Atherosclerosis

Morphological parameters contributing to aneurysm rupture: Identifying the rogue from the mugshot using different statistical methods.

INTRODUCTION: Current scores that discriminate rupture status/rupture-associated morphology of aneurysm rupture rely on size being >7 mm, ignoring important morphological parameters. This study applies advanced statistical methods on historical patient data to identify morphological features associated with aneurysms rupture. METHODS: Data from 429 aneurysms along with demographics and morphologic...

Region-Specific Evaluation of Plaque Segmentation in Cross-sectional Projections of Carotid Ultrasound Images Using Deep Learning Models in a Sub-clinical Atherosclerosis Cohort.

OBJECTIVE: Detection of atherosclerotic plaque in the carotid arteries is essential for early cardiovascular risk assessment. While B-mode ultrasound is the standard imaging modality, most deep learning studies focus on longitudinal views of the common carotid artery, with limited investigation of cross-sectional imaging and other clinically relevant regions such as the carotid bulb and split. To ...

Protocol for a Radial Pulse-Based Vascular Age Index Integrated with Traditional Korean Medicine Pulse Diagnosis.

OBJECTIVES: Vascular aging, a central determinant of cardiovascular risk, is commonly assessed by pulse wave velocity (PWV)-based indices such as caro...

Secondary prevention of recurrent ischemic stroke: from guidelines to precision medicine.

Recurrent ischemic stroke remains a major global health challenge, accounting for substantial disability and mortality despite advances in acute manag...

Statin adherence among patients with hypertension in Swedish primary health care: a QregPV cohort study using explainable machine learning.

AIMS: Evidence regarding statin adherence among patients with hypertension in primary care is limited. We assessed statin adherence in Swedish primary...

Proteomic signatures as biomarkers of atherosclerosis burden.

AIMS: Atherosclerosis is currently evaluated by imaging, but scalable circulating biomarkers to detect its presence and quantify overall burden are la...

Bioactive Natural Products in Cardiovascular Disease: Focus on Thrombotic Events.

Bioactive compounds derived from natural products (NPs) continue to attract considerable scientific interest due to their wide range of beneficial bio...

Real-world integration of an autonomous artificial intelligence system for diabetic retinopathy screening in an endocrinology outpatient clinic.

AIM: To evaluate a real-world clinical integration of an autonomous artificial intelligence (AI) system (AEYE Diagnostic Screening (AEYE-DS), AEYE Hea...

Comparative analysis of quantitative fundus results of the left and right eyes and screening for coronary atherosclerotic disease: a binocular study.

BACKGROUND: Retinal microvascular parameters are potential biomarkers for systemic vascular health. This study aimed to assess the interocular consist...

The diagnostic and predictive value of AI-combined multilayer spiral CT for MACE after emergency PCI in STEMI patients: A prospective cohort study.

ST-segment elevation myocardial infarction (STEMI) patients remain at substantial risk for major adverse cardiovascular events (MACE) following emerge...

Disulfidptosis-related signatures identify SPARC+/CYR61+ stromal cells mediating immunosuppression in gastric cancer.

BACKGROUND: Disulfidptosis is a novel form of glucose starvation-induced cell death, yet its prognostic implications in gastric cancer (GC) remain lar...

Machine Learning-Based single-cell characterization of lipid metabolic reprogramming in prostate cancer.

Prostate cancer (PCa) is one of the most prevalent malignancies in men worldwide, and metabolic reprogramming particularly of lipid metabolism plays a...

Interpretable machine learning reveals the synergistic impact of essential hypertension on early recurrence in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) patients often ential hypertension, yet how systemic vascular stress synergizes with tumor aggressiveness to driv...

Maternal circulating lipid metabolic heterogeneity in preeclampsia: machine learning identifies clinically distinct subtypes.

BACKGROUND: Preeclampsia is associated with dyslipidemia. Maternal circulating lipid profiles may reflect underlying placental-metabolic interactions....

The Unseen Aneurysm: Can Artificial Intelligence Bridge the Diagnostic Gap in Angiogram-Negative Subarachnoid Hemorrhage?

Evaluating expert decision-pattern alignment in endovascular planning for intracranial aneurysms using a multimodal large language model.

BACKGROUND: Endovascular treatment planning for intracranial aneurysms requires integrating vascular geometry, branch preservation, device feasibility...

Hypoperfusion Intensity Ratio as a Predictive Marker in Pre-Endovascular Treatment Perfusion MRI for Acute Middle Cerebral Artery Occlusion with Intracranial Atherosclerosis.

Introduction Identifying the cause of MCA occlusion before endovascular treatment (EVT) in acute ischemic stroke is useful. Hypoperfusion intensity ra...

AneuSI: A software tool to isolate a region of interest in cerebral aneurysms from full geometrical models.

BACKGROUND AND OBJECTIVE: Modeling cerebral aneurysms using patient-specific geometries demands significant computational resources, particularly when...

Benzo(a)pyrene aggregating lung inflammation via inducing IL1R1 expression in asthma: Insights from network toxicology, single-cell transcriptomics, and Mendelian randomization.

OBJECTIVE: Exposure to benzo(a)pyrene (BaP) negatively affects lung inflammation in patients with asthma. However, there is a lack of systematic resea...

Multicenter evaluation of real-time artificial intelligence assistance for carotid artery stenting.

BACKGROUND: Unintended device movement during carotid artery stenting (CAS) may lead to procedural complications. Our previous preliminary single-cent...