Atherosclerosis

Jointly Learned 3D Non-Cartesian Sampling With Wave Encoding and Reconstruction for Neurovascular Phase Contrast MRI.

PURPOSE: To develop accelerated 3D phase contrast (PC) MRI using jointly learned wave encoding and reconstruction. METHODS: Pseudo-fully sampled neurovascular 4D flow data (N = 40) and a simulation framework were used to learn phase encoding locations, wave readout parameters, and model-based reconstruction network (MoDL) for a rapid 3D PC scan (2.25 min). Parameters were also learned for an other...

Predictors of glycemic control with imeglimin for type 2 diabetes: Results of machine learning analyses using clinical trial data.

INTRODUCTION: Identifying patient characteristics predictive of treatment response is crucial for optimizing type 2 diabetes outcomes. Using data from three phase 2/3 imeglimin trials in Japan, this analysis applied machine learning to determine characteristics associated with HbA1c improvement. METHODS: Regression tree and random forest methods identified baseline characteristics predictive of Hb...

Sex-specific cardiovascular risk prediction using AI-derived epicardial adipose tissue measurements on CT calcium scoring exams.

BACKGROUND: The Agatston CAC score from CT-calcium scoring (CTCS) is a standard guideline recommended measure for cardiovascular risk assessment that ...

Major depressive disorder and Hashimoto's thyroiditis: Shared immunometabolic signatures revealed by integrative transcriptomics.

Major depressive disorder (MDD) and Hashimoto's thyroiditis (HT) frequently co-occur, yet their shared molecular underpinnings remain unclear. We perf...

Development and validation of a novel machine learning-based algorithm to predict incident atrial fibrillation: A multicohort analysis.

BACKGROUND: Existing atrial fibrillation (AF) risk prediction models incorporate race as a covariate, systematically underestimating AF risk in black ...

Statin-Induced Decade-Long Stabilization of Noncalcified Coronary Plaque Despite a Zero Calcium Score.

BACKGROUND: A 48-year-old man with a coronary artery calcium (CAC) score of 0 underwent serial artificial intelligence (AI)-assisted coronary computed...

Precision medicine in Moyamoya vasculopathy.

PURPOSE OF REVIEW: Moyamoya vasculopathy is a progressive cerebrovascular steno-occlusive disease with variable presentation. As revascularization tec...

Gut microbiome profiles and associated functional pathways are linked to Mediterranean diet adherence and blood glucose control in adults with type 1 diabetes mellitus.

BACKGROUND AND AIMS: The Mediterranean diet (MD) has been associated with better glycaemic control in children with type 1 diabetes mellitus (T1DM) an...

The AENEAS Project: Intraoperative Anatomical Guidance Through Real-Time Landmark Detection Using Machine Vision.

OBJECTIVE: To investigate the performance of a deep learning machine vision-based model in identifying anatomical landmarks in a complex microsurgical...

Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces.

Abdominal aortic aneurysms (AAAs) are progressive focal dilatations of the abdominal aorta. AAAs may rupture, with fatal consequences in >80% of cases...

Personalized adrenal gland volume reference ranges and development of a fully automated deep learning screening tool.

OBJECTIVE: This study aims to develop a low-dose CT-based, fully automated deep learning tool for screening adrenal gland volume abnormalities and est...

Membrane-Penetrating Molecular Device Based on a Triplex Containing Acyclic L-Threoninol Nucleic Acid Functionalized with Cholesterol.

Membrane-penetrating molecular devices are valuable biological tools. Herein, we describe membrane-targeting molecular devices based on the triplexes ...

Clinically oriented deep learning framework for automated vessel wall segmentation in black-blood MRI: a multi-center study.

OBJECTIVES: To develop and validate a clinically applicable deep learning framework for automated segmentation of intracranial and carotid vessel wall...

Enhanced Visualization of Intracranial Cortical Arteries Using Deep Learning Reconstruction in Vessel Wall MR Imaging.

This study evaluated the utility of deep learning reconstruction (DLR) in vessel wall imaging (VWI) for visualizing the entire cerebral arterial syste...

Unsupervised machine learning for identifying morphological phenotypes in abdominal aortic aneurysms using fully automated volume-segmented imaging: a multicentre cohort study.

AIMS: Thrombo- and microembolic complications following abdominal aortic aneurysm (AAA) repair are hypothesized to be associated with wall thrombus bu...

Sex differences in plaque burden and outcomes in symptomatic patients with suspected coronary artery disease.

BACKGROUND: Sex-related differences in coronary artery disease (CAD) burden and outcomes are increasingly recognized but not fully understood, particu...

Effects of Real-Time Notification of AI-Detected Incidental Coronary Artery Calcium on Statin Prescription: The NOTIFY-PICTURE Trial.

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approach to identify individuals at risk for heart failur...

Evaluation of Approved AI-based Brain Aneurysm Detection Software in Clinical Practice: Comparison with Radiologist Assessment and Image Re-review.

PURPOSE: This study evaluated the performance of artificial intelligence (AI)-based brain aneurysm detection software in clinical settings, aiming to ...

Anterior segment optical coherence tomography in uveitis: A comprehensive review of clinical applications, diagnostic insights, and future directions.

Anterior segment optical coherence tomography (AS-OCT) is emerging as an essential tool in the diagnosis and monitoring of uveitis. Offering noninvasi...