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Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging
PURPOSE: To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for refe...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544898/ https://www.ncbi.nlm.nih.gov/pubmed/35713206 http://dx.doi.org/10.1002/mrm.29295 |
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author | Hoh, Tobias Vishnevskiy, Valery Polacin, Malