Lymphoma

Multidimensional 5-hydroxymethylcytosine features in cell-free DNA enable the detection, staging and subtyping of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignant cancer with limited biomarkers for early detection and disease stratification. Here, we investigated whether multidimensional 5-hydroxymethylcytosine (5hmC) features in plasma cell-free DNA (cfDNA) could support the noninvasive detection, staging, and subtyping of PDAC. We performed a genome-wide cfDNA 5hmC analysis in 274 indivi...

Integrated Clinical-Molecular Risk Stratification in Diffuse Large B-Cell Lymphoma: Machine Learning Survival Analysis.

BACKGROUND: The clinical outcomes of diffuse large B-cell lymphoma (DLBCL) are highly heterogeneous. While clinical indices like the international prognostic index (IPI) are widely used, their predictive accuracy remains limited. The integration of molecular features with clinical characteristics holds promise for developing more precise prognostic models to improve risk stratification and persona...

Intravoxel incoherent motion imaging with improved image quality by deep learning reconstruction for prediction of lymph-vascular space invasion in patients with cervical cancer.

PURPOSE: To evaluate the performance of intravoxel incoherent motion (IVIM) imaging with deep learning reconstruction (DLR) for prediction of lymph-va...

Large Language Models for Oncology Guideline Maintenance: Prospective Case Study.

BACKGROUND: Maintenance of oncology clinical practice guidelines (CPGs) is increasingly challenged by the rapid growth of trial data and therapeutic c...

Validation of federated analytics across secure data environments: A comparative study of synthetic healthcare datasets using machine learning and general linear models.

OBJECTIVES: To enable research and innovation, most health data systems are moving away from a model of pooled data egress and instead highlight the b...

MambaGCN-SMI: Protocol state machine inference framework based on Mamba and GCN.

To address the limitations of existing non-interactive protocol state machine inference methods in feature representation capability, inter-stage info...

Tumor spread through air spaces in non-small-cell lung cancer: 18F-fluorodeoxyglucose PET-based tumoral and peritumoral radiomics analysis with machine learning.

OBJECTIVE: To investigate the utility of tumoral and peritumoral [18F]-fluorodeoxyglucose PET-based radiomics models for predicting tumor spread throu...

Self-supervised multimodal swin UNETR for PET/CT segmentation of diffuse large B-cell lymphoma.

Accurate segmentation of diffuse large B-cell lymphoma (DLBCL) is critical for reliable PET/CT-based quantification and total metabolic tumor volume (...

Deep Learning-Accelerated 3D Vessel Wall MRI: Prospective Evaluation of Sonic DL with Substantial Scan Time Reduction.

PURPOSE: While 3D vessel wall MRI (VW-MRI) is essential for characterizing vasculopathies, prolonged acquisition times limit its utility by increasing...

A Dual-Center, Interpretable Deep Learning-Radiomics Fusion Model for Distinguishing Nasopharyngeal Carcinoma from Nasopharyngeal Lymphoma Using FDG PET/CT.

RATIONALE AND OBJECTIVES: Accurate differentiation between Nasopharyngeal Carcinoma (NPC) and Nasopharyngeal Lymphoma (NPL) is critical for clinical m...

NMR metabolomics and glycomics for cancer detection in patients with non-specific symptoms: a prospective observational cohort study.

BACKGROUND: Early cancer diagnosis in patients with non-specific symptoms is limited by the lack of discriminatory tests. Within the Oxfordshire Suspe...

Adapted foundation models for breast MRI triaging in contrast-enhanced and non-contrast-enhanced protocols.

OBJECTIVES: To evaluate a DINOv2-based medical slice transformer (MST) for triaging abbreviated breast MRI by ruling out examinations with suspicious ...

A radiomic approach to non-invasively decode tumor immune microenvironmental features in surgically resected non-small cell lung cancer.

INTRODUCTION: This study aimed to develop radiomics-based multivariate classifiers able to non-invasively decipher the tumor immune microenvironment (...

[Advances in electroencephalographic biomarkers of cognitive dysfunction in obstructive sleep apnea].

Obstructive sleep apnea (OSA) is a common sleep disorder frequently accompanied by cognitive impairment. The electroencephalographic signals, with its...

Deep Learning Enables Automated Detection of Mature B Cell Neoplasms by Flow Cytometry.

Multiparameter flow cytometry is essential for diagnosing mature B-cell lymphomas, yet analysis remains largely manual, time-consuming, and subject to...

Cost-effectiveness and environmental impact of artificial intelligence-assisted colonoscopy with the resect-and-discard strategy: a microsimulation study.

Background Artificial intelligence (AI)-assisted colonoscopy reduces costs in colorectal cancer screening, but its incremental value relative to non-A...

Deep learning for CT-less attenuation correction synthesis in non-small cell lung cancer: A proof-of-concept evaluated for quantitative and physical characteristics.

To develop and rigorously validate a deep learning framework for CT-free positron emission tomography (PET) attenuation correction in non-small cell l...

MRI-based deep learning models match or surpass physician performance for early detection and staging of avascular necrosis of the femoral head: A systematic review.

PURPOSE: Efficient and reliable magnetic resonance imaging (MRI)-based diagnosis of early avascular necrosis of the femoral head (AVNFH) is essential ...

Effect of genetic factors on [18F]FDG PET metabolic phenotypes in dementia with Lewy bodies.

BACKGROUND: Neuroimaging with [18F]FDG PET can support the diagnosis of Dementia with Lewy Bodies (DLB), but it remains unclear how genetic factors in...

AI-driven PROTAC design overcomes oncogenic resilience by eliminating the CLIP1-LTK fusion protein.

The discovery of CAP-Gly domain-containing linker protein 1(CLIP1)-Leukocyte tyrosine kinase (LTK) as an oncogenic fusion reveals a unique dependency ...