Non-mucinous Pancreatic Cysts Research Articles

Amplified Sciences PanCyst Pro Panel to accurately identify non-mucinous pancreatic cyst fluid.

617 Background: Pancreatic cysts are rarely symptomatic, and, consequently, are detected incidentally during routine imaging analyses for unrelated disorders. Guidelines for diagnosis of pancreatic cysts rely on imaging and supportive analyses of fluid extracted during endoscopic ultrasound with fine-needle aspiration (EUS-FNA). Unfortunately, currently available protein markers and assays are not sufficiently accurate to rule-out patients in whom a non-mucinous pancreatic cyst has formed. Since non-mucinous pancreatic cysts seldom progress to cancer, this patient population is at risk of being subjected to the severe physical, emotional, and financial burdens associated with unwarranted surveillance, testing, and possible surgical intervention. Furthermore, identification of mucinous pancreatic cysts does not establish the risk of progression to cancer (rule-in) or the need for surgical intervention. Methods: To address the unmet needs in pancreatic cyst diagnosis, Amplified Sciences has combined a panel of markers with a clinically translated surface enhanced Raman spectroscopy (SERS)-based protease activity assay as a rule-out diagnostic tool. The tri-analyte panel was tested on a cohort of 185 retrospective samples gathered from three separate institutions (UPMC, IU Health, and UCSF) and consumed only 12 µL of cyst fluid per sample. The goals of this study were to establish the negative predictive value (NPV) of this panel prior to translation to a CLIA-regulated laboratory and create a preliminary algorithm for analysis. Results: The results of this statistically powered study show that protease activity outperforms carcinoembryonic antigen (CEA), a current standard diagnostic marker for pancreatic cyst fluid, in sensitivity, specificity, and NPV. Furthermore, in combination, the tri-analyte panel identifies non-mucinous pancreatic cysts with 99% sensitivity and a negative predictive value >95%. Conclusions: These results support the use of this panel in clinical settings as a diagnostic tool to rule-out patients from surgical intervention, as well as the use of SERS as an optical detection mode for clinical diagnostics. Future work will continue to address the unmet need for improved diagnostic information through multiplexed analyses of markers that consume comparatively minimal volume of pancreatic cyst fluid samples. Studies will also seek to build on the SERS platform by introducing more dyes, substrates, assays, and analytical methods. Amplified Sciences would like to acknowledge significant efforts to build the clinical samples cohort from Gina Zhu, Kelli Ifuku, and Dr. Kimberly Kirkwood from USCF, Christine Decapite and Dr. Randall Brand from UPMC, and Michele Yip-Schneider and Dr. C. Max Schmidt from IU Health.

Diagnostic performance of intracystic carcinoembryonic antigen (CEA) versus glucose in differentiation of mucinous and non-mucinous pancreatic cysts.

Pancreatic cysts have various potential for malignant transformation. Differentiating mucinous from non-mucinous cysts is crucial to make the right decision about further management, since mucinous cysts carry the risk of malignancy. Using endoscopic ultrasound (EUS) guided fine needle aspiration to determine intracystic carcinoembryonic antigen (CEA) levels is the recommended method for identifying mucinous cysts, although intracystic glucose assessment has also proved to be an effective tool. This study aims to compare the diagnostic performance of intracystic glucose and CEA in distinguishing between mucinous and non-mucinous pancreatic cystic lesions. In this single center study, we prospectively collected and analyzed the data of 91 consecutive patients who underwent endoscopic ultrasound (EUS)-guided fine-needle aspiration (FNA) with cytological analysis and measurement of intracystic CEA and glucose levels. The cyst type was classified based on radiological and EUS morphology, string sign, CEA, cytological and histological findings in resected cases. The diagnosis was established retrospectively by three experienced gastroenterologists blinded for glucose level in cases without definitive cytology or histology. We calculated the sensitivity, specificity, the positive- and negative predictive value of glucose and CEA respectively, and compared the two methods. The sensitivity of intracystic glucose versus CEA proved to be 96.2% vs. 69.2% in identifying mucinous cysts, while the specificity of glucose was shown to be 79.5%, compared to 100% for CEA. Intracystic glucose is a sensitive, easily accessible biomarker in identifying mucinous pancreatic cysts, however, the specificity is lower compared to CEA. The measurement of intracystic glucose level could help in decision-making in daily clinical practice, however the diagnostic performance of the method remains inferior to "through-the-needle" techniques, such as confocal laser endomicroscopy and Moray forceps biopsy.

