Multimodal pancreatic cancer detection using methylated DNA biomarkers in pancreatic juice and plasma CA 19-9: A prospective multicenter study.

BACKGROUND AND AIMS: In previous studies methylated DNA markers (MDMs) have been identified in pancreatic juice (PJ) for detecting pancreatic ductal adenocarcinoma (PDAC). In this prospective multicenter study, the sensitivity and specificity characteristics of this panel of PJ-MDMs was evaluated standalone and in combination with plasma CA 19-9. METHODS: Paired PJ and plasma were assayed from 88 biopsy-proven treatment naïve PDAC cases and 134 controls (normal pancreas: 53, chronic pancreatitis (CP): 23, intraductal papillary mucinous neoplasm (IPMN): 58). Bisulfite-converted DNA from buffered PJ was analyzed using long-probe quantitative amplified signal assay targeting 14 MDMs (NDRG4, BMP3, TBX15, C13orf18, PRKCB, CLEC11A, CD1D, ELMO1, IGF2BP1, RYR2, ADCY1, FER1L4, EMX1, and LRRC4) and a reference gene (methylated B3GALT6). Logistic regression was used to fit the previously identified 3-MDM PJ panel (FER1L4, C13orf18 and BMP3). Discrimination accuracy was summarized using area under the receiver operating characteristic curve (AUROC) with corresponding 95% confidence intervals. RESULTS: Methylated FER1L4 had the highest individual AUROC of 0.83 (95% CI: 0.78-0.89). The AUROC for the 3-MDM PJ + Plasma CA 19-9 model (0.95 (0.92-0.98))) was higher than both the 3-MDM PJ panel (0.87 (0.82-0.92)) and plasma CA 19-9 alone ((0.91 (0.87-0.96) (p=0.0002 and 0.0135, respectively). At a specificity of 88% (95% CI: 81-93%), the sensitivity of this model was 89% (80-94%) for all PDAC stages and 83% (64-94%) for stage I/II PDAC. CONCLUSION: A panel combining PJ-MDMs and plasma CA19-9 discriminates PDAC from both healthy and disease control groups with high accuracy. This provides support for combining pancreatic juice and blood-based biomarkers for enhancing diagnostic sensitivity and successful early PDAC detection.

EUS for the evaluation of esophageal injury after catheter ablation for atrial fibrillation.

BACKGROUND AND AIMS: Atrial fibrillation (AF) ablation is an increasingly used rhythm control strategy that can damage adjacent structures in the mediastinum including the esophagus. Atrioesophageal fistulas and esophagopericardial fistulas are life-threatening adverse events that are believed to progress from early esophageal mucosal injury (EI). EUS has been proposed as a superior method to EGD to survey EI and damage to deeper structures. We evaluated the safety of EUS in categorizing postablation EI and quantified EUS-detected lesions and their correlation with injury severity and clinical course. METHODS: We retrospectively reviewed 234 consecutive patients between 2006 and 2020 who underwent AF ablation followed by EUS for the purpose of EI screening. The Kansas City classification was used to classify EI (type 1, type 2a/b, or type 3a/b). RESULTS: EUS identified pleural effusions in 31.6% of patients, mediastinal adventitia changes in 22.2%, mediastinal lymphadenopathy in 14.1%, pulmonary vein changes in 10.6%, and esophageal wall changes in 7.7%. EGD revealed 175 patients (75%) without and 59 (25%) with EI. Patients with type 2a/b EI and no EI were compared with multivariate logistic regression, and the presence of esophageal wall abnormality on EUS (odds ratio [OR], 72.85; 95% confidence interval [CI], 13.9-380.7), female sex (OR, 3.97; 95% CI 1.3-12.3), and number of energy deliveries (OR, 1.01; 95% CI, 1.003-1.03) were associated with EI type 2a or 2b. Preablation use of proton pump inhibitors was not associated with a decreased risk of EI. CONCLUSIONS: EUS safely assesses mediastinal damage after ablation for AF and may excel over EGD in evaluating mucosal lesions of uncertain significance, with a reduced risk of gas embolization in the setting of a full-thickness injury (enterovascular fistula). We propose an EUS-first guided approach to post-AF ablation examination, followed by EGD if it is safe to do so.

Utilization of an artificial intelligence-enhanced, web-based application to review bile duct brushing cytologic specimens: A pilot study.

BACKGROUND: The authors previously developed an artificial intelligence (AI) to assist cytologists in the evaluation of digital whole-slide images (WSIs) generated from bile duct brushing specimens. The aim of this trial was to assess the efficiency and accuracy of cytologists using a novel application with this AI tool. METHODS: Consecutive bile duct brushing WSIs from indeterminate strictures were obtained. A multidisciplinary panel reviewed all relevant information and provided a central interpretation for each WSI as being "positive," "negative," or "indeterminate." The WSIs were then uploaded to the AI application. The AI scored each WSI as positive or negative for malignancy (i.e., computer-aided diagnosis [CADx]). For each WSI, the AI prioritized cytologic tiles by the likelihood that malignant material was present in the tile. Via the AI, blinded cytologists reviewed all WSIs and provided interpretations (i.e., computer-aided detection [CADe]). The diagnostic accuracies of the WSI evaluation via CADx, CADe, and the original clinical cytologic interpretation (official cytologic interpretation [OCI]) were compared. RESULTS: Of the 84 WSIs, 15 were positive, 42 were negative, and 27 were indeterminate after central review. The WSIs generated on average 141,950 tiles each. Cytologists using the AI evaluated 10.5 tiles per WSI before making an interpretation. Additionally, cytologists required an average of 84.1 s of total WSI evaluation. WSI interpretation accuracies for CADx (0.754; 95% CI, 0.622-0.859), CADe (0.807; 95% CI, 0.750-0.856), and OCI (0.807; 95% CI, 0.671-0.900) were similar. CONCLUSIONS: This trial demonstrates that an AI application allows cytologists to perform a triaged review of WSIs while maintaining accuracy.

Celiac artery mesenteric fat measurement with endosonography (CAMEUS) reliably correlates with obesity and related comorbidities.

Background: Visceral fat represents a metabolically active entity linked to adverse metabolic sequelae of obesity. We aimed to determine if celiac artery mesenteric fat thickness can be reliably measured during endoscopic ultrasound (EUS), and if these measurements correlate with metabolic disease burden. Methods: This was a retrospective analysis of patients who underwent celiac artery mesenteric fat measurement with endosonography (CAMEUS) measurement at a tertiary referral center, and a validation prospective trial of patients with obesity and nonalcoholic steatohepatitis who received paired EUS exams with CAMEUS measurement before and after six months of treatment with an intragastric balloon. Results: CAMEUS was measured in 154 patients [56.5% females, mean age 56.5 ± 18.0 years, body mass index (BMI) 29.8 ± 8.0 kg/m2] and was estimated at 14.7 ± 6.5 mm. CAMEUS better correlated with the presence of non-alcoholic fatty liver disease (NAFLD) (R2 = 0.248, P < 0.001) than BMI (R2 = 0.153, P < 0.001), and significantly correlated with metabolic parameters and diseases. After six months of intragastric balloon placement, the prospective cohort experienced 11.7% total body weight loss, 1.3 points improvement in hemoglobin A1c (P = 0.001), and a 29.4% average decrease in CAMEUS (-6.4 ± 5.2 mm, P < 0.001). CAMEUS correlated with improvements in weight (R2 = 0.368), aspartate aminotransferase to platelet ratio index (R2 = 0.138), and NAFLD activity score (R2 = 0.156) (all P < 0.05). Conclusions: CAMEUS is a novel measure that is significantly correlated with critical metabolic indices and can be easily captured during routine EUS to risk-stratify susceptible patients. This station could allow for EUS access to sampling and therapeutics of this metabolic region.

Safety of EUS latex balloon use in patients with a latex allergy.

BACKGROUND AND AIMS: Balloons are used in EUS to improve visualization. However, data on the safety of latex balloons in patients with latex allergies are limited, and nonlatex alternatives can be costly. We investigated the safety of latex balloon use during EUS. METHODS: A retrospective review was conducted at a tertiary center between 2019 and 2022. Patients with reported latex allergies who underwent linear EUS were included. Baseline demographics, EUS characteristics, and adverse events were collected. The primary outcome was the rate of adverse events. RESULTS: Eighty-seven procedures were performed on 57 unique patients (mean age, 65.3 ± 14.5 years). Latex balloons were used in 59 procedures (67.8%), with only 8 procedures (13.6%) using prophylactic medications. No adverse events occurred during or after procedures, regardless of medication use or history of anaphylaxis. CONCLUSIONS: The use of EUS latex balloons in patients with a latex allergy was associated with no adverse events.

A novel blood-sensing capsule for rapid detection of upper GI bleeding: a prospective clinical trial.

BACKGROUND AND AIMS: Upper GI bleeding (UGIB) is a common medical emergency associated with high resource utilization, morbidity, and mortality. Timely EGD can be challenging from personnel, resource, and access perspectives. PillSense (EnteraSense Ltd, Galway, Ireland) is a novel swallowed bleeding sensor for the detection of UGIB, anticipated to aid in patient triage and guide clinical decision-making for individuals with suspected UGIB. METHODS: This prospective, open-label, single-arm comparative clinical trial of a novel bleeding sensor for patients with suspected UGIB was performed at a tertiary care center. The PillSense system consists of an optical sensor and an external receiver that processes and displays data from the capsule as "Blood Detected" or "No Blood Detected." Patients underwent EGD within 4 hours of capsule administration; participants were followed up for 21 days to confirm capsule passage. RESULTS: A total of 126 patients were accrued to the study (59.5% male; mean age, 62.4 ± 14.3 years). Sensitivity and specificity for detecting the presence of blood were 92.9% (P = .02) and 90.6% (P < .001), respectively. The capsule's positive and negative predictive values were 74.3% and 97.8%, and positive and negative likelihood ratios were 9.9 and .08. No adverse events or deaths occurred related to the PillSense system, and all capsules were excreted from patients on follow-up. CONCLUSIONS: The PillSense system is safe and effective for detecting the presence of blood in patients evaluated for UGIB before upper GI endoscopy. It is a rapidly deployed tool, with easy-to-interpret results that will affect the diagnosis and triage of patients with suspected UGIB. (Clinical trial registration number: NCT05385224.).

Prospective Study Assessing Impact of Ethylene Oxide Sterilization on Endoscopic Ultrasound Image Quality.

BACKGROUND & AIMS: Duodenoscope-associated transmission of infections has raised questions about efficacy of endoscope reprocessing using high-level disinfection (HLD). Although ethylene oxide (ETO) gas sterilization is effective in eradicating microbes, the impact of ETO on endoscopic ultrasound (EUS) imaging equipment remains unknown. In this study, we aimed to compare the changes in EUS image quality associated with HLD vs HLD followed by ETO sterilization. METHODS: Four new EUS instruments were assigned to 2 groups: Group 1 (HLD) and Group 2 (HLD + ETO). The echoendoscopes were assessed at baseline, monthly for 6 months, and once every 3 to 4 months thereafter, for a total of 12 time points. At each time point, review of EUS video and still image quality was performed by an expert panel of reviewers along with phantom-based objective testing. Linear mixed effects models were used to assess whether the modality of reprocessing impacted image and video quality. RESULTS: For clinical testing, mixed linear models showed minimal quantitative differences in linear analog score (P = .04; estimated change, 3.12; scale, 0-100) and overall image quality value (P = .007; estimated change, -0.12; scale, 1-5) favoring ETO but not for rank value (P = .06). On phantom testing, maximum depth of penetration was lower for ETO endoscopes (P < .001; change in depth, 0.49 cm). CONCLUSIONS: In this prospective study, expert review and phantom-based testing demonstrated minimal differences in image quality between echoendoscopes reprocessed using HLD vs ETO + HLD over 2 years of clinical use. Further studies are warranted to assess the long-term clinical impact of these findings. In the interim, these results support use of ETO sterilization of EUS instruments if deemed clinically necessary.

Pancreatic Cancer is More Frequently Early Stage at Diagnosis in Surgically Resected Intraductal Papillary Mucinous Neoplasms With Preoperative Surveillance.

