Objectives While the link between carotid plaque composition and cerebrovascular vascular
(CVE) events is recognized, the role of calcium configuration remains unclear. This study …

BACKGROUND: This study aimed to develop and validate a computed tomography
angiography based machine learning model that uses plaque composition data and degree …

Purposes Radiomics is a quantitative method able to analyze a high-throughput extraction of
minable imaging features. Herein, we aim to develop a CT angiography-based radiomics …

AIM To develop and validate a deep learning (DL) algorithm for the automated detection and
classification of carotid artery plaques (CAPs) on computed tomography angiography (CTA) …

AIM To develop and validate a radiomics nomogram for identifying high-risk carotid plaques
on computed tomography (CT) angiography (CTA). MATERIALS AND METHODS A total of …

Background Primary to validate a commercial semi-automated computed tomography
angiography (CTA)–software for vulnerable plaque detection compared to histology of …

BACKGROUND AND PURPOSE: CT is considered the standard reference both for
quantification and characterization of carotid artery calcifications. Our aim was to investigate …

Aim Calcium burden measurement in internal carotid artery (ICA) plaque could play an
important role in assessing stroke risk and stenosis quantification in the ICA. We propose an …

Purpose To develop and validate a combined model incorporating conventional clinical and
imaging characteristics and radiomics signatures based on head and neck computed …

Objective This study aimed to develop and validate a machine learning model incorporating
both dual-energy computed tomography (DECT) angiography quantitative parameters and …