Radiology

Randomized controlled trials in valvular heart disease: the evolving role of multimodality imaging.

Valvular heart disease represents a significant global health burden, with an estimated prevalence of 2.5% in high-income countries and projected increases due to population ageing. Randomized controlled trials in valvular heart disease have undergone substantial evolution, shifting from mortality-focused endpoints toward comprehensive assessments integrating imaging parameters and patient-centere...

NIAID Biodosimetry Strategic Plan.

In the face of emerging threats from natural disasters, nuclear accidents, and potential malicious use of radiation, the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH) has created the "2024 NIH Strategic Plan and Research Agenda for Development of Radiation Biodosimetry Approaches Against Radiological and Nuclear Threats." This document represent...

Deep Learning Identification of Clear Cell Renal Cell Carcinoma on MR Imaging.

OBJECTIVE: To investigate the performance of various convolutional neural networks (CNNs) in identifying clear renal cell carcinoma (ccRCC) on MRI and...

Machine Learning Algorithm to Predict Change in the Decision-Making for Thoracolumbar Fractures Without Neurological Deficit After MRI: A Multicenter Study.

Study DesignA multicenter study.ObjectiveTo develop a machine learning algorithm to predict when magnetic resonance imaging (MRI) may change the thora...

[Imaging of eosinophilic pneumonia : Differential diagnosis in radiological practice].

CLINICAL/METHODICAL ISSUE: Eosinophilic pneumonias are rare inflammatory lung diseases with heterogeneous clinical presentation and variable computer ...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinica...

Primary tumor-derived, multiparametric MRI-based deep learning-radiomics-clinical model for predicting lymph node metastasis in early-stage cervical cancer.

OBJECTIVES: To develop and validate a primary tumor-derived, multiparametric MRI-based deep learning-radiomics-clinical (DLRC) model for predicting pe...

CBCT assisted diagnosis system for temporomandibular joint disc displacement based on deep learning.

BACKGROUND: The diagnosis of temporomandibular joint (TMJ) disc displacement relies on clinical symptoms and magnetic resonance imaging (MRI), which i...

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence...

ChatGPT-4 reliability when applied to the regional anesthesia technique sonoanatomy.

BACKGROUND: Ultrasound-guided regional anesthesia is commonly used to enhance perioperative analgesia. However, the technique is limited by inter-oper...

Association of epicardial adipose tissue with markers of cardiac remodelling and clinical outcomes in asymptomatic aortic stenosis.

BACKGROUND: Previous studies have suggested an adverse role of epicardial adipose tissue (EAT) in aortic stenosis (AS), potentially mediated by direct...

High-Resolution MRI Using Artificial Intelligence-Assisted Acceleration and Radial Dynamic Contrast Enhancement for Improved Detection of Pituitary Microadenomas in Cushing's Disease.

BACKGROUND AND PURPOSE: Accurate detection of pituitary microadenomas is critical for the diagnosis and treatment of Cushing's disease (CD). However, ...

Deep learning for synthetic PET imaging: a systematic mapping review of techniques, metrics, and clinical relevance.

BACKGROUND: Synthetic positron emission tomography (PET) imaging, enabled by deep learning, represents a promising approach to minimize radiation expo...

Integrating standard and native spaces for radiomics and brain network analysis in Alzheimer's disease diagnosis and prognosis.

INTRODUCTION: Structural MRI analysis for Alzheimer's disease (AD) is limited by balancing group-level comparability in standard space with anatomical...

Cardiac MR function analysis with DL-based super resolution reconstruction: application in the clinical setting.

To assess differences in volumetry, image quality and acquisition time between balanced steady-state free precession cine sequences acquired using (a)...

Glymphatic dysfunction in trigeminal neuralgia: A multimodal MRI study.

BACKGROUND: Trigeminal neuralgia (TN) has traditionally been attributed to peripheral neurovascular compression at the trigeminal nerve root entry zon...

PCOSFusionNet: Hybrid Deep Feature Fusion Network for PCOS Classification from Ultrasound Images of Ovaries.

Polycystic Ovary Syndrome (PCOS) is a leading cause of female infertility and is associated with various health complications, including preterm abort...

CGLK-GNN : A connectome generation network with large kernels for GNN based Alzheimer's disease analysis.

Alzheimer's disease (AD) is a currently incurable neurodegenerative disease, with early detection representing a high research priority. AD is charact...

Physics-informed graph neural networks for flow field estimation in carotid arteries.

Hemodynamic quantities are valuable biomedical risk factors for cardiovascular pathology such as atherosclerosis. Non-invasive, in-vivo measurement of...

The potential of optical coherence tomography angiography in progressive multiple sclerosis.

Early detection and monitoring of neurodegenerative processes in persons with multiple sclerosis (PwMS) is currently a major challenge. Optical cohere...