Background and Aims: Management of intraductal papillary mucinous neoplasms (IPMNs) relies on clinical and imaging features to select patients for either pancreatectomy or periodic image-based surveillance. We aimed to compare outcomes in patients with IPMNs who underwent surgery at diagnosis with those who underwent surgery after a period of surveillance and identify preoperative clinical and imaging features associated with advanced neoplasia. Methods: Patients with surgically resected IPMN (n = 450) were divided into 2 groups: "immediate surgery": resection within 6 months of IPMN detection, and "surveillance surgery": resection after surveillance >6 months. Survival was analyzed with Kaplan-Meier estimates and Cox proportional hazard models. Results: Pancreatic cancers in the surveillance surgery group (n = 135) was more frequently stage I compared with the immediate surgery group (9/13, 69.2% vs 41/110, 37.3%; P = .027). Among Fukuoka "worrisome features," only main pancreatic duct dilation 5-9 mm (odds ratio [OR] = 3.12, 95% confidence interval [CI]: 1.72-5.68; P < .001) and serum CA 19-9≥ 35 U/mL (OR = 2.82, 95% CI: 1.31-6.06; P = .008) were significantly associated with advanced neoplasia. In addition, smoking history was associated with increased risk of advanced neoplasia (OR = 2.05, 95% CI: 1.23-3.43). Occurrence of future cancer was 16-fold higher in IPMN with high-grade dysplasia when compared with low-grade dysplasia (hazard ratio: 16.5; 95% CI: 4.19-64.7). Conclusion: Surveillance-detected pancreatic cancers in patients with IPMNs are more frequently stage I, and IPMN-HGD on surgical pathology is associated with significant risk of future pancreatic cancer. In addition to known "high-risk" features, main pancreatic duct dilation 5-9 mm, CA 19-9 elevation, and smoking history are significantly associated with advanced neoplasia.

Determining age and sex-specific distribution of pancreatic whole-gland CT attenuation using artificial intelligence aided image segmentation: Associations with body composition and pancreatic cancer risk.

BACKGROUND & AIMS: Increased intrapancreatic fat is associated with pancreatic diseases; however, there are no established objective diagnostic criteria for fatty pancreas. On non-contrast computed tomography (CT), adipose tissue shows negative Hounsfield Unit (HU) attenuations (-150 to -30 HU). Using whole organ segmentation on non-contrast CT, we aimed to describe whole gland pancreatic attenuation and establish 5th and 10th percentile thresholds across a spectrum of age and sex. Subsequently, we aimed to evaluate the association between low pancreatic HU and risk of pancreatic ductal adenocarcinoma (PDAC). METHODS: The whole pancreas was segmented in 19,456 images from 469 non-contrast CT scans. A convolutional neural network was trained to assist pancreas segmentation. Mean pancreatic HU, volume, and body composition metrics were calculated. The lower 5th and 10th percentile for mean pancreatic HU were identified, examining the association with age and sex. Pre-diagnostic CT scans from patients who later developed PDAC were compared to cancer-free controls. RESULTS: Less than 5th percentile mean pancreatic HU was significantly associated with increase in BMI (OR 1.07; 1.03-1.11), visceral fat (OR 1.37; 1.15-1.64), total abdominal fat (OR 1.12; 1.03-1.22), and diabetes mellitus type 1 (OR 6.76; 1.68-27.28). Compared to controls, pre-diagnostic scans in PDAC cases had lower mean whole gland pancreatic HU (-0.2 vs 7.8, p = 0.026). CONCLUSION: In this study, we report age and sex-specific distribution of pancreatic whole-gland CT attenuation. Compared to controls, mean whole gland pancreatic HU is significantly lower in the pre-diagnostic phase of PDAC.

Outcomes of endoscopic ultrasound and endoscopic resection of gastrointestinal subepithelial lesions: a single-center retrospective cohort study.

BACKGROUND: Endoscopic resection (ER) is an emerging therapeutic alternative for subepithelial gastrointestinal lesions (SELs). We aimed to determine whether size, layer of origin, and histology based on endoscopic ultrasound (EUS) and EUS-guided sampling (EUS-GS) influenced the outcomes and selection of patients for ER. METHODS: We performed a retrospective review of patients who underwent EUS, EUS-GS and resection of SELs from 2012-2019. Two pathologists reviewed the histology and layer of origin of all resected specimens, serving as the criterion for EUS accuracy. RESULTS: Seventy-three patients were included, of whom 59 (81%) were gastric SELs. Per EUS, median lesion size was 21 mm (interquartile range 15-32), and 63 (86%) originated from the 4th layer. The overall accuracy of EUS and EUS-GS in predicting the layer of origin and histology was 88% (95% confidence interval [CI] 77-94%) and 96% (95%CI 87-98%), respectively. Based on EUS, 18 (25%) patients were referred for ER, 5 (7%) to laparoscopic-endoscopic cooperative surgery, and 50 (68%) to surgery. Size >20 mm was associated with the type of resection approach (P=0.005), while layer of origin and histology were not (P=0.06 and P=0.09, respectively). When SELs were inaccurately classified (n=4) there were no adverse events or revision of the resection approach. CONCLUSIONS: EUS plays an important role in the outcome of resection approach for SELs, with size significantly influencing the selection for ER. In patients undergoing ER, no revised resections were needed when EUS was inaccurate.

