Pancreatic Diseases

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI for predicting preoperative perineural invasion (PNI) in pancreatic ductal adenocarcinoma (PDAC) and to evaluate its role in guiding postoperative prognostic and therapeutic decision-making. MATERIALS AND METHODS: In this multicenter retrospective study, we enrolled 714 eligible patients, allocating ...

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for several primary and metastatic malignancies; however, considerable heterogeneity remains in its definition, clinical indications, and technical delivery. METHODS: In May 2025, the SBRT Focus Group of the European Society for Radiotherapy and Oncology (ESTRO), in collaboration with International Stereotac...

Emerging nanoparticle-based therapies for pancreatic cancer: Current clinical landscape.

Pancreatic cancer, particularly ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal subtypes due to late diagnosis, the absence of e...

Artificial intelligence-driven 3-dimensional simulation system for enhanced preoperative planning in gastric cancer surgery: a retrospective validation study.

BACKGROUND: Few studies have developed artificial intelligence (AI) systems for the automatic recognition of the anatomy of the stomach, a dynamic org...

Enlarged Perivascular Spaces and Modifiable Vascular Risk Factors: Cross-Sectional and Longitudinal Analysis in the UK Biobank Cohort.

OBJECTIVE: To examine cross-sectional and longitudinal associations between vascular risk factors, APOE genotype, and perivascular spaces (PVS), with ...

Leveraging large language models to automate scoping reviews: A case study in treatment options for pancreatic cancer.

MKNet-family architectures for auto-segmentation of the residual pancreas after pancreatic resection: a deep learning comparative study.

PURPOSE: Accurate interpretation of CT scans after pancreatic resection is crucial for detecting abnormalities, including postoperative complications ...

Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.

Type 2 diabetes is a polygenic, heterogeneous disease affecting over 530 million individuals worldwide, a number projected to rise to 1.3 billion by 2...

Accuracy of Photon Dose Calculation on Photon-Counting Computed Tomography-A Comparison Study Based on Virtual Monoenergetic and Electron Density (Rho) Images for Pancreatic Cases.

PURPOSE: Photon-counting computed tomography (PCCT) offers versatile anatomic information because of better energy discrimination and higher spatial r...

Feasibility of deep learning-accelerated HASTE-FS for pancreatic cystic lesion surveillance: comparison with conventional HASTE and MRCP.

PURPOSE: Pancreatic cystic lesions (PCL) commonly undergo surveillance using MRI with MR cholangiopancreatography (MRCP). Our objective is to compare ...

Abdominal multi-organ segmentation on 3D negative-contrast CT cholangiopancreatography: a comparative study of deep learning methods.

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCT...

Cancer as a main contributor to multimorbidity in the UK Biobank: analysis of risk factors using conventional statistical modelling and machine learning.

Cancer frequently co-occurs with other chronic conditions, contributing substantially to disease burden. Multimorbidity is an increasing public health...

Deep-Learning Virtual Superior Mesenteric Artery Modeling for Risk Stratification in Pancreas Surgery.

BACKGROUND: Understanding the patient-specific anatomy of the superior mesenteric artery (SMA) and its branches is of critical importance when perform...

Machine learning to predict complications after salvage surgery in head and neck cancers.

The aim of this study was to develop a machine learning classification model that can forecast salvage surgery complications. This was a retrospective...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Observation and Localization in CT Images.

Pancreatic cancer remains one of the deadliest malignancies, primarily because of its subtle CT appearance and frequent late-stage diagnosis. We intro...

Revisiting drunk driving risk among individuals with alcohol use disorder using unsupervised learning: From clinical characteristics and neuropsychological performance to EEG data.

The strong association between alcohol use disorder (AUD) and driving under the influence of alcohol (DUIA) suggests substantial overlaps across the b...

Artificial intelligence-assisted biliary stent length selection for common bile duct strictures in endoscopic retrograde cholangiopancreatography: Model development and validation.

BACKGROUND: Biliary stent placement during endoscopic retrograde cholangiopancreatography (ERCP) is important for drainage in common bile duct (CBD) s...

Ethanol consumption has minimal effects on cancellous bone architecture in femur and lumbar vertebra in two species of non-human primates.

Alcohol abuse is a risk factor for atraumatic fractures. Our previous work using a non-human primate model of voluntary ethanol consumption showed tha...

Predictive value of dynamic creatinine cumulative exposure and trajectory classification onmortality in severe acute pancreatitis: a multicenter retrospective cohort study.

AIMS: This study aims to evaluate the predictive value of cumulative creatinine exposure (CumCr) and dynamic creatinine trajectories for severe acute ...

Deep learning-based combined noise reduction and contrast enhancement for post-neoadjuvant pancreatic cancer CT: does improved image quality translate to better resectability assessment?

PURPOSE: To evaluate whether deep learning-based combined noise reduction and contrast enhancement reconstruction (DLR) improves image quality and res...