Impact of deep Learning-enhanced contrast on diagnostic accuracy in stroke CT angiography.

Purpose: To examine the impact of deep learning-augmented contrast enhancement on image quality and diagnostic accuracy of poorly contrasted CT angiography in patients with suspected stroke.

Methods: This retrospective single-centre study included 102 consecutive patients who underwent CT imaging for suspected stroke between 01/2021 and 12/2022, including whole brain volume perfusion CT (VPCT) and, specifically, a poorly contrasted CT angiography (defined as < 350HU in the proximal MCA). CT angiography imaging data was reconstructed using i.

Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study.

To evaluate the effect of a vendor-agnostic deep learning denoising (DLD) algorithm on diagnostic image quality of non-contrast cranial computed tomography (ncCT) across five CT scanners.This retrospective single-center study included ncCT data of 150 consecutive patients (30 for each of the five scanners) who had undergone routine imaging after minor head trauma. The images were reconstructed using filtered back projection (FBP) and a vendor-agnostic DLD method.

Improvement of Neurovascular Imaging Using Ultra-High-Resolution Computed Tomography Angiography.

Objective: To evaluate diagnostic image quality of ultra-high-resolution computed tomography angiography (UHR-CTA) in neurovascular imaging as compared to normal resolution CT-angiography (NR-CTA).

Material And Methods: In this retrospective single-center study brain and neck CT-angiography was performed using an ultra-high-resolution computed tomography scanner (n = 82) or a normal resolution CT scanner (NR-CTA; n = 73). Ultra-high-resolution images were reconstructed with a 1024 × 1024 matrix and a slice thickness of 0.

Gender differences in self-assessed performance and stress level during training of basic interventional radiology maneuvers.

Objectives: Gender differences have been reported to influence medical training. We investigated gender differences encountered during training in interventional radiology maneuvers.

Methods: Catheter handling was analyzed under standardized conditions in 64 participants naïve to endovascular procedures (26 women, 38 men).

Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI.

Rationale And Objectives: To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T.

Materials And Methods: Thirty consecutive patients who underwent clinically indicated MRI at a 1.

Clinical feasibility and validation of the accelerated T2 mapping sequence GRAPPATINI in brain imaging.

Rationale And Objectives: To prospectively evaluate feasibility and robustness of an accelerated T2 mapping sequence (GRAPPATINI) in brain imaging and to assess its synthetic T2-weighted images (sT2w) in comparison with a standard T2-weighted sequence (T2 TSE).

Material And Methods: Volunteers were included to evaluate the robustness and consecutive patients for morphological evaluation. They were scanned on a 3 T MR-scanner.

Single-Energy Metal Artifact Reduction (SEMAR) in Ultra-High-Resolution CT Angiography of Patients with Intracranial Implants.

Purpose: To evaluate the effects of single-energy metal artifact reduction (SEMAR) on image quality of ultra-high-resolution CT-angiography (UHR-CTA) with intracranial implants after aneurysm treatment.

Methods: Image quality of standard and SEMAR-reconstructed UHR-CT-angiography images of 54 patients who underwent coiling or clipping was retrospectively evaluated. Image noise (i.

Feasibility of Ultra-High Resolution Supra-Aortic CT Angiography: An Assessment of Diagnostic Image Quality and Radiation Dose.

(1) : To evaluate diagnostic image quality and radiation exposure of ultra-high resolution cerebral Computed-Tomography (CT) angiography (CTA) obtained on an ultra-high resolution computed tomography scanner (UHR-CT). (2) : Fifty consecutive patients with UHR-CTA were enrolled. Image reconstruction was processed with a 1024 × 1024 matrix and a slice thickness of 0.