Theragnostic chromosomal rearrangements in treatment-naive pancreatic ductal adenocarcinomas obtained via endoscopic ultrasound.

A crucial mutational mechanism in malignancy is structural variation, in which chromosomal rearrangements alter gene functions that drive cancer progression. Herein, the presence and pattern of structural variations were investigated in twelve prospectively acquired treatment-naïve pancreatic cancers specimens obtained via endoscopic ultrasound (EUS). In many patients, this diagnostic biopsy procedure and specimen is the only opportunity to identify somatic clinically relevant actionable alterations that may impact their care and outcome. Specialized mate pair sequencing (MPseq) provided genome-wide structural variance analysis (SVA) with a view to identifying prognostic markers and possible therapeutic targets. MPseq was successfully performed on all specimens, identifying highly rearranged genomes with complete SVA on all specimens with > 20% tumour content. SVA identified chimeric fusion proteins and potentially immunogenic readthrough transcripts, change of function truncations, gains and losses of key genes linked to tumour progression. Complex localized rearrangements, termed chromoanagenesis, with broad pattern heterogeneity were observed in 10 (83%) specimens, impacting multiple genes with diverse cellular functions that could influence theragnostic evaluation and responsiveness to immunotherapy regimens. This study indicates that genome-wide MPseq can be successfully performed on very limited clinically EUS obtained specimens for chromosomal rearrangement detection and potential theragnostic targets.

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based convolutional neural network (CNN) model for the purpose of identifying and classifying FLLs. METHODS: A prospective EUS database comprising cases of FLLs visualized and sampled via EUS was reviewed. Relevant still images and videos of liver parenchyma and FLLs were extracted. Patient data were then randomly distributed for the purpose of CNN model training and testing. Once a final model was created, occlusion heatmap analysis was performed to assess the ability of the EUS-CNN model to autonomously identify FLLs. The performance of the EUS-CNN for differentiating benign and malignant FLLs was also analyzed. RESULTS: A total of 210,685 unique EUS images from 256 patients were used to train, validate, and test the CNN model. Occlusion heatmap analyses demonstrated that the EUS-CNN model was successful in autonomously locating FLLs in 92.0% of EUS video assets. When evaluating any random still image extracted from videos or physician-captured images, the CNN model was 90% sensitive and 71% specific (area under the receiver operating characteristic [AUROC], 0.861) for classifying malignant FLLs. When evaluating full-length video assets, the EUS-CNN model was 100% sensitive and 80% specific (AUROC, 0.904) for classifying malignant FLLs. CONCLUSIONS: This study demonstrated the capability of an EUS-CNN model to autonomously identify FLLs and to accurately classify them as either malignant or benign lesions.

Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis.

OBJECTIVE: The diagnosis of autoimmune pancreatitis (AIP) is challenging. Sonographic and cross-sectional imaging findings of AIP closely mimic pancreatic ductal adenocarcinoma (PDAC) and techniques for tissue sampling of AIP are suboptimal. These limitations often result in delayed or failed diagnosis, which negatively impact patient management and outcomes. This study aimed to create an endoscopic ultrasound (EUS)-based convolutional neural network (CNN) model trained to differentiate AIP from PDAC, chronic pancreatitis (CP) and normal pancreas (NP), with sufficient performance to analyse EUS video in real time. DESIGN: A database of still image and video data obtained from EUS examinations of cases of AIP, PDAC, CP and NP was used to develop a CNN. Occlusion heatmap analysis was used to identify sonographic features the CNN valued when differentiating AIP from PDAC. RESULTS: From 583 patients (146 AIP, 292 PDAC, 72 CP and 73 NP), a total of 1 174 461 unique EUS images were extracted. For video data, the CNN processed 955 EUS frames per second and was: 99% sensitive, 98% specific for distinguishing AIP from NP; 94% sensitive, 71% specific for distinguishing AIP from CP; 90% sensitive, 93% specific for distinguishing AIP from PDAC; and 90% sensitive, 85% specific for distinguishing AIP from all studied conditions (ie, PDAC, CP and NP). CONCLUSION: The developed EUS-CNN model accurately differentiated AIP from PDAC and benign pancreatic conditions, thereby offering the capability of earlier and more accurate diagnosis. Use of this model offers the potential for more timely and appropriate patient care and improved outcome.