In the past few years, computed tomography coronary angiography (CTCA) has rapidly become a widely used diagnostic tool in several clinical settings and is recommended by the European guidelines with a high degree of recommendation in patients with s...
To assess the utility of dual-energy CT scanning (DECTs) with popliteal artery (PA) monitoring in dual low-dose (radiation and contrast) lower-extremity CT angiography (LE-CTA). 135 patients undergoing LE-CTA were prospectively included and divided i...
Endovascular Aneurysm Repair (EVAR) is a minimally invasive procedure crucial for treating abdominal aortic aneurysms (AAA), where precise pre-operative planning is essential. Current clinical methods rely on manual measurements, which are time-consu...
PURPOSE: This study proposes a novel deep learning-based approach for aneurysm wall characteristics, including thin-walled (TW) and hyperplastic-remodeling (HR) regions.
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...
Background Precise assessment of myocardial ischemia burden and cardiovascular risk stratification based on dynamic CT myocardial perfusion imaging (MPI) is lacking. Purpose To develop and validate a deep learning (DL) model for automated quantificat...
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...
Subtraction computed tomography angiography (sCTA) can effectively separate enhanced cerebral arteries from similar signal intensity and proximity (i.e., vertebrae and skull). However, sCTA is not considered mainstream because of the high radiation d...
OBJECTIVE: Compare the image quality of image reconstructed using deep learning-based image reconstruction (DLIR) and iterative reconstruction algorithms for head and neck dual-energy CT angiography (DECTA).
Background Chest pain is a leading cause of outpatient and emergency department visits; advancements in artificial intelligence (AI) could improve coronary CT angiography (CCTA) workflows for these patients. Purpose To evaluate the performance of an ...