Radiology

The expanding horizon: Role of widefield imaging in uveitis.

Conventional retinal imaging has historically been limited to the posterior pole, capturing only 30-50° field-of-view. The advent of widefield (WF) and ultra-widefield (UWF) imaging (WFI) technology has transformed this landscape, enabling visualization of up to 200° of retina in a single capture. This expanded field-of-view has revealed changes to help document peripheral retinal pathology like v...

MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI.

The circulation of cerebrospinal and interstitial fluid plays a vital role in clearing metabolic waste from the brain, and its disruption has been linked to neurological disorders. However, directly measuring brain-wide fluid transport, especially in the deep brain, has remained elusive. Here, we introduce magnetic resonance artificial intelligence velocimetry (MR-AIV), a framework featuring a spe...

A machine learning-based interpretable model for predicting pancreatic cancer in chronic pancreatitis patients with focal pancreatic lesions.

BACKGROUND: Pancreatic cancer (PC) is deadly and distinguishing it from inflammatory conditions in chronic pancreatitis (CP) patients is challenging. ...

Dynamic Mechanics and Longitudinal Changes in Temporomandibular Joint Structural Integrity.

BACKGROUND: Longitudinal changes in temporomandibular joint (TMJ) structures may reflect joint contact mechanics and jaw loading behaviours (Mechanobe...

AI-Assisted MRI Interpretation in Diagnosing Bankart and Reverse Bankart Lesions.

BACKGROUND: Accurate detection of glenoid labral tears remains challenging; however, it is essential for guiding treatment and return-to-play decision...

AI as a Safety-Net Reader for Mammograms Classified as Normal or Benign in the French Screening Program.

In the French national breast cancer screening program, second reading is performed only for mammograms interpreted as negative (BI-RADS 1-2) at first...

Measuring Radiology's Impact: Core Concepts for Tracking Patient-Oriented Outcomes and Delivering High-Value Care-A Perspective by the ACR's Relevance and Impact Committee.

Radiology strongly impacts patient care. However, radiologists' potential to promote high-value care has long been underappreciated, partly related to...

Multimodal GPT-5 for Predicting Poor Functional Outcomes After Intracerebral Hemorrhage in the Emergency Department: Validation Study.

BACKGROUND: In the emergency department, rapid prognostic assessment of patients with intracerebral hemorrhage (ICH) is essential for guiding early ma...

Multimodal Prediction of Renal Tumor Malignancy From Radiology Reports and Structured Electronic Health Records: Retrospective Cohort Study.

BACKGROUND: Accurate preoperative prediction of renal tumor malignancy is critical for guiding decisions and reducing overtreatment, as a substantial ...

Deep Learning-Enhanced X-Space Reconstruction for Magnetic Particle Imaging: A Physics-Consistent Approach.

Magnetic Particle Imaging (MPI) is an emerging tracer-based imaging modality with high sensitivity and excellent temporal resolution; however, X-space...

Integrating Structural and Functional Ultrasound Carotid Assessment in a Single Software Platform: Development and Feasibility Evaluation.

BACKGROUND: The extensive assessment of vascular health requires the integration of both structural and functional (hemodynamic) parameters. These are...

[MRI-based deep learning model for preoperative prediction of urothelial carcinoma with variant histology of bladder: a retrospective, multicenter study].

Objectives: To develop a deep learning model based on magnetic resonance imaging (MRI) for the preoperative prediction of urothelial carcinoma with va...

Dense-MoE vs Lite-MoE: A Gating-Weight-Aware Pruning Framework for Unpaired Multimodal Breast Cancer Diagnosis.

This study proposes a unique Mixture-of-Experts (MoE)-based deep learning framework for the effective use of unpaired multimodal images in breast canc...

A stacked multi-classifier for multi-modal data fusion in transcranial sonography-based Parkinson's disease assessment.

Parkinson's disease (PD) is a catastrophic neurodegenerative disorder and a major culprit of neurological disability worldwide. Accurate diagnosis of ...

In-vivo iron mapping in patients with Parkinson's disease using deep learning-based susceptibility source separation MRI.

Parkinson's disease (PD) involves pathological iron accumulation, yet MRI metrics, such as R2* or magnetic susceptibility (χ), lack mechanistic specif...

A Multi-center Gadolinium-ethoxybenzyl-diethylenetriamine Pentaacetic Acid (Gd-EOB-DTPA) MRI Dataset with Expert Annotations and clinicopathological data.

Liver resection is a cornerstone treatment for liver tumors, yet post-hepatectomy liver failure (PHLF) remains a severe and life-threatening complicat...

What Are Computer-Assisted Methods Achieving in Fine-Needle Aspiration Cytology of the Pancreas? A Systematic Review and Meta-Analysis.

OBJECTIVE: Pancreatic malignancies present major diagnostic challenges. The gold standard for diagnosis is endoscopic ultrasound-guided fine-needle as...

Comparison of systolic and diastolic CT-FFR for myocardial ischemia diagnosis.

BACKGROUND: CT-derived fractional flow reserve (CT-FFR) is a powerful tool for identifying hemodynamic ischemia. Coronary CT angiography (CCTA) images...

Prediction of myelosuppression in cervical cancer after concurrent chemoradiotherapy by CT radiomics-based model.

BACKGROUND: Concurrent chemoradiotherapy (CCRT) was highly effective in treating cervical cancer (CC) but raised the risk of bone marrow suppression. ...

Exploring the value of peritumoral brain zone for classification of two malignant brain tumors based on the MRI interpretable models.

OBJECTIVES: This study aims to develop and validate a novel multimodal interpretable artificial intelligence model capable of fusing radiomics feature...