S50 Utilization of Analytic Morphomics to Differentiate Mucinous From Nonmucinous Pancreatic Cysts

S50 Utilization of Analytic Morphomics to Differentiate Mucinous From Nonmucinous Pancreatic Cysts

B-343 Validation of Glucose Test in Pancreatic Cyst Fluid

Abstract Background Pancreatic cysts may be detected in 40 to 50 percent of patients who undergo abdominal magnetic resonance imaging for unrelated reasons. Mucinous cysts such as intraductal papillary mucinous neoplasms (IPMN) and mucinous cystic neoplasms (MCN) are known precursor lesions of pancreatic ductal adenocarcinoma. Therefore, it is imperative to identify mucinous cysts from nonmucinous cysts. In addition to cytology analysis, biomarker analysis in cyst fluid obtained by endoscopic ultrasound-guided fine needle aspiration can also provide information for the differential diagnosis of a mucinous cyst. Carcinoembryonic antigen (CEA) has been used as the biomarker to differentiate mucinous and nonmucinous pancreatic cysts with a sensitivity of around 63% and specificity of around 88%. Recently, glucose in pancreatic cyst fluid has been shown to have a better sensitivity (92%) and specificity (87%) in the differentiation of mucinous cysts using a threshold of <50 mg/dL. Therefore, it is consequential for clinical laboratories to validate glucose tests in pancreatic cyst fluid samples. In this study, we report the validation of the glucose test in pancreatic cyst fluid samples using the glucose assay on an automated chemistry analyzer. Methods The glucose assay, GLUC3, on Roche Cobas c702 analyzer was used to measure glucose in pancreatic cyst fluid samples. For linearity and recovery studies, cyst fluid samples were spiked with stock glucose solutions of known concentrations in a way that the spiked fluid samples always contained no less than 90% of the cyst fluid. Linearity was determined by assaying nine samples with glucose concentrations from 0–718 mg/dL. For the recovery study, various amounts of glucose were added to a cyst fluid sample containing undetectable glucose. The expected glucose concentrations in these samples are 23.2, 46.4, 92.7, and 159 mg/dL, respectively. Intra-run and inter-run precisions were determined by measuring glucose ten times in a run and in 10 separated runs, respectively, in 9 cyst fluid samples containing various amounts of glucose ranging from 0–718 mg/dL. The effect of hemoglobin was tested by spiking one cyst fluid sample with a hemolysate. Stability was determined by testing one sample at 0 and 24 h at room temperature, respectively. Results The assay was linear from 0–718 mg/dL of glucose with a slope of 1.05 and an intercept of 3.5. The recovery ranged from 103% to 111% in samples containing 23.2, 46.4, 92.7, and 159 mg/dL glucose, respectively. Both the intra-run and inter-run precisions for the nine samples with different glucose concentrations had a coefficient of variation of <5%. The samples were stable at room temperature for the study period of 24 h. No interference was observed at hemoglobin of 477 mg/dL. Conclusion Our study indicates that the glucose assay, GLUC3, on Roche Cobas c702 analyzer can be used to measure glucose in pancreatic cyst fluid samples. Our results show that glucose measurement in pancreatic cyst fluid had a good recovery and reproducible results with precision being <5%. This test may aid in the differential diagnosis of pancreatic mucinous cysts.

B-358 Application of Surface-Enhanced Raman Spectroscopy to Improve Sensitivity of Clinical Assays

