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Computed Tomography Angiography

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On-Site Computed Tomography-Derived Fractional Flow Reserve Using a Machine-Learning Algorithm - Clinical Effectiveness in a Retrospective Multicenter Cohort.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: This study evaluated the diagnostic capability of on-site coronary computed tomography-derived computational fractional flow reserve (CT-FFR) determinations for detecting coronary artery disease (CAD), as assessed by invasive fractional f...

Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry.

AJR. American journal of roentgenology
Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR). However, attenuation values vary according to the tube voltage used, and i...

Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning.

Journal of cardiovascular computed tomography
In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs ...

Deep learning-based image restoration algorithm for coronary CT angiography.

European radiology
OBJECTIVES: The purpose of this study was to compare the image quality of coronary computed tomography angiography (CTA) subjected to deep learning-based image restoration (DLR) method with images subjected to hybrid iterative reconstruction (IR).

Cycle-consistent adversarial denoising network for multiphase coronary CT angiography.

Medical physics
PURPOSE: In multiphase coronary CT angiography (CTA), a series of CT images are taken at different levels of radiation dose during the examination. Although this reduces the total radiation dose, the image quality during the low-dose phases is signif...

Radiomics-Based Intracranial Thrombus Features on CT and CTA Predict Recanalization with Intravenous Alteplase in Patients with Acute Ischemic Stroke.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Thrombus characteristics identified on non-contrast CT (NCCT) are potentially associated with recanalization with intravenous (IV) alteplase in patients with acute ischemic stroke (AIS). Our aim was to determine the best radio...

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

European radiology
OBJECTIVES: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FF...

A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography.

IEEE transactions on medical imaging
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different management of patients with a coronary artery disease. Therefore, it is crucial to detect and classify the type of coronary artery plaque, as well as to de...

Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks.

Medical image analysis
Excellent image quality is a primary prerequisite for diagnostic non-invasive coronary CT angiography. Artifacts due to cardiac motion may interfere with detection and diagnosis of coronary artery disease and render subsequent treatment decisions mor...