Version 1
: Received: 29 January 2024 / Approved: 30 January 2024 / Online: 31 January 2024 (01:46:33 CET)
How to cite:
Ozpeynirci, Y.; Gorodezky, M.; Sanches, A.F.; Solana, A.B.; Liebig, T. Impact of Various Non-contrast Enhanced MRA Techniques on Lumen Visibility in Vascular Flow Models with Surpass Evolve Flow Diverter. Preprints2024, 2024012077. https://doi.org/10.20944/preprints202401.2077.v1
Ozpeynirci, Y.; Gorodezky, M.; Sanches, A.F.; Solana, A.B.; Liebig, T. Impact of Various Non-contrast Enhanced MRA Techniques on Lumen Visibility in Vascular Flow Models with Surpass Evolve Flow Diverter. Preprints 2024, 2024012077. https://doi.org/10.20944/preprints202401.2077.v1
Ozpeynirci, Y.; Gorodezky, M.; Sanches, A.F.; Solana, A.B.; Liebig, T. Impact of Various Non-contrast Enhanced MRA Techniques on Lumen Visibility in Vascular Flow Models with Surpass Evolve Flow Diverter. Preprints2024, 2024012077. https://doi.org/10.20944/preprints202401.2077.v1
APA Style
Ozpeynirci, Y., Gorodezky, M., Sanches, A.F., Solana, A.B., & Liebig, T. (2024). Impact of Various Non-contrast Enhanced MRA Techniques on Lumen Visibility in Vascular Flow Models with Surpass Evolve Flow Diverter. Preprints. https://doi.org/10.20944/preprints202401.2077.v1
Chicago/Turabian Style
Ozpeynirci, Y., Ana Beatriz Solana and Thomas Liebig. 2024 "Impact of Various Non-contrast Enhanced MRA Techniques on Lumen Visibility in Vascular Flow Models with Surpass Evolve Flow Diverter" Preprints. https://doi.org/10.20944/preprints202401.2077.v1
Abstract
Background: Silent MRA has shown promising results in evaluating the stents used for intracranial aneurysm treatment. A deep learning-based algorithm was recently introduced by GE. The purpose of this study was to compare the performance of several MRA techniques in lumen visibility in silicone models with flow diverter stents.
Methods: Two Surpass Evolve stents of different sizes were implanted in two silicone tubes. The tubes were placed in separate boxes in straight position and in two different curve configurations and connected to a pulsatile pump to construct a flow loop. Using a GE 3.0T scanner, TOF and silent MRA images were acquired, and deep learning reconstruction was applied to the silent MRA dataset. Intra-luminal signal intensity in the stent (SIin-stent), in the tube outside the stent (SIvessel) and of the background (SIbg) were measured for each scan.
Results: The SIin-stent/SIbg and SIin-stent/SIv ratio were higher on silent scans and DL-based reconstructions than on TOF images. The stent tips created severe artefacts on TOF images, which could not be observed on silent scans.
Conclusions: Our study demonstrated that the DL algorithm improved the quality of the silent technique in evaluating the flow diverter stent patency.
Keywords
silent MRA; deep learning; flow diverter; intracranial aneurysm
Subject
Medicine and Pharmacology, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