Abstract Background Current efforts to expand the pool of available markers that can be analyzed in clinical settings is hampered by limited volumes of biomaterial-rich fluids and low concentrations of certain analytes, coupled with poor sensitivity of existing detection techniques. Although progress has been made using advanced sample preparation or assay techniques such as miRNeasy or ELISA for genomic and protein assays, respectively, little research has focused on adapting new optical methods as detection modes in the clinic. Amplified Sciences has developed an enzymatic activity assay platform using SERS detection to improve diagnostic sensitivities in multiple disease indications. Along with the experts at Wasatch Photonics, research focused on adaptation of this assay platform has enabled investigation of multiple markers of disease that had previously been undervalued or overlooked, as well as stacking of multiple markers in precious, low-volume samples. Methods Building upon previously published data using gastricsin as a marker to identify benign, non-mucinous pancreatic cysts, Amplified Sciences has added several SERS laser wavelengths, and different sample preparation methods to the existing platform. To examine the sensitivities of laser and dye combinations, solutions representative of assay samples containing rhodamine-dimer dye-labeled peptide were tested using Wasatch Photonics Raman spectrometers at 532, 638, 785, and 830 nm laser wavelengths. Samples at different pH were analyzed after addition of colloidal Au or Ag nanoparticles to determine the impacts of sample preparation on SERS spectral features. After drying in a desiccator overnight, the samples were reanalyzed to assess the stability of the SERS signals. As a pertinent application of this technology, an activity assay was developed for the known COVID protease 3ClPro. Release of rhodamine dimer dye as a result of 3ClPro cleavage of the substrate was quantified using SERS. The data were analyzed using Bruker OPUS Software package, and plotted using Graphpad Prism 9. Results Each laser, buffer, and metal used for SERS provided a unique spectral signature, suggesting that different transitions are available and potentially tunable depending on the application under investigation. Sensitivity was, as expected, best with the 532 nm SERS system purportedly due to enhancement factors, and the resonance impacts of rhodamine dyes at 532 nm. It was found that the Limit of Detection of Rhodamine-dimer dye was 100-fold lower with SERS compared to fluorescence, even after a 3-fold dilution with colloidal Ag. However, the remaining lasers could be more finely tuned, and, thus, provide alternate spectral properties, and different sensitivities which has implications when new dye classes are introduced into the platform. Furthermore, when SERS was applied to the 3ClPro assay, it was determined that activity could be detected below the dimerization concentration of 3ClPro, described in the literature as ∼25 nM. Also, a monomeric version of 3ClPro that is expected to have no reactivity with the substrate was found to display activity above background at concentrations as low as 1 µM. Conclusion SERS is an appropriate method for measuring activity in clinically relevant markers of disease, with tunable characteristics based upon the dye composition and the spectrometer in use.

Addressing the unmet clinical need for low-volume assays in early diagnosis of pancreatic cancer

The incidental detection of pancreatic cysts, an opportunity for the early detection of pancreatic cancer, is increasing, owing to an aging population and improvements in imaging technology. The classification of pancreatic cystic precursors currently relies on imaging and cyst fluid evaluations, including cytology and protein and genomic analyses. However, there are persistent limitations that obstruct the accuracy and quality of information for clinicians, including the limited volume of the complex, often acellular, and proteinaceous milieu that comprises pancreatic cyst fluid. The constraints of currently available clinical assays lead clinicians to the subjective and inconsistent application of diagnostic tools, which can contribute to unnecessary surgery and missed pancreatic cancers. Herein, we describe the pathway toward pancreatic cyst classification and diagnosis, the volume requirements for several clinically available diagnostic tools, and some analytical and diagnostic limitations for each assay. We then discuss current and future work on novel markers and methods, and how to expand the utility of clinical pancreatic cyst fluid samples. Results of ongoing studies applying SERS as a detection mode suggest that 50 µL of pancreatic cyst fluid is more than sufficient to accurately rule out non-mucinous pancreatic cysts with no malignant potential from further evaluation. This process is expected to leave sufficient fluid to analyze a follow-up, rule-in panel of markers currently in development that can stratify grades of dysplasia in mucinous pancreatic cysts and improve clinical decision-making.

Pancreatic cyst fluid interleukin-1 beta (IL-1β) level in predicting the risk of malignancy in pancreatic cysts

