AIMC Topic: Pancreatic Neoplasms

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Machine learning-powered single-molecule cancer diagnosis using DNA origami tags.

Science advances
Single-molecule detection (SMD) holds considerable promise in biomedical research. Although atomic force microscopy (AFM) provides an important technique with nanoscale resolution for SMD, its broader application is limited by labeling challenges and...

MRI and PET-Based Machine Learning Radiomics for Metastasis Prediction in Pancreatic Ductal Adenocarcinoma: A Systematic Review.

Journal of gastrointestinal cancer
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor survival, driven in part by early metastatic spread. Conventional imaging lacks sufficient precision to predict metastasis accurately. Machine learning (ML)-bas...

Development of a consensus molecular classifier for pancreatic ductal adenocarcinoma.

Genome medicine
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) presents a significant challenge, with a 5-year survival rate of approximately 10%. Tumor heterogeneity contributes to the limited effectiveness of treatments. Several tumor and stroma molecular cla...

A matrix stiffness gene signature identifies SLC20A1 as a novel mechano-immunological checkpoint enabling synergistic immunotherapy in pancreatic ductal adenocarcinoma.

Cancer immunology, immunotherapy : CII
Matrix stiffness is a defining feature of pancreatic ductal adenocarcinoma (PDAC) and drives malignant progression through mechanisms that remain poorly understood. Using an ensemble machine learning approach, we integrated multiomics data from 886 p...

High-acceleration pancreatobiliary MRI with deep learning-based super-resolution reconstruction for evaluating presumed pancreatic intraductal papillary mucinous neoplasm.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To evaluate the feasibility and diagnostic utility of a deep learning (DL)-based super-resolution (SR) reconstruction algorithm applied to pancreatobiliary MRI for assessing pancreatic intraductal papillary mucinous neoplasms (IPMNs).

Deep learning automatic segmentation and radiomics model for diagnosing pancreatic solid neoplasms in MRI.

BMC cancer
BACKGROUND: To develop and validate a deep learning tool for the automatic segmentation of pancreatic solid neoplasms and to establish a radiomics model for diagnosing these solid neoplasms in MRI.

Development of a serum protein biomarker panel for the diagnosis of pancreatic ductal adenocarcinoma using a machine learning approach.

Scientific reports
Early detection of pancreatic ductal adenocarcinoma (PDA) remains a major clinical challenge due to the lack of reliable biomarkers. We developed and validated a machine learning (ML)-based serum protein biomarker panel to enhance PDA diagnosis. Seru...

Overcoming the tumor microenvironment in pancreatic cancer barrier-specific nanoparticle drug delivery.

Nanoscale
Pancreatic cancer is one of the most lethal malignancies, largely due to the formidable pathophysiological barriers presented by its tumor microenvironment (TME). These include metabolic stress, such as acidosis and elevated reactive oxygen species; ...

An injury-associated lobular microniche is associated with the classical tumor cell phenotype in pancreatic cancer.

Nature communications
Pancreatic cancer is an aggressive disease with a dense fibrotic stroma and is often accompanied by chronic inflammation. Peritumoral inflammation is typically viewed as a reaction to nearby tumor growth. Here, we report that the inflamed pancreatic ...

Endoscopic ultrasound for pancreatic cystic lesions: a narrative review.

BMJ open gastroenterology
The incidence of incidental pancreatic cystic lesions (PCLs) has risen in recent years, largely due to advances in and increased use of imaging techniques. Endoscopic ultrasound (EUS) has become a crucial tool for evaluating and characterising PCLs, ...