic (CDx) adequacy requirements. We compared the adequacy for genomic profiling DNA (quantity) and histology yields with both needles. Results Analysis included 50 patients (25 men; mean age 68 [standard deviation (SD) 13] years), with a mean lesion size of 38 (SD 17) mm; 37 lesions (74 %) were pancreatic ductal adenocarcinoma (PDAC). The mean DNA concentrations in PDAC by FNB and FNA needles were 5.930 (SD 0.881) µg/mL vs. 3.365 (SD 0.788) µg/mL, respectively (P = 0.01). The median standardized histology score per pass with EUS-FNB was 5 (sufficient for histology) and for EUS-FNA was 2 (enough for cytology). Specimen adequacy for genomic profiling and yield of DNA was significantly higher with FNB than with FNA needles. Conclusions In this study, adequacy for genomic profiling, DNA, and histology yield were considerably superior using an EUS-FNB needle compared with an EUS-FNA needle.

AbstractVolumetric laser endomicroscopy (VLE) has been shown to improve detection of early neoplasia in Barrett’s esophagus (BE). However, diagnostic performance using histopathology-correlated VLE regions of interest (ROIs) has not been adequately studied. We evaluated the diagnostic accuracy of VLE assessors for identification of early BE neoplasia in histopathology-correlated VLE ROIs. In total, 191 ROIs (120 nondysplastic and 71 neoplastic) from 50 BE patients were evaluated in a random order using a web-based module. All ROIs contained histopathology correlations enabled by VLE laser marking. Assessors were blinded to endoscopic BE images and histology. ROIs were first scored as nondysplastic or neoplastic. Level of confidence was assigned to the predicted diagnosis. Outcome measures were: (i) diagnostic performance of VLE assessors for identification of BE neoplasia in all VLE ROIs, defined as accuracy, sensitivity, and specificity; (ii) diagnostic performance of VLE assessors for only high level of confidence predictions; and (iii) interobserver agreement. Accuracy, sensitivity, and specificity for BE neoplasia identification were 79% (confidence interval [CI], 75–83), 75% (CI, 71–79), and 81% (CI, 76–86), respectively. When neoplasia was identified with a high level of confidence, accuracy, sensitivity, and specificity were 88%, 83%, and 90%, respectively. The overall strength of interobserver agreement was fair (k = 0.29). VLE assessors can identify BE neoplasia with reasonable diagnostic accuracy in histopathology-correlated VLE ROIs, and accuracy is enhanced when BE neoplasia is identified with high level of confidence. Future work should focus on renewed VLE image reviewing criteria and real-time automatic assessment of VLE scans.

Abstract Background Volumetric laser endomicroscopy (VLE) allows for near-microscopic imaging of the superficial esophageal wall and may improve detection of early neoplasia in Barrett’s esophagus (BE). Interpretation of a 6-cm long, circumferential VLE “full scan” may however be challenging for endoscopists. We aimed to evaluate the accuracy of VLE experts in correctly diagnosing VLE full scans of early neoplasia and non-dysplastic BE (NDBE). Methods 29 VLE full scan videos (15 neoplastic and 14 NDBE) were randomly evaluated by 12 VLE experts using a web-based module. Experts were blinded to the endoscopic BE images and histology. The 15 neoplastic cases contained a subtle endoscopically visible lesion, which on endoscopic resection showed high grade dysplasia or cancer. NDBE cases had no visible lesions and an absence of dysplasia in all biopsies. VLE videos were first scored as “neoplastic” or “NDBE.” If neoplastic, assessors located the area most suspicious for neoplasia. Primary outcome was the performance of VLE experts in differentiating between non-dysplastic and neoplastic full scan videos, calculated by accuracy, sensitivity, and specificity. Secondary outcomes included correct location of neoplasia, interobserver agreement, and level of confidence. Results VLE experts correctly labelled 73 % (95 % confidence interval [CI] 67 % – 79 %) of neoplastic VLE videos. In 54 % (range 27 % – 66 %) both neoplastic diagnosis and lesion location were correct. NDBE videos were consistent with endoscopic biopsies in 52 % (95 %CI 46 % – 57 %). Interobserver agreement was fair (kappa 0.28). High level of confidence was associated with a higher rate of correct neoplastic diagnosis (81 %) and lesion location (73 %). Conclusions Identification of subtle neoplastic lesions in VLE full scans by experts was disappointing. Future studies should focus on improving methodologies for reviewing full scans, development of refined VLE criteria for neoplasia, and computer-aided diagnosis of VLE scans.