Pancreatic cystic lesions (PCLs) may be accidentally discovered in up to 13.5% of cases. These PCLs are of multiple types, including mucinous cysts (intra-ductal papillary mucinous neoplasms [IPMN] and mucinous cystic neoplasms [MCN]) that have a risk of malignant transformation. The difficulty in differentiation between the various PCLs and their unpredictable risk of malignant transformation makes their management difficult. The new diagnostic tools of PCLs often include endoscopic ultrasound guided fine needle aspiration (EUS-FNA) for pancreatic cyst fluid analysis. This study aimed to determine if cystic fluid IL-1β can predict the risk of malignancy and the degrees of dysplasia of pancreatic cysts. The study included 50 PCL patients. They were subjected to radiological, biochemical, serological, and histopathological examinations. Pancreatic cyst fluid IL-1β was analyzed using an ELISA. Our data indicated that cyst fluid IL-1 β can differentiate between benign and malignant cysts at cut-off value >150 pg/ml; with sensitivity and specificity of 84.00% and 56.00% respectively. Also, cyst fluid IL-1 β can differentiate between mucinous and non- mucinous pancreatic cysts at cut-off value >150 pg/ml; with a sensitivity and specificity of 83.33% and 53.78%, respectively. However, cyst fluid IL-1 β cannot differentiate between degrees of dysplasia of IPMN. In conclusion, our study suggested that pancreatic cyst fluid IL-1β can differentiate between.

Lower cyst fluid carcinoembryonic antigencutoff is helpful in the differential diagnosis of mucinous versus non-mucinous pancreatic cysts.

Pancreatic cystic lesions (PCLs) are being diagnosed with increased frequency and have varying neoplastic potential. We conducted this multimodal, prospective study to evaluate the role of tumor cytology and molecular markers to differentiate PCL subtypes. Consecutive undiagnosed patients with PCLs (n = 100, mean age: 50.37 years; 41% males) were prospectively studied. Cyst fluid carcinoembryonic antigen (CEA), CA19.9, CA125, CA72.4, and vascular endothelial growth factor-alpha (VEGF-α) levels were measured by quantitative enzyme-linked immunosorbent assay (ELISA) method. Mutational analysis of the KRAS gene (exon 2, Codon 12 and 13) and GNAS gene (Exon 8, Codon 201) were performed by Sanger's sequencing. The mean cyst size was 4.32 ± 2.4 cm. Fluid cytology revealed definitive diagnosis in 21 (22.3%) patients. All malignant PCLs could be identified on cytology whereas 10/14 (71%) non-malignant mucinous PCLs could also be identified on cytology based on mucin staining. Among the tested tumor markers, cyst fluid CEA had the best diagnostic performance for differentiation between mucinous and non-mucinous PCLs (AUC 0.933 [95% CI 0.86-0.91]). At a cyst fluid CEA cutoff level of 45.0 ng/mL, the sensitivity, specificity, positive predictive value, and negative predictive value for differentiation between mucinous and non-mucinous cysts were 88.5%, 96.8%, 92.0%, and 95.3%, respectively (p < 0.05). KRAS and GNAS mutation had no significant diagnostic benefit in comparison to fluid cytology and CEA levels. Fluid CEA at a lower cutoff of 45 ng/mL is the most accurate marker to differentiate between mucinous and non-mucinous PCL. The KRAS and GNAS mutational analysis does not improve upon the diagnostic performance of fluid cytology and tumor markers.

The Role of Interleukin 1 Beta in Differentiating Malignant from Benign Pancreatic Cysts.

Background and Aim: The frequency of detection of pancreatic cystic lesions (PCLs) in magnetic resonance imaging performed for reasons unrelated to the pancreas reaches up to 13.5%. The aim of this study was to evaluate the role of cyst fluid interleukin 1 beta (IL1β) and different endoscopic ultrasound (EUS) features in differentiating premalignant/malignant from benign pancreatic cysts. In addition, to evaluate the role of pancreatic cyst fluid carcinoembryonic antigen (CEA) in differentiating mucinous from nonmucinous pancreatic cysts. Methods: This study was conducted on 73 patients with PCLs. EUS-guided fine-needle aspiration (EUS-FNA) was performed on all patients. Estimation of IL1β and CEA levels in aspirated specimens were carried out. Results: Pancreatic cyst fluid IL1β level could not differentiate between premalignant/malignant and benign pancreatic cysts. At a cutoff value of 19.81 ng/mL pancreatic cyst fluid CEA has 64.3% sensitivity and 84.4% specificity in differentiating mucinous from nonmucinous pancreatic cyst. EUS can differentiate between premalignant/malignant pancreatic cysts and benign cysts with a sensitivity of 66.7%, specificity of 69.2% Conclusions: Pancreatic cyst fluid IL1β level cannot differentiate between premalignant/malignant and benign pancreatic cysts. CEA level can help in differentiation between mucinous and nonmucinous cysts. EUS can be useful in differentiation between premalignant/malignant pancreatic cysts and benign cysts.

Confocal Laser Endomicroscopy in the Diagnosis of Biliary and Pancreatic Disorders: A Systematic Analysis.

Background/AimsEndoscopic visualization of the microscopic anatomy can facilitate the real-time diagnosis of pancreatobiliary disorders and provide guidance for treatment. This study aimed to review the technique, image classification, and diagnostic performance of confocal laser endomicroscopy (CLE). MethodsWe conducted a systematic review of CLE in pancreatic and biliary ducts of humans, and have provided a narrative of the technique, image classification, diagnostic performance, ongoing research, and limitations. ResultsProbe-based CLE differentiates malignant from benign biliary strictures (sensitivity, ≥89%; specificity, ≥61%). Needle-based CLE differentiates mucinous from non-mucinous pancreatic cysts (sensitivity, 59%; specificity, ≥94%) and identifies dysplasia. Pancreatitis may develop in 2-7% of pancreatic cyst cases. Needle-based CLE has potential applications in adenocarcinoma, neuroendocrine tumors, and pancreatitis (chronic or autoimmune). Costs, catheter lifespan, endoscopist training, and interobserver variability are challenges for routine utilization. ConclusionsCLE reveals microscopic pancreatobiliary system anatomy with adequate specificity and sensitivity. Reducing costs and simplifying image interpretation will promote utilization by advanced endoscopists.

Utility of Cyst Fluid Carcinoembryonic Antigen in Differentiating Mucinous and Non-mucinous Pancreatic Cysts: An Updated Meta-Analysis.

Mucinous pancreatic cysts are considered premalignant and managed differently compared to benign pancreatic cystic lesions. The aim of this updated meta-analysis is to assess the diagnostic accuracy of cyst carcinoembryonic antigen (CEA) in differentiating between mucinous and non-mucinous pancreatic cysts. Studies comparing the diagnostic accuracy of CEA (cutoff level of 192ng/mL) in differentiating between mucinous and non-mucinous pancreatic cysts were searched in Medline, Ovid journals, Medline nonindexed citations, and Cochrane Central Register of Controlled Trials and Database of Systematic Reviews. Pooled estimates of diagnostic precision were calculated using random and fixed effects models. Initial search identified 526 reference articles, of these 34 relevant articles were selected and reviewed. Data were extracted from 15 studies (n = 2063) which met the inclusion criteria. The pancreatic cystic fluid CEA level at a 192ng/mL cutoff value had pooled specificity of 88.6% (95% CI 85.9-90.9) and pooled sensitivity was found to be 60.4% (95% CI 57.7-62.9). The pooled positive likelihood ratio was 4.5 (95% CI 2.9-6.9) and the pooled negative likelihood ratio was 0.45 (95% CI 0.38-0.52). The pooled diagnostic odds ratio, the odds of having mucinous cyst with elevated CEA, was 11.4 (95% CI 6.9-18.7). ThePfor chi-squared heterogeneity for all the pooled accuracy estimates was > 0.10. This meta-analysis suggests that the cyst fluid CEA level at a 192ng/mL cutoff value is highly specific in the diagnosis of mucinous cystic lesions with reasonable sensitivity.

Machine learning principles applied to CT radiomics to predict mucinous pancreatic cysts.

Current diagnostic and treatment modalities for pancreatic cysts (PCs) are invasive and are associated with patient morbidity. The purpose of this study is to develop and evaluate machine learning algorithms to delineate mucinous from non-mucinous PCs using non-invasive CT-based radiomics. A retrospective, single-institution analysis of patients with non-pseudocystic PCs, contrast-enhanced computed tomography scans within 1year of resection, and available surgical pathology were included. A quantitative imaging software platform was used to extract radiomics. An extreme gradient boosting (XGBoost) machine learning algorithm was used to create mucinous classifiers using texture features only, or radiomic/radiologic and clinical combined models. Classifiers were compared using performance scoring metrics. Shapely additive explanation (SHAP) analyses were conducted to identify variables most important in model construction. Overall, 99 patients and 103 PCs were included in the analyses. Eighty (78%) patients had mucinous PCs on surgical pathology. Using multiple fivefold cross validations, the texture features only and combined XGBoost mucinous classifiers demonstrated an area under the curve of 0.72 ± 0.14 and 0.73 ± 0.14, respectively. By SHAP analysis, root mean square, mean attenuation, and kurtosis were the most predictive features in the texture features only model. Root mean square, cyst location, and mean attenuation were the most predictive features in the combined model. Machine learning principles can be applied to PC texture features to create a mucinous phenotype classifier. Model performance did not improve with the combined model. However, specific radiomic, radiologic, and clinical features most predictive in our models can be identified using SHAP analysis.

The Yield of String Sign in Differentiating Mucinous from Non-Mucinous Pancreatic Cysts: A Retrospective Cross-Sectional Study

Background and Objectives: The diagnosis of pancreatic cysts is mostly based on a combination of morphological appearance and fluid analysis of amylase and carcinoembryonic antigen (CEA). We aimed to assess the capability of the string sign in differentiating mucinous from non-mucinous pancreatic cysts. Materials and Methods: All patients who were referred for endoscopic ultrasound (EUS) for pancreatic cysts assessment from 2015 to 2020 were retrospectively analyzed. Results: Our cohort consisted of 112 patients. Of them, 92 patients (82.1%) had mucinous cystic neoplasms (group A) and 20 patients (17.9%) had non-mucinous cystic neoplasms (group B). The average age in groups A and B was 71.3 and 60.4 years, respectively. String sign was positive in 47 patients (51.1%) and negative in 21 patients (22.8%) in group A, while in group B, string sign was negative in 19 patients (95%). String sign showed significant correlation with the diagnosis of mucinous cystic neoplasms (OR 64.2, 95% CI 8.1–508.6, p = 0.0001). Cytology confirmed mucinous cystic neoplasms that included 32 patients; the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of string sign for mucinous cystic neoplasms were high, reaching 93.8%, 85.7%, 96.8%, and 75%, respectively, with an excellent accuracy rate of 92.3%. Conclusions: The string sign is highly accurate for predicting pancreatic mucinous cystic neoplasms, and should be used as an important aid for improving diagnostic accuracy.

Intracystic Glucose Levels in Differentiating Mucinous From Nonmucinous Pancreatic Cysts: A Systematic Review and Meta-analysis.

Mucinous pancreatic cysts are well reported to transform into pancreatic adenocarcinoma, whereas nonmucinous cysts are mostly benign with low risk for malignant transformation. Nonsurgical methods of differentiating mucinous and nonmucinous pancreatic cysts are challenging and entail a multi investigational approach. Low intracystic glucose levels have been evaluated in multiple studies for its accuracy in differentiating mucinous from nonmucinous cysts of the pancreas. Multiple databases were searched and studies that reported on the utility of intracystic glucose levels in diagnosing mucinous pancreatic cysts were analyzed. Meta-analysis was conducted using the random-effects model, heterogeneity was assessed by I2%, and pooled diagnostic test accuracy values were calculated. Seven studies were included in the analysis from an initial total of 375 citations. The pooled sensitivity of low glucose in differentiating mucinous pancreatic cyst was 90.5% [95% confidence interval (CI): 88.1-92.5; I2=0%] and the pooled specificity was 88% (95% CI: 80.8-92.7; I2=79%). The sensitivity at a glucose cut-off of 50 was 90.1% (95% CI: 87.2-92.5; I2=0%) and the specificity was 85.3% (95% CI: 76.8-91.1; I2=76%). The sensitivity of glucose levels in pancreatic cyst fluid taken by endoscopic ultrasound guided fine-needle aspiration was 90.8% (95% CI: 87.9-93.1; I2=0%) and the specificity was 90.5% (95% CI: 81.7-95.3; I2=83%). The sensitivity of point-of-care glucometers was 89.5% (95% CI: 87.9-93.1; I2=0%) and specificity was 83.9% (95% CI: 68.5-92.6; I2=43%). Low glucose level at a cut-off of 50 mg/dL on fluid samples collected by endoscopic ultrasound guided fine-needle aspiration and analyzed by point-of-care glucometer achieves excellent diagnostic accuracy in differentiating mucinous pancreatic cysts.

An international study of interobserver variability of "string sign" of pancreatic cysts among experienced endosonographers.

