Citations

INTRODUCTION: Mucosal healing is a widely accepted target for ulcerative colitis (UC) treatment. Linked color imaging (LCI) is a novel endoscopic enhancement system that utilizes Light Emitting Diode (LED) sources to spectrally enhance subtle erythema and mucosal surface patterns which may improve endoscopic classification of IBD associated inflammation. We aimed to assess the accuracy of LCI in classifying UC-associated mucosal healing compared to a validated histological reference standard (Geboes score). METHODS: 22 patients with ulcerative colitis were prospectively enrolled and evaluated by LCI colonoscopy using the Fujifilm’s digital video Processor VP-7000 and LED light source BL-7000 (Fujifilm, Tokyo Japan). Interobserver agreement was reported as kappa values. Geboes score was reported as score range of 0 to 5.4. A Geboes score of ≥3.1 (presence of surface intraepithelial neutrophils or < 5% crypts) was used to define histologic activity and a score of < 2B (no increase in neutrophils in the lamina propria) was used to define histologic remission. Geboes score has been previously validated to predict clinical recurrence. We calculated the overall accuracy, positive predictive value (PPV) and negative predictive value (NPV) of the LCI classification identifying mucosal healing against the Geboes score using the Fisher’s exact test. RESULTS: Total of 62 endoscopic images were obtained for different parts of the colon, 43 of which were matched to a corresponding biopsy. Endoscopic images were scored by 2 endoscopists into LCI-A (no redness), LCI-B (redness with visible vessels) and LCI-C (redness without visible vessels). A final LCI score was given for images with discrepant scores based on a consensus vote from both endoscopists. The interobserver agreement between the two endoscopists was 81%, kappa of 0.71 (95% confidence interval [CI] 0.57- 0.86). Among regions scored ≥3.1 on Geboes score, 9.5%, 28.6% and 61.9 % were classified as LCI-A, LCI-B and LCI-C, respectively ( P < 0.0001). Among images scored < 2B on Geboes score, 81.8%, 13.6% and 4.6% were classified as LCI-A, LCI-B and LCI-C, respectively ( P < 0.0001). Analyzing data against histology with LCI-A representing mucosal healing and LCI-B and C representing active mucosal disease, the overall accuracy becomes 86%, with NPV of 82.6% and PPV of 90% for identifying UC patients with histological and endoscopic evidence of mucosal healing. CONCLUSION: LCI technology has a potential role in assessing mucosal healing in UC.

SummaryBackgroundBecause most pancreatic intraductal papillary mucinous neoplasms (IPMNs) will never become malignant, currently advocated long‐term surveillance is low‐yield for most individuals.AimTo develop a score chart identifying IPMNs at lowest risk of developing worrisome features or high‐risk stigmata.MethodsWe combined prospectively maintained pancreatic cyst surveillance databases of three academic institutions. Patients were included if they had a presumed side‐branch IPMN, without worrisome features or high‐risk stigmata at baseline (as defined by the 2012 international Fukuoka guidelines), and were followed ≥ 12 months. The endpoint was development of one or more worrisome features or high‐risk stigmata during follow‐up. We created a multivariable prediction model using Cox‐proportional logistic regression analysis and performed an internal‐external validation.Results875 patients were included. After a mean follow‐up of 50 months (range 12‐157), 116 (13%) patients developed worrisome features or high‐risk stigmata. The final model included cyst size (HR 1.12, 95% CI 1.09‐1.15), cyst multifocality (HR 1.49, 95% CI 1.01‐2.18), ever having smoked (HR 1.40, 95% CI 0.95‐2.04), history of acute pancreatitis (HR 2.07, 95% CI 1.21‐3.55), and history of extrapancreatic malignancy (HR 1.34, 95% CI 0.91‐1.97). After validation, the model had good discriminative ability (C‐statistic 0.72 in the Mayo cohort, 0.71 in the Columbia cohort, 0.64 in the Erasmus cohort).ConclusionIn presumed side branch IPMNs without worrisome features or high‐risk stigmata at baseline, the Dutch‐American Risk stratification Tool (DART‐1) successfully identifies pancreatic lesions at low risk of developing worrisome features or high‐risk stigmata.

Objective This study aimed to evaluate a deep learning protocol to identify neoplasia in intraductal papillary mucinous neoplasia (IPMN) in comparison to current radiographic criteria. Methods A computer-aided framework was designed using convolutional neural networks to classify IPMN. The protocol was applied to magnetic resonance images of the pancreas. Features of IPMN were classified according to American Gastroenterology Association guidelines, Fukuoka guidelines, and the new deep learning protocol. Sensitivity and specificity were calculated using surgically resected cystic lesions or healthy controls. Results Of 139 cases, 58 (42%) were male; mean (standard deviation) age was 65.3 (11.9) years. Twenty-two percent had normal pancreas; 34%, low-grade dysplasia; 14%, high-grade dysplasia; and 29%, adenocarcinoma. The deep learning protocol sensitivity and specificity to detect dysplasia were 92% and 52%, respectively. Sensitivity and specificity to identify high-grade dysplasia or cancer were 75% and 78%, respectively. Diagnostic performance was similar to radiologic criteria. Areas under the receiver operating curves (95% confidence interval) were 0.76 (0.70–0.84) for American Gastroenterology Association, 0.77 (0.70–0.85) for Fukuoka, and 0.78 (0.71–0.85) for the deep learning protocol ( P = 0.90). Conclusions The deep learning protocol showed accuracy comparable to current radiographic criteria. Computer-aided frameworks could be implemented as aids for radiologists to identify high-risk IPMN.

e13161 Background: Capturing family health history is a simple and cost-effective way to identify individuals at increased risk for hereditary cancers. Several barriers exist to family history collection in the clinical setting. Self-reported histories can be limited, inaccurate or static. Physicians are often overwhelmed with data and “alert fatigue.” These complex factors make it difficult to quantify hereditary risks. Patients with increased genetic predisposition may be missed and may not receive individualized cancer surveillance measures. Methods: A practice improvement project was implemented at Mayo Clinic Florida to enhance family history screening. A questionnaire and simple scoring algorithm were developed to prompt referral for genetic counseling. This tool was pilot tested in a multi-specialty gastroenterology clinic. The questionnaire was administered in the waiting room (tablet interface). Patients with significant risk factors identified were contacted and offered genetic counseling. Results: Currently, 291 patients have completed the questionnaire. Thirty of the 60 patients identified to have significant familial risk factors met with a genetic counselor. Of the twenty who completed genetic testing, 9 patients received one or more variants of unknown significance. Two pathogenic variants were identified. One patient was molecularly confirmed to have multiple endocrine neoplasia type 2, which can allow for cascade screening in her unaffected sibling. A pathogenic ATM variant was found in a patient with a recent personal history of pancreatic cancer. The result prompted consideration of platinum based chemotherapy and/or PARP inhibitors in her cancer management. She has had a visible response thus far with the treatment. Her sister implemented a new surveillance regimen after testing positive for the familial variant. Conclusions: Enhanced family history screening is a low cost, effective method for the identification of patients who may benefit from hereditary cancer screening and genetic testing. Increased attention to family history is a vital component of precision medicine in any care setting.

SUMMARY Volumetric laser endomicroscopy (VLE) uses optical coherence tomography (OCT) for real-time, microscopic cross-sectional imaging. A US-based multi-center registry was constructed to prospectively collect data on patients undergoing upper endoscopy during which a VLE scan was performed. The objective of this registry was to determine usage patterns of VLE in clinical practice and to estimate quantitative and qualitative performance metrics as they are applied to Barrett's esophagus (BE) management. All procedures utilized the NvisionVLE Imaging System (NinePoint Medical, Bedford, MA) which was used by investigators to identify the tissue types present, along with focal areas of concern. Following the VLE procedure, investigators were asked to answer six key questions regarding how VLE impacted each case. Statistical analyses including neoplasia diagnostic yield improvement using VLE was performed. One thousand patients were enrolled across 18 US trial sites from August 2014 through April 2016. In patients with previously diagnosed or suspected BE (894/1000), investigators used VLE and identified areas of concern not seen on white light endoscopy (WLE) in 59% of the procedures. VLE imaging also guided tissue acquisition and treatment in 71% and 54% of procedures, respectively. VLE as an adjunct modality improved the neoplasia diagnostic yield by 55% beyond the standard of care practice. In patients with no prior history of therapy, and without visual findings from other technologies, VLE-guided tissue acquisition increased neoplasia detection over random biopsies by 700%. Registry investigators reported that VLE improved the BE management process when used as an adjunct tissue acquisition and treatment guidance tool. The ability of VLE to image large segments of the esophagus with microscopic cross-sectional detail may provide additional benefits including higher yield biopsies and more efficient tissue acquisition. Clinicaltrials.gov NCT02215291

Objective The aim of the study was to perform an economic analysis to identify the clinical and cost determinants of pancreatic cancer (PC) surveillance in high-risk individuals (HRIs). Methods A Markov model was created to compare the following 3 strategies: no screening, endoscopic ultrasound (EUS), and magnetic resonance imaging (MRI) screening. Patients were considered HRIs according to the Cancer of the Pancreas Screening consortium recommendations. Risk for developing PC, survival, and costs data were obtained from the Surveillance, Epidemiology, and End Results and Medicare databases. Surveillance effectiveness was obtained from a recent meta-analysis. Results Analysis of a cohort with fivefold relative risk of PC higher than the US population showed that MRI is the most cost-effective strategy. For those with the highest risk (>×20 relative risk), EUS became the dominant strategy. Our model was impacted by cost and imaging performance, but still cost-effective within the range reported in literature. Threshold analysis showed that if MRI increases greater than US $1600, EUS becomes more cost-effective. Once patients reached the age of 76 years, “no screening” was favored. Both surveillance strategies were cost-effective over a wide range of willingness to pay. Conclusions Abdominal imaging followed by pancreatectomy is cost-effective to prevent PC in HRIs, favoring MRI in moderate risk cases but EUS in those with highest risk.

Objective It is unclear whether endoscopic assessment of scars after colorectal endoscopic mucosal resection (EMR) has to include biopsies, even if endoscopy is negative. Vice versa, endoscopic diagnosis of recurrent adenoma may not require biopsy before endoscopic reinterventions. We prospectively analysed various endoscopic modalities in the diagnosis of recurrence following EMR. Design We conducted a prospective study of patients undergoing colonoscopy after EMR of large (≥20 mm) colorectal neoplasia. Endoscopists predicted recurrence and confidence level with four imaging modes: high-definition white light (WL) and narrow-band imaging (NBI) with and without near focus (NF). Separately, 26 experienced endoscopists assessed offline images. Results Two hundred and thirty patients with 255 EMR scars were included. The prevalence of recurrent adenoma was 24%. Diagnostic values were high for all modes (negative predictive value (NPV) ≥97%, positive predictive value (PPV) ≥81%, sensitivity ≥90%, specificity ≥93% and accuracy ≥93%). In high-confidence cases, NBI with NF had NPV of 100% (95% CI 98% to 100%) and sensitivity of 100% (95% CI 93% to 100%). Use of clips at initial EMR increased diagnostic inaccuracy (adjusted OR=1.68(95% CI 1.01 to 2.75)). In offline assessment, specificity was high for all imaging modes (mean: ≥93% (range: 55%–100%)), while sensitivity was significantly higher for NBI-NF (82%(72%–93%)%)) compared with WL (69%(38%–86%); p<0.001), WL-NF (68%(55%–83%); p<0.001) and NBI (71%(59%–90%); p<0.001). Conclusion Our study demonstrates very high sensitivity and accuracy for all four imaging modalities, especially NBI with NF, for diagnosis of recurrent neoplasia after EMR. Our data strongly suggest that in cases of high confidence negative optical diagnosis based on NBI-NF, no biopsy is needed to confirm absence of recurrence during colorectal EMR follow-up. A high confidence positive optical diagnosis can lead to immediate resection of any suspicious area. In all cases of low confidence, biopsy is still required. Trial registration number NCT02668198 .