Trends and impact of endoscopic ultrasound utilization for suspected intraductal papillary mucinous neoplasms.

Background: Multiple management guidelines for intraductal papillary mucinous neoplasms (IPMNs) have been published to improve risk stratification and resource utilization. This study aims to evaluate trends in endoscopic ultrasound (EUS) use and agreement between cross-sectional imaging and EUS for specific pancreas cystic lesion (PCL) features.

Methods: This retrospective cohort study included consecutive adults undergoing EUS for suspected IPMN detected with cross-sectional imaging (CT/MRCP) between 2013 and 2015 (Cohort 1) and 2018-2020 (Cohort 2).

Early detection of pancreatic cancer: Study design and analytical considerations in biomarker discovery and early phase validation studies.

Objectives: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease that is challenging to detect at an early stage. Biomarkers are needed that can detect PDAC early in the course of disease when interventions lead to the best outcomes. We highlight study design and statistical considerations that inform pancreatic cancer early detection biomarker evaluation.

Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data-A Systematic Review and Assessment.

Introduction: Accurate risk prediction can facilitate screening and early detection of pancreatic cancer (PC). We conducted a systematic review to critically evaluate effectiveness of machine learning (ML) and artificial intelligence (AI) techniques applied to electronic health records (EHR) for PC risk prediction.

Methods: Ovid MEDLINE(R), Ovid EMBASE, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, Scopus, and Web of Science were searched for articles that utilized ML/AI techniques to predict PC, published between January 1, 2012, and February 1, 2024.

Identification of pancreatic cancer risk factors from clinical notes using natural language processing.

Objectives: Screening for pancreatic ductal adenocarcinoma (PDAC) is considered in high-risk individuals (HRIs) with established PDAC risk factors, such as family history and germline mutations in PDAC susceptibility genes. Accurate assessment of risk factor status is provider knowledge-dependent and requires extensive manual chart review by experts. Natural Language Processing (NLP) has shown promise in automated data extraction from the electronic health record (EHR).

Long-Term Outcomes and Risk of Pancreatic Cancer in Intraductal Papillary Mucinous Neoplasms.

Importance: Intraductal papillary mucinous neoplasms (IPMNs) are pancreatic cysts that can give rise to pancreatic cancer (PC). Limited population data exist on their prevalence, natural history, or risk of malignant transformation (IPMN-PC).

Objective: To fill knowledge gaps in epidemiology of IPMNs and associated PC risk by estimating population prevalence of IPMNs, associated PC risk, and proportion of IPMN-PC.

Utility of Urgent Endoscopic Retrograde Cholangiopancreatography in Patients with Predicted Mild Acute Pancreatitis and Cholestasis.

Background: Endoscopic retrograde cholangiopancreatography (ERCP) within 72 h is suggested for patients presenting with acute biliary pancreatitis (ABP) and biliary obstruction without cholangitis. This study aimed to identify if urgent ERCP (within 24 h) improved outcomes compared to early ERCP (24-72 h) in patients admitted with predicted mild ABP.

Methods: Patients admitted for predicted mild ABP defined as a bedside index of severity in acute pancreatitis score < 3 and underwent ERCP for biliary obstruction within 72 h of presentation during the study period were included.

A Rare Cause of Abdominal Pain: Erdheim-Chester Disease.

A 65-year-old man presented with hematuria, night sweats, nausea, intermittent nonbloody diarrhea, and abdominal pain. Computed tomography angiogram with enterography showed retroperitoneal fibrosis surrounding both kidneys and ureters without any evidence of vascular obstruction or hydronephrosis. Laparoscopic biopsy demonstrated fibroadipose tissue involved by a subtle histiocytic infiltrate in a background of marked fibrosis, scattered lymphocytes, and plasma cells.

Risk of Syndrome-Associated Cancers Among First-Degree Relatives of Patients With Pancreatic Ductal Adenocarcinoma With Pathogenic or Likely Pathogenic Germline Variants.

Importance: Increased cancer risk in first-degree relatives of probands with pancreatic ductal adenocarcinoma (PDAC probands) who carry pathogenic or likely pathogenic germline variants (PGVs) in cancer syndrome-associated genes encourages cascade genetic testing. To date, unbiased risk estimates for the development of cancers on a gene-specific basis have not been assessed.

Objective: To quantify the risk of development of PDAC and extra-PDAC among first-degree relatives of PDAC probands who carry a PGV in 1 of 9 cancer syndrome-associated genes-ATM, BRCA1, BRCA2, PALB2, MLH1, MSH2, MSH6, PMS2, and CDKN2A.

Artificial intelligence assisted whole organ pancreatic fat estimation on magnetic resonance imaging and correlation with pancreas attenuation on computed tomography.

Background: Fatty pancreas is associated with inflammatory and neoplastic pancreatic diseases. Magnetic resonance imaging (MRI) is the diagnostic modality of choice for measuring pancreatic fat. Measurements typically use regions of interest limited by sampling and variability.

Volumetric Pancreas Segmentation on Computed Tomography: Accuracy and Efficiency of a Convolutional Neural Network Versus Manual Segmentation in 3D Slicer in the Context of Interreader Variability of Expert Radiologists.

Purpose: This study aimed to compare accuracy and efficiency of a convolutional neural network (CNN)-enhanced workflow for pancreas segmentation versus radiologists in the context of interreader reliability.

Methods: Volumetric pancreas segmentations on a data set of 294 portal venous computed tomographies were performed by 3 radiologists (R1, R2, and R3) and by a CNN. Convolutional neural network segmentations were reviewed and, if needed, corrected ("corrected CNN [c-CNN]" segmentations) by radiologists.

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.

Tissue methylated DNA markers for sporadic pancreatic cancer are strongly associated with familial and genetically predisposed pancreatic cancer.

High-risk individuals (HRIs) with familial and genetic predisposition to pancreatic ductal adenocarcinoma (PDAC) are eligible for screening. There is no accurate biomarker for detecting early-stage PDAC. We previously demonstrated that a panel of methylated DNA markers (MDMs) accurately detect sporadic PDAC.

Radiomics-based Machine-learning Models Can Detect Pancreatic Cancer on Prediagnostic Computed Tomography Scans at a Substantial Lead Time Before Clinical Diagnosis.

Background & Aims: Our purpose was to detect pancreatic ductal adenocarcinoma (PDAC) at the prediagnostic stage (3-36 months before clinical diagnosis) using radiomics-based machine-learning (ML) models, and to compare performance against radiologists in a case-control study.

Methods: Volumetric pancreas segmentation was performed on prediagnostic computed tomography scans (CTs) (median interval between CT and PDAC diagnosis: 398 days) of 155 patients and an age-matched cohort of 265 subjects with normal pancreas. A total of 88 first-order and gray-level radiomic features were extracted and 34 features were selected through the least absolute shrinkage and selection operator-based feature selection method.

PET/CT and PET/MRI in neuroendocrine neoplasms.

Advanced molecular imaging has come to play an integral role in the management of gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs). Somatostatin receptor (SSTR) PET has now emerged as the reference standard for the evaluation of NENs and is particularly critical in the context of peptide receptor radionuclide therapy (PRRT) eligibility. SSTR PET/MRI with liver-specific contrast agent has a strong potential for one-stop-shop multiparametric evaluation of GEP-NENs.

Discovery and Validation of Methylated DNA Markers From Pancreatic Neuroendocrine Tumors.

Background And Aims: Methylated DNA markers (MDMs) accurately identify several different cancer types, but there are limited data for pancreatic neuroendocrine tumors (pNETs). We aimed to identify MDM candidates in tissue that differentiate pNETs from normal pancreas.

Methods: wUsing DNA from frozen normal pancreas (13) and pNET (51) tissues, we performed reduced representation bisulfite sequencing for MDM discovery.

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.