Background and Objectives: No single optimal test reliably determines the pancreatic cyst subtype. Following EUS-FNA, the “string sign” test can differentiate mucinous from nonmucinous cysts. However, the interobserver variability of string sign results has not been studied.Methods: An experienced endosonographer performed EUS-FNA of pancreatic cysts on different patients and was recorded on video performing the string sign test for each. The videos were shared internationally with 14 experienced endosonographers, with a survey for each video: “Is the string sign positive?” and “If the string sign is positive, what is the length of the formed string?” Also asked “What is the cutoff length for string sign to be considered positive?” Interobserver variability was assessed using the kappa statistic (κ).Results: A total of 112 observations were collected from 14 endosonographers. Regarding string sign test positivity, κ was 0.6 among 14 observers indicating good interrater agreement (P < 0.001) while κ was 0.38 when observers were compared to the index endosonographer demonstrating marginal agreement (P < 0.001). Among observations of the length of the string in positive samples, 89.8% showed >5 mm of variability (P < 0.001), indicating marked variability. There was poor agreement on the cutoff length for a string to be considered positive.Conclusion: String sign of pancreatic cysts has a good interobserver agreement regarding its positivity that can help in differentiating mucinous from nonmucinous pancreatic cysts. However, the agreement is poor on the measured length of the string and the cutoff length of the formed string to be considered a positive string sign.

The utility of intracystic glucose levels in differentiating mucinous from non-mucinous pancreatic cysts

BackgroundDifferentiating benign non-mucinous from potentially malignant mucinous pancreatic cysts is still a challenge. This study aims to improve this distinction with cyst fluid analysis. MethodsA cohort study of pancreatic cyst undergoing EUS/FNA was performed from a prospectively maintained database between 2014 and 2018 was performed. Results113 patients were analyzed (40 non-mucinous and 73 mucinous). For differentiating mucinous from non-mucinous cyst: intracyst glucose ≤41 mg/dl had a sensitivity of 92% and a specificity of 92%; positive predictive value (PPV) of 96 and negative predictive value (NPV) of 86. Glucose ≤21 mg/dl had a sensitivity of 88%, specificity of 97%, PPV of 98 and NPV of 81. CEA ≥192 ng/mL had a sensitivity of 50% and a specificity of 92%; PPV of 92 and NPV of 50. Glucose ≤21 mg/dl or CEA ≥192 ng/mL combined had a sensitivity of 93%, specificity of 92%, PPV of 96 and NPV of 87 (Fig. 1, Table 1). ConclusionIntra-cyst glucose levels (≤41 mg/dl) outperforms classic CEA testing for differentiation of mucinous from non-mucinous pancreatic cysts. It was found to be an excellent diagnostic test with an AUC of 0.95 (95% CI: 0.81, 0.97).

Differential diagnosis of pancreatic cysts: A prospective study on the role of intra-cystic glucose concentration

BackgroundThe accuracy and costs of current diagnostic methods in the differential diagnosis of pancreatic cystic lesions still has ample room for improvement. AimsThe aim of the study was to confirm the diagnostic yield of intracystic glucose in the diagnosis of pancreatic cyst subtypes. MethodsWe prospectively recruited all patients who underwent Endoscopic Ultrasound with Fine Needle Aspiration of pancreatic cyst at our Institution. ResultsFifty-six patients were included in the study. We found that intracystic glucose concentration < 50 mg/dL was significantly more sensitive than a concentration of Carcinoembryonic Antigen > 192 ng/mL (93.6% vs 54.8%; p = 0.003) for the diagnosis of mucinous cysts. In terms of specificity, the two markers were not different (96% vs 100%; p = 1). Regarding the diagnosis of non-mucinous cysts, intracystic glucose concentration ≥ 50 mg/mL showed higher sensitivity than Carcinoembryonic Antigen level < 5 ng/mL (96% vs 72%) although a statistical significance could not be reached (p = 0.07). The two markers were not statistically different in terms of specificity (93.6% vs 87.1%; p = 0.62). ConclusionGiven its diagnostic performance and ease of measurement, intracystic glucose may replace Carcinoembryonic Antigen in the differential diagnosis of mucinous versus non-mucinous pancreatic cysts.

Decision Tree Analysis of Pancreatic Cyst Fluid Data for the Detection of Mucinous Cysts

Introduction: Though cyst fluid glucose levels have been shown to be a reliable marker for differentiating Mucinous and Non-Mucinous pancreatic cysts, a number of cysts have a more complex association with CEA and amylase enzyme values. Our project aimed to utilize machine learning to develop a decision tree that will provide clinicians with a practical tool to optimally determine the mucinous character of the lesion from lab results alone. Methods: This is a retrospective study conducted at a high-volume advanced endoscopy center. Clinical and lab data was abstracted from the electronic medical records of all patients who underwent pancreatic cyst aspiration between June 2015 and November 2017. Statistical analysis was done using STATA v 15.1. A decision tree was built using the J48 classifier algorithm in Weka 3.8.0. Factors used for data modelling were age, gender, diabetic status, and levels of glucose, CEA and amylase. The decision tree thus generated was validated using 10-fold cross validation. Results: A total of 57 lesions were included in the analysis. The average age of the cohort was 62.6 years (SD ±16.4). The most common diagnosis was pseudocyst (n=21, 36.8%), followed by 20 IPMNs (14 branch ducts (24.6%), 3 main duct (5.3%), and 3 mixed duct cysts (5.3%)), 11 mucinous Cystadenomas (19.3%), 4 lymphoepithelial cysts (7.0%), and 1 ciliated foregut cyst (1.6%). Thus, there were 31 Mucinous and 26 Non-Mucinous pancreatic cysts in our cohort. Mucinous cysts had higher CEA levels compared to Non-Mucinous cysts (Median 56.4 ng/mL vs 3.1 ng/mL, Mann-Whitney-U, pvalue=0.0018). However, Glucose and Amylase levels were lower in Mucinous cysts compared to Non-mucinous cysts (Both Mann-Whitney-U, p-value= 0.0002 and 0.0107 respectively). The decision tree algorithm revealed that pancreatic cysts will be non-mucinous if the glucose level is greater than 16 mg/dL. Additionally, cysts will non-mucinous if their CEA < 3.1 ng/mL and undetectable glucose levels. This model thus correctly classified 77.2% of all cysts, and, had a kappa statistic of 0.5473. Its ROC was 0.757 and r2-statistic was 0.85. Conclusion: Our decision tree analysis reveals that in addition to the expected non-mucinous cysts with high glucose values, there exists a small group of zero-glucose low-CEA cysts with CEA < 3.1 ng/mL and undetectable glucose levels. Our decision tree can be used by endoscopists in clinical practice as a simple and easy tool to predict the mucinous/non-mucinous character of pancreatic cysts.73_A Figure 1. Pancreatic Cysts Descriptive Statistics73_B Figure 2. Pancreatic Cyst Fluid Decision Tree Analysis - Results73_C Figure 3. Pancreatic Cyst Decision Tree Model

Endoscopic diagnosis of cystic lesions of the pancreas

Endoscopic methods are increasingly used in the diagnosis of cystic lesions of the pancreas. The two major endoscopic approaches are endoscopic ultrasonography (EUS) and transpapillary diagnosis. EUS-guided fine-needle aspiration cytology and EUS-guided fine needle-based confocal laser endomicroscopy have been used in the differential diagnosis of mucinous and non-mucinous pancreatic cysts. EUS is the most sensitive modality for detecting mural nodules (MN) in intraductal papillary mucinous neoplasms (IPMN). Contrast-enhanced harmonic EUS (CH-EUS), as an add-on to EUS, is useful for identifying and characterizing MN. Recent studies show that CH-EUS has a sensitivity of 60-100% and a specificity of 75-92.9% for diagnosing malignant cysts. Intraductal ultrasonography and peroral pancreatoscopy are especially useful for detecting MN and IPMN. A recent meta-analysis showed that cytological assessment of pancreatic juice using a transpapillary approach had a pooled sensitivity, specificity, and accuracy of 35.1%, 97.2%, and 92.9%, respectively, for diagnosing malignant IPMN. Further studies are warranted to determine the indications for each of these novel techniques in assessing cystic lesions of the pancreas.

157 - The Utility of Intracystic Glucose Levels in Differentiating Mucinous from Non-Mucinous Pancreatic Cysts

157 - The Utility of Intracystic Glucose Levels in Differentiating Mucinous from Non-Mucinous Pancreatic Cysts