AI Medical Compendium Topic

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Plaque, Atherosclerotic

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Prospective deep learning-based quantitative assessment of coronary plaque by computed tomography angiography compared with intravascular ultrasound: the REVEALPLAQUE study.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography provides non-invasive assessment of coronary stenosis severity and flow impairment. Automated artificial intelligence (AI) analysis may assist in precise quantification and characterization of coronary a...

Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study.

Clinical cardiology
BACKGROUND: Stent malapposition (SM) following percutaneous coronary intervention (PCI) for myocardial infarction continues to present significant clinical challenges. In recent years, machine learning (ML) models have demonstrated potential in disea...

[Deep Learning-Based Artificial Intelligence Model for Automatic Carotid Plaque Identification].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
This study aims at developing a dataset for determining the presence of carotid artery plaques in ultrasound images, composed of 1761 ultrasound images from 1165 participants. A deep learning architecture that combines bilinear convolutional neural n...

Classification of Carotid Plaque with Jellyfish Sign Through Convolutional and Recurrent Neural Networks Utilizing Plaque Surface Edges.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In carotid arteries, plaque can develop as localized elevated lesions. The Jellyfish sign, marked by fluctuating plaque surfaces with blood flow pulsation, is a dynamic characteristic of these plaques that has recently attracted attention. Detecting ...

Enhancing coronary artery plaque analysis via artificial intelligence-driven cardiovascular computed tomography.

Therapeutic advances in cardiovascular disease
Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality of cardiac structures and vasculature considered comparable to invasive coronary angiography for the evaluation of coronary artery disease (CAD) in several major cardio...

A Video-based Automated Tracking and Analysis System of Plaque Burden in Carotid Artery Using Deep Learning: A Comparison with Senior Sonographers.

Current medical imaging
BACKGROUND AND OBJECTIVE: The incidence of stroke is rising, and it is the second major cause of mortality and the third leading cause of disability around the globe. The goal of this study was to rapidly and accurately identify carotid plaques and a...

Enhanced Diagnosis of Plaque Erosion by Deep Learning in Patients With Acute Coronary Syndromes.

JACC. Cardiovascular interventions
BACKGROUND: Acute coronary syndromes caused by plaque erosion might be potentially managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires expertise in optical coherence tomographic (OCT) image interpretation. In ...

Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.

Journal of biomedical optics
SIGNIFICANCE: Coronary heart disease has the highest rate of death and morbidity in the Western world. Atherosclerosis is an asymptomatic condition that is considered the primary cause of cardiovascular diseases. The accumulation of low-density lipop...

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

The Lancet. Digital health
BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of p...