Radiology

Simulating quadrupolar NMR dynamics in solid electrolyte Li10GeP2S12.

Quadrupolar solid-state nuclear magnetic resonance (NMR) spectroscopy is an excellent tool to trace lithium (Li) ion diffusion in solid electrolytes due to its sensitivity to dynamics over timescales from nanoseconds to seconds. However, the structural and dynamical complexity of battery materials limits the unambiguous interpretation of experimental data. Fast ionic motion can partially average e...

Efficient Serum Metabolic Fingerprints for Ectopic Pregnancy Diagnosis and Rupture Risk Prediction.

Ectopic pregnancy (EP) is a leading cause of maternal morbidity and mortality in early pregnancy. Current diagnostic approaches, which rely on ultrasound scanning and blood measurements, are limited by low detection sensitivity. Herein, we propose a one-step system that uses EP-associated serum metabolic fingerprints (ESF) for efficient EP diagnosis and risk prediction. The system employs nanopart...

Explainable Machine Learning for Coma Outcome Prediction Based on Structural and Functional Brain MRI.

OBJECTIVES: Advanced MRI is recommended for the clinical evaluation of patients with coma. However, the implementation of these guidelines has been hi...

Liquid-Sequencer: A Lightweight Liquid Neural Network for Real-Time Fetal Congenital Heart Disease Diagnosis.

Congenital heart disease (CHD) is the leading cause of neonatal mortality worldwide, making early and accurate diagnosis crucial. In resource-constrai...

Clinical Grading of Artificial Intelligence-Based 3D Fetal Brain Segmentations: A Cross-Vendor Evaluation of Deep Learning in Fetal Neuroimaging.

OBJECTIVE: To evaluate the performance of automated (sub)cortical fetal brain segmentation methods on a novel 3D ultrasound dataset acquired from a di...

Outcomes with revascularization vs. medical therapy according to plaque burden from coronary computed tomography angiography.

AIMS: We aimed to investigate whether plaque burden from coronary computed tomography angiography (CCTA) could be used to identify patients potentiall...

Automated subcutaneous fat segmentation with a convolutional neural network in magnetic resonance guided high-intensity focused ultrasound treatment for uterine fibroids.

INTRODUCTION: In MR-guided high-intensity focused ultrasound (MR-HIFU) treatment for uterine fibroids, the subcutaneous abdominal fat layer is prone t...

Feasibility study of fast nuclide identification for beta-emitting sources using learning-based models.

This study investigates the feasibility of rapidly identifying beta-emitting radionuclides based on the beta spectrum data measured in air using learn...

Preoperative identification of deep myometrial invasion in endometrial cancer: a multicenter MRI study with a vision foundation model-enhanced multimodal deep learning framework.

OBJECTIVE: To develop and validate a Vision Foundation Model-enhanced Multimodal Deep Learning Radiomics (VFM-MDLR) framework that integrates MR imagi...

Thermal signatures in breast cancer: Deciphering latent biomarkers through deep learning and explainable AI.

Breast cancer, characterized by its aggressive pro-gression and high mortality rates, continues to be among the most common types of cancer. While ear...

Integrating Multimodal Neuroimaging and Physical-Health Markers for Autism Spectrum Disorder in the ABCD Study.

BACKGROUND: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by diverse presentations, which complicates the ide...

From permeability to prediction: evolving strategies for evaluating oral drug absorption.

Oral drug administration, preferred for patient compliance and convenience, encounters significant bioavailability challenges arising from complex phy...

A transparent, lightweight and sustainable Green Learning AI model for prostate cancer detection on MRI.

OBJECTIVES: To develop a novel transparent and lightweight machine learning model, the Green Learning (GL), for automated prostate segmentation (PS) a...

Beyond Human Variability: Deep Learning for Intravascular Ultrasound Segmentation With Noisy Labels.

OBJECTIVE: Intravascular ultrasound (IVUS) is an imaging modality that provides cross-sectional visualization of the coronary lumen and vessels. To ad...

Current Status and Future Perspective for Bladder Cancer MR Imaging and the Vesical Imaging-Reporting and Data System (VI-RADS) in Japan: Challenges and Solutions.

Bladder cancer carries one of the highest lifetime costs among malignancies, and accurate distinction between non-muscle-invasive and muscle-invasive ...

Radiopharmaceuticals: Status, Regulatory Landscape and Future Perspective.

Radiopharmaceuticals are biologically active molecules labeled with radionuclides that have advanced the possibility of the nuclear medicine. They sup...

Right and Left Atrial Dysfunction as Independent Cardiovascular Risk Factors: A UK Biobank Study.

BACKGROUND: Atrial cardiopathy often precedes atrial fibrillation (AF) and has emerged as an independent risk factor for cardiovascular outcomes. Howe...

Fully automated segmentation of foot bones using machine learning and convolutional neural networks.

BackgroundRecent advancements in medical imaging technology have significantly increased the prevalence of automatic and semi-automatic segmentation t...

EEG microstate-derived dynamic network biomarkers for lateralization and structural etiology in temporal lobe epilepsy.

OBJECTIVE: Temporal lobe epilepsy (TLE) is the most common focal epilepsy but remains highly heterogeneous across hemispheric and structural etiology....

Attenuation correction of cardiac 82Rb pet using deep learning generated synthetic CT.

Ischemic heart disease remains a leading cause of mortality worldwide. Myocardial perfusion imaging (MPI) using Rubidium-82 (82Rb) positron emission t...