Faculty Bibliography

BACKGROUND:Symptomatic postoperative fluid collections (POFCs) can result in significant morbidity and mortality after abdominal surgery requiring timely intervention. EUS-guided drainage is traditionally delayed up to four weeks to allow wall maturation and reduce perforation or peritonitis risk. However, some POFCs may be suitable for earlier intervention. This study compared the efficacy and safety of acute (≤ 15 days), early (16-30 days), and delayed (> 30 days) EUS-guided drainage. METHODS:A retrospective cohort of patients undergoing EUS-guided drainage for symptomatic POFCs between 2013 and 2023 at a single tertiary center was evaluated. Technical success was defined as accessing and draining a POFC by transmural stent placement on initial endoscopy. Clinical success was defined as radiographically or endosonographically confirmed symptomatic POFC improvement without further percutaneous or surgical intervention. RESULTS:Among 85 patients with POFCs, most (61%) had undergone distal pancreatectomy with splenectomy. 59% required drainage ≤ 30 days after surgery, with 28% managed acutely. Most (83%) received lumen-apposing metal stents. Overall technical and clinical success rates were 94% and 79%, respectively, after a median 2 endoscopies (IQR 2-3). Success did not differ by timing (technical: 92% vs. 96% vs. 94%; clinical: 83% vs. 85% vs. 71%; P = 0.86 and P = 0.37). Adverse event rates were similar across groups (P = 0.85). Transgastric access was associated with clinical success (P < 0.001) and fewer adverse events (P = 0.03). Transduodenal access predicted technical (P = .05) and clinical failure (P = 0.02). CONCLUSIONS:In this large single-center experience of symptomatic POFCS, acute and early EUS-guided drainage with lumen-apposing metal stents in carefully selected patients was found to be technically safe and clinically effective, potentially avoiding more morbid interventions such as ERCP, percutaneous drainage, or surgery. Further randomized, prospective studies are needed to define predictors of technical and clinical success as well as adverse events.

Endoscopic ultrasound (EUS) guided ablation is an evolving minimally invasive approach for treating pancreatic lesions. While current guidelines do not yet recommend routine use, EUS ablation offers targeted, organ-sparing therapy that bridges the gap between surveillance and surgical resection. Techniques are evolving but data is available for ethanol ablation, intralesional chemoablation, radiofrequency ablation, among many others. For pancreatic cystic lesions and neuroendocrine tumors, EUS ablation achieves promising complete and partial response rates and favorable safety profile. Early studies in unresectable pancreatic adenocarcinoma show technical feasibility, safety, and potential synergy with systemic therapy. This review summarizes the current literature on EUS-guided ablation, highlighting clinical outcomes, limitations, and techniques, while emphasizing the need for further research to define optimal patient selection and long-term efficacy.

OBJECTIVES/OBJECTIVE:Pancreatic ductal adenocarcinoma (PDAC) screening is recommended for High-Risk Individuals (HRI) with Familial Pancreatic Cancer (FPC) or certain pathogenic germline variants (PGVs). Screening MRI commonly identifies pancreatic cystic lesions (PCLs), but comparative data between HRI and average-risk individuals (ARI) are limited. We aimed to quantify and characterize PCL differences between these groups. METHODS:In this retrospective study, 317 HRI were age-, sex- and race-matched to 634 ARI undergoing MRI/MRCP between 7/2018-9/2024. Demographics, genetic factors, and baseline MRI/MRCP outcomes were analyzed. HRI were classified as FPC or PGV±PDAC family history. Statistical analysis compared: all HRI vs. all ARI; single HRI subgroups vs. matched ARI; single HRI subgroups vs. other HRI. RESULTS:HRIs were more likely to have PCLs than ARIs (50.8% vs. 25.7%, P <0.001). FPC HRI were more likely to have PCLs (54.1% vs. 44.4%, P =0.049) than PGV HRI. However, PCLs in HRI were smaller than in ARI (7.4±5.7 vs. 10.8±12.6 mm; P =0.002). HRI and ARI did not differ regarding worrisome feature prevalence. No solid lesions were observed. CONCLUSIONS:PCLs are significantly more common among HRI than matched ARI, although typically small and low-risk. Future longitudinal studies should determine whether the higher prevalence of PCLs among HRI translates into increased risk of PCL-derived malignancy or reflects heighted detection on MRI.

BACKGROUND/UNASSIGNED:Acute pancreatitis (AP) is a common gastrointestinal disease with a rising global incidence. While most cases are mild, severe AP (SAP) carries high mortality. Early and accurate severity prediction facilitates management optimization. However, existing clinical severity prediction models, such as Bedside Index of Severity in Acute Pancreatitis (BISAP) and Modified CT Severity Index (mCTSI), have modest accuracy and often rely on data unavailable at admission. PURPOSE/UNASSIGNED:This study proposes a deep learning (DL) model to predict AP severity using abdominal contrast-enhanced CT scans acquired within 24 hours of admission. MATERIALS AND METHODS/UNASSIGNED: = 518 patients). RESULTS/UNASSIGNED: = .002). In retrospective triage analysis, the model correctly identified 50%-73% of patients who progressed to SAP and 40%-73% of those with MAP. CONCLUSION/UNASSIGNED:The proposed DL model achieved performance comparable to or better than established prognostic tools and maintained robust external performance. These findings suggest that AI-assisted CT analysis may support early, automated risk stratification of AP.

INTRODUCTION/BACKGROUND:Accurate preoperative evaluation of pancreatic cysts is essential. However, cytology and biochemical analysis are often limited by low cellularity, and risk stratification is critical for management. PancreaSeq Genomic Classifier (GC) analyzes cyst fluid for molecular alterations to aid diagnosis and risk assessment. MATERIALS AND METHODS/METHODS:We retrospectively analyzed 219 pancreatic cysts from 206 patients using PancreaSeq GC, integrating molecular findings with cytology, biochemical, imaging, surgical pathology, and follow-up. RESULTS:PancreaSeq GC successfully analyzed 216/219 cysts (99%) and detected alterations in 182 (83%). Among cases with both cytology and molecular data (n = 201), concordance was high in cytologically mucinous neoplasms (94%) and atypical cases (95%). Notably, among cases reported as negative for malignancy or nondiagnostic on cytology (n = 128), PancreaSeq GC identified mucinous neoplasms in 82 cases (64%), demonstrating added value in limited samples. Surgical pathology correlation (n = 24) showed excellent performance for distinguishing mucinous from nonmucinous cysts (area under the curve [AUC] = 0.94, P < 0.001). Risk stratification for detection of any dysplasia yielded an AUC of 0.78 (P = 0.006), and for high-grade dysplasia an AUC of 0.74 (P = 0.046). PancreaSeq GC reliably predicted neuroendocrine tumors, but the sensitivity for focal high-grade dysplasia in mucinous neoplasms and serous cystadenoma was limited. Compared with carcinoembryonic antigen (CEA), cyst fluid glucose showed higher sensitivity but lower specificity for mucinous cyst detection. CONCLUSIONS:PancreaSeq GC provides significant diagnostic and risk-stratification value that complements cytological evaluation, particularly in indeterminate or nondiagnostic cytology specimens and when biochemical data are unavailable. Integration of molecular findings improves cyst classification and dysplasia risk assessment. Multidisciplinary assessment remains essential, given the assay's limited sensitivity for focal high-grade dysplasia and serous cystadenomas.

IMPORTANCE/UNASSIGNED:Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths in the US. Although early detection improves survival, the rarity of the disease has rendered population screening a difficult approach. OBJECTIVE/UNASSIGNED:To develop and validate a parsimonious, interpretable, and generalizable model predicting incident PDAC-termed PRIME (PDAC Risk Model for Earlier Detection)-using routinely available electronic health record (EHR) data. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This cohort study used the Optum Labs Data Warehouse, a longitudinal, deidentified US EHR and claims database. Adults 40 years or older with an outpatient clinical encounter between 2016 and 2018 were included. Participants from 23 health systems (n = 4 859 833) comprised the training cohort; 31 additional systems (n = 5 619 091) served as validation. International validation was conducted in the UK Biobank (n = 498 754). Data analysis occurred July 2025 to January 2026. EXPOSURES/UNASSIGNED:Demographics, diagnosis codes, and routinely measured laboratory values were evaluated. Elastic-net regularization with 10-fold cross-validation selected the predictor set. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Incident PDAC was identified by International Classification of Diseases, Ninth and Tenth Revisions (ICD-9/10) codes. Model performance was assessed using time-dependent area under the curve (AUC) and calibration metrics. RESULTS/UNASSIGNED:Overall, the study included more than 11 million adults (2.1% Asian individuals, 8.4% Black individuals, 4.3% Hispanic/Latino individuals, 82.7% White individuals, and 2.4% other race/ethnicity by EHR reporting). In the training cohort (mean [SD] age, 60.4 [11] years), 14 405 individuals were diagnosed with PDAC (incidence 55 per 100 000 person-years) over a mean (SD) of 5.4 (2.5) years; in the validation cohort, 11 693 individuals were diagnosed with PDAC (54 per 100 000 person-years) over a mean (SD) of 3.9 (2.5) years. PRIME retained 19 predictors including history of pancreatitis, gastrointestinal disorders, prior cancers, type 2 diabetes, elevated aspartate aminotransferase levels, smoking, non-type-O blood, and male sex. Discrimination was strong at the 36-month time horizon (AUC = 0.75 in both the training and validation cohorts) with good calibration. In the validation cohort, patients in the top 1% of predicted risk had substantially higher PDAC risk (HR, 7.63; 95% CI, 6.85-8.49) compared with average-risk patients. In the UK Biobank, PRIME achieved a 36-month AUC of 0.71 with good calibration. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this validation cohort study, PRIME was a transparent EHR-based model that effectively stratified PDAC risk across diverse US health systems and generalized internationally. Prospective studies should evaluate for EHR-guided PDAC case-finding and integration with blood-based early-detection assays.

BACKGROUND:Accurate preoperative malignancy risk assessment in intraductal papillary mucinous neoplasm (IPMN) is essential to balance timely intervention for high-grade dysplasia or invasive cancer (HGD/IC) against avoiding unnecessary or premature surgery in low-grade IPMN. This study aimed to externally validate the 2023 International Association of Pancreatology (IAP)/Kyoto guidelines and develop a combined prediction model incorporating routinely collected clinical data and laboratory parameters. METHODS:We conducted a retrospective cohort study of 194 patients who underwent resection for IPMN between 2012 and 2024. We evaluated the predictive performance of the current IAP/Kyoto criteria ("Kyoto model"), developed a clinical model using routinely available laboratory and clinical variables, and integrated both into a combined model. Model performance was assessed using discrimination and calibration metrics, with internal validation via bootstrapping and five-fold cross-validation. RESULTS:The Kyoto model demonstrated modest discrimination (AUC 0.62). The clinical model, incorporating neutrophil-to-lymphocyte ratio (NLR), smoking history, blood glucose, CA19-9, and alkaline phosphatase, achieved an optimism-corrected AUC of 0.76. Compared to the Kyoto model, the combined model (AUC 0.77) significantly improved discrimination and calibration (p < 0.001). At a predicted probability threshold of >0.75, the combined model achieved a 90% specificity and 91% positive predictive value for HGD/IC, identifying a high-risk subgroup suitable for surgical intervention. CONCLUSIONS:Integrating routinely collected clinical and laboratory parameters with guideline-based imaging features shows promise to enhance preoperative identification of high-risk IPMN in patients already being considered for surgical resection. The combined model offers a practical, high-specificity tool to support surgical decision-making in this selected population, though its performance metrics should not be extrapolated to unselected surveillance cohorts. External validation is required before broader clinical implementation.

BACKGROUND:Epigenetic regulators represent a novel strategy to modulate the tumor immune microenvironment in pancreatic ductal adenocarcinoma (PDAC). In preclinical models, DNA hypomethylating agents enhance cytotoxic T-cell infiltration, synergize with PD-1 blockade, and improve survival when combined with immune checkpoint blockade. This single-institution, phase II study evaluated the safety, efficacy, and biomarkers of azacitidine plus pembrolizumab in patients with previously treated PDAC. METHODS:Patients with locally advanced or metastatic PDAC after one prior regimen received 50 mg/m2 subcutaneous azacitidine on days 1-5 of a 28-day cycle, starting week 1, and pembrolizumab 200 mg intravenously every 3 weeks starting week 3. Baseline and on-treatment blood and tumor was collected for exploratory biomarker analysis. RESULTS:Thirty-six patients enrolled between October 2017 and September 2021 (median age: 62.5 years); 34 were evaluable for safety; 31 for efficacy. Treatment was generally well-tolerated, with Grade 1-2 fatigue and diarrhea most common AEs. Three patients (9.7%) had a partial response, and the disease control rate was 35.5%. Median progression-free and overall survival was 1.51 and 4.83 months, respectively. Exploratory analysis suggested higher baseline CD8+ T cells and lower tumor Ki-67 was associated with response, whereas low baseline CD8+ T cell and Granzyme B infiltration correlated with higher exponential tumor growth rate. PD-L1 and CD68 expression were not predictive of benefit. CONCLUSION/CONCLUSIONS:Azacitidine plus pembrolizumab demonstrated limited clinical activity in second line, locally advanced or metastatic PDAC. Biomarker analysis suggests higher baseline CD8+ T-cell infiltration and lower proliferative index may identify patients more likely to benefit. (NCT03264404).