Diagnostic Performance of Dynamic Myocardial Perfusion Imaging Using Third-Generation Dual-Source Computed Tomography in Patients with Intermediate Pretest Probability of Coronary Artery Disease.

(1) Background: Our aim was to evaluate the diagnostic performance of combined coronary computed tomography angiography (CCTA) and dynamic CT myocardial perfusion imaging (CT-MPI) for detecting hemodynamically significant coronary artery disease (CAD) in patients with intermediate pretest probability. (2) Methods: Patients with an intermediate pretest probability of CAD were retrospectively enrolled. All patients underwent CCTA and dynamic CT-MPI using a third-generation dual-source CT scanner prior to invasive coronary angiography (ICA).

Image quality and radiation dose of reduced-dose abdominopelvic computed tomography (CT) with silver filter and deep learning reconstruction.

To assess the image quality and radiation dose between reduced-dose CT with deep learning reconstruction (DLR) using SilverBeam filter and standard dose with iterative reconstruction (IR) in abdominopelvic CT. In total, 182 patients (mean age ± standard deviation, 63 ± 14 years; 100 men) were included. Standard-dose scanning was performed with a tube voltage of 100 kVp, automatic tube current modulation, and IR reconstruction, whereas reduced-dose scanning was performed with a tube voltage of 120 kVp, a SilverBeam filter, and DLR.

Super-resolution deep learning image reconstruction: image quality and myocardial homogeneity in coronary computed tomography angiography.

Background: The recently introduced super-resolution (SR) deep learning image reconstruction (DLR) is potentially effective in reducing noise level and enhancing the spatial resolution. We aimed to investigate whether SR-DLR has advantages in the overall image quality and intensity homogeneity on coronary computed tomography (CT) angiography with four different approaches: filtered-back projection (FBP), hybrid iterative reconstruction (IR), DLR, and SR-DLR.

Methods: Sixty-three patients (mean age, 61 ± 11 years; range, 18-81 years; 40 men) who had undergone coronary CT angiography between June and October 2022 were retrospectively included.

A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial aneurysms.

Objectives: To investigate the usefulness of super-resolution deep learning reconstruction (SR-DLR) with cardiac option in the assessment of image quality in patients with stent-assisted coil embolization, coil embolization, and flow-diverting stent placement compared with other image reconstructions.

Methods: This single-centre retrospective study included 50 patients (mean age, 59 years; range, 44-81 years; 13 men) who were treated with stent-assisted coil embolization, coil embolization, and flow-diverting stent placement between January and July 2023. The images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (IR), and SR-DLR.