eprintid: 10134941
rev_number: 21
eprint_status: archive
userid: 608
dir: disk0/10/13/49/41
datestamp: 2021-09-23 10:06:57
lastmod: 2022-08-21 06:10:21
status_changed: 2021-09-23 10:06:57
type: article
metadata_visibility: show
creators_name: Jaubert, O
creators_name: Steeden, J
creators_name: Montalt-Tordera, J
creators_name: Arridge, S
creators_name: Kowalik, GT
creators_name: Muthurangu, V
title: Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease
ispublished: pub
divisions: UCL
divisions: B02
divisions: D14
divisions: GA1
divisions: B04
divisions: C05
divisions: F48
keywords: Cardiac MRI, Congenital heart disease, Real time, Flow imaging, Image reconstruction, Machine learning
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
abstract: PURPOSE: Real-time spiral phase contrast MR (PCMR) enables rapid free-breathing assessment of flow. Target spatial and temporal resolutions require high acceleration rates often leading to long reconstruction times. Here we propose a deep artifact suppression framework for fast and accurate flow quantification. METHODS: U-Nets were trained for deep artifact suppression using 520 breath-hold gated spiral PCMR aortic datasets collected in congenital heart disease patients. Two spiral trajectories (uniform and perturbed) and two losses (Mean Absolute Error -MAE- and average structural similarity index measurement -SSIM-) were compared in synthetic data in terms of MAE, peak SNR (PSNR) and SSIM. Perturbed spiral PCMR was prospectively acquired in 20 patients. Stroke Volume (SV), peak mean velocity and edge sharpness measurements were compared to Compressed Sensing (CS) and Cartesian reference. RESULTS: In synthetic data, perturbed spiral consistently outperformed uniform spiral for the different image metrics. U-Net MAE showed better MAE and PSNR while U-Net SSIM showed higher SSIM based metrics. In-vivo, there were no significant differences in SV between any of the real-time reconstructions and the reference standard Cartesian data. However, U-Net SSIM had better image sharpness and lower biases for peak velocity when compared to U-Net MAE. Reconstruction of 96 frames took ~59 s for CS and 3.9 s for U-Nets. CONCLUSION: Deep artifact suppression of complex valued images using an SSIM based loss was successfully demonstrated in a cohort of congenital heart disease patients for fast and accurate flow quantification.
date: 2021-11
date_type: published
official_url: https://doi.org/10.1016/j.mri.2021.08.005
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1884741
doi: 10.1016/j.mri.2021.08.005
lyricists_name: Arridge, Simon
lyricists_name: Jaubert, Olivier
lyricists_name: Kowalik, Grzegorz
lyricists_name: Muthurangu, Vivek
lyricists_name: Steeden, Jennifer
lyricists_id: SRARR14
lyricists_id: OJAUB16
lyricists_id: GKOWA82
lyricists_id: VMUTH99
lyricists_id: JAEDG41
actors_name: Muthurangu, Vivek
actors_id: VMUTH99
actors_role: owner
full_text_status: public
publication: Magnetic Resonance Imaging
volume: 83
pagerange: 125-132
citation:        Jaubert, O;    Steeden, J;    Montalt-Tordera, J;    Arridge, S;    Kowalik, GT;    Muthurangu, V;      (2021)    Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease.                   Magnetic Resonance Imaging , 83    pp. 125-132.    10.1016/j.mri.2021.08.005 <https://doi.org/10.1016/j.mri.2021.08.005>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10134941/3/Muthurangu_Deep%20artifact%20suppression%20for%20spiral%20real-time%20phase%20contrast%20cardiac%20magnetic%20resonance%20imaging%20in%20congenital%20heart%20disease_AAM.pdf