Radiology

[Innovative imaging techniques for urothelial carcinoma].

BACKGROUND: Imaging guides the staging of urothelial carcinoma and thus plays a central role in treatment decisions. Current guidelines reflect the increasing importance of multiparametric MRI (mpMRI) of the bladder with standardized reporting according to the Vesical Imaging Reporting and Data System (VI-RADS). MATERIALS AND METHODS: This work comprises a narrative, guideline-oriented update base...

Artificial intelligence in estimating instantaneous wave-free ratio: a systematic literature review of techniques.

Fractional flow reserve (FFR) is an essential tool for evaluating coronary artery disease and directing percutaneous coronary intervention (PCI). The instantaneous wave-free ratio (iFR) has been validated as a non-hyperemic alternative with less procedural complexity and adverse effects, as no pharmacological induction of hyperemia is required. Nevertheless, iFR invasiveness limits the popularity ...

A new model based on multi-axis vision transformer for chondromalacia patella diagnosis in magnetic resonance scans.

A degenerative disease of the patellofemoral joint cartilage, chondromalacia patella (CMP) often results in anterior knee discomfort and functional di...

Evaluation of an artificial intelligence model for the identification of obstructive hydrocephalus on computed tomography of the head.

OBJECTIVE: Obstructive hydrocephalus is a critical radiographic finding requiring emergent treatment. Its identification on head CT by an AI model cou...

Development and interpretation of a dual-energy CT-based deep learning radiomics model for predicting new cerebral ischemic lesions after carotid artery stenting: a multicenter study.

OBJECTIVES: Early recognition of individuals at elevated risk for new ipsilateral ischemic lesions (NIILs) after carotid artery stenting (CAS) is vita...

Enhancing diagnostic safety with low iodine, low radiation CTPA classification using deep learning.

Pulmonary embolism (PE) is a life-threatening condition for which computed tomography pulmonary angiography (CTPA) is the standard diagnostic modality...

Comparison of Image Quality Reconstructed Using Iterative Reconstruction and Deep Learning Algorithms Under Varying Dose Reductions in Dual-Energy Carotid CT Angiography.

Carotid CT angiography (CTA) is valuable for diagnosing carotid artery disease but involves radiation and contrast agent risks. Deep Learning Image Re...

An ensemble machine learning classifier for Parkinson's disease diagnosis using optical coherence tomography angiography.

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder worldwide, yet its early diagnosis remains a major challenge due to the abs...

Clinical Profile of Neurosurgical Consultations from the Emergency Department : A Retrospective Analysis.

OBJECTIVE: This study aimed to retrospectively analyze consultations requested from the emergency departments (EDs) to the neurosurgery (NS) departmen...

Artificial intelligence risk stratification from dynamic digital subtraction angiography radiomics predicts pulmonary embolism and associates with clinical outcomes in deep vein thrombosis: A retrospective cohort study.

OBJECTIVE: Current risk stratification for lower extremity deep vein thrombosis remains limited, often failing to identify high-risk patients for impe...

Clinical-radiological machine learning model for non-invasive diagnosis and stratification of peripheral artery disease: a multicenter study.

BACKGROUND AND OBJECTIVE: Peripheral artery disease (PAD) is an atherosclerotic disorder prevalent in the elderly that leads to peripheral function de...

AI-based analysis of label-free live cell imaging of T-cell mediated tumor killing assay enables competitive and robust hit calling.

For the discovery and optimization of personalized cancer treatments using immune cell therapeutics, such as T-cell receptor (TCR-T) therapy and bispe...

Comparison of bulk flow measurements in the large vessels between four-dimensional flow (4D-flow) and two-dimensional phase contrast (2D-PC) magnetic resonance imaging (MRI).

AIM: The clinical integration of four-dimensional flow magnetic resonance imaging (4D-flow MRI) for cardiovascular assessment remains a challenge due ...

Incremental prognostic value of immune cell densities beyond clinical parameters in non-small cell lung cancer.

BACKGROUND: Multiplex immunofluorescence imaging enables detailed characterization of the tumor immune microenvironment, but whether immune cell densi...

Pilot clinical evaluation of artificial intelligence-driven guiding catheter simulation for optimizing percutaneous coronary intervention.

AIMS: In percutaneous coronary intervention (PCI), a suboptimal choice of guiding catheter may compromise coaxial alignment and backup support, prolon...

Development and Validation of a Machine Learning Model That Uses Voice to Predict Aspiration Risk.

BACKGROUND: Aspiration causes or aggravates a variety of respiratory diseases. Subjective bedside evaluations of aspiration are limited by poor inter-...

Topology-aware multiclass segmentation of the Circle of Willis from MRA and CTA images.

The Circle of Willis (CoW) is an essential network of arteries that ensures blood flow throughout the brain. From a clinical perspective, evaluating t...

Machine learning-based prediction of CAC-defined cardiovascular risk using routine health examination data: a retrospective cross-sectional study in a Taiwanese population.

BACKGROUND: Early identification of individuals at elevated cardiovascular risk using routine health examination data is essential for preventive card...

Motion-Informed 3D Deep Learning Reconstruction in Patients with Cognitive Impairment.

BACKGROUND AND PURPOSE: Motion artifacts remain a key limitation in brain MRI, particularly during 3D acquisitions in cognitively impaired patients. M...

Automated Detection of Cervical Spinal Cord Compression on MRI Using YOLO11 Deep Learning Architecture: A Two-Center External Validation Study.

STUDY DESIGN: Retrospective two-center external validation study conducted at two medical centers, collecting cervical spine MRI data from patients su...