Artifact Reduction in Interventional Devices Using Virtual Monoenergetic Images and Iterative Metal Artifact Reduction on Photon-Counting Detector CT.

Objectives: The aim of this study was to assess the impact of an iterative metal artifact reduction (iMAR) algorithm combined with virtual monoenergetic images (VMIs) for artifact reduction in photon-counting detector computed tomography (PCDCT) during interventions.

Materials And Methods: Using an abdominal phantom, we conducted evaluations on the efficacy of iMAR and VMIs for mitigating image artifacts during interventions on a PCDCT. Four different puncture devices were employed under 2 scan modes (QuantumSn at 100 kV, Quantumplus at 140 kV) to simulate various clinical scenarios.

Intra-individual Differences in Pericoronary Fat Attenuation Index Measurements Between Photon-counting and Energy-integrating Detector Computed Tomography.

Rationale And Objectives: The purpose of this study was to explore intra-individual differences in pericoronary adipose tissue (PCAT) fat attenuation index (FAI) between photon-counting detector (PCD)- and energy-integrating detector (EID)-CT.

Material And Methods: Patients were prospectively enrolled for a PCD-CT research scan within 30 days of EID-CT. Both acquisitions were reconstructed using a Qr36 kernel at 0.

Ultra-high gradient performance 3-Tesla MRI for super-fast and high-quality prostate imaging: initial experience.

Objectives: To implement and evaluate a super-fast and high-quality biparametric MRI (bpMRI) protocol for prostate imaging acquired at a new ultra-high gradient 3.0-T MRI system.

Methods: Participants with clinically suspected prostate cancer prospectively underwent a multiparametric MRI (mpMRI) on a new 3.

The Influence of Emphysema on Treatment Response to Biologic Therapy in Severe Asthma.

Background: Patients with severe asthma (SA) benefit from biologic therapy substantially. However, the impact of smoking-related comorbidities remains unclear due to the exclusion of patients with ≥10 pack-years from asthma studies. Our aim was to examine the effects of emphysema on biologic treatment response in SA in this retrospective cohort study.

Deep learning super-resolution reconstruction for fast and high-quality cine cardiovascular magnetic resonance.

Objectives: To compare standard-resolution balanced steady-state free precession (bSSFP) cine images with cine images acquired at low resolution but reconstructed with a deep learning (DL) super-resolution algorithm.

Materials And Methods: Cine cardiovascular magnetic resonance (CMR) datasets (short-axis and 4-chamber views) were prospectively acquired in healthy volunteers and patients at normal (cine: 1.89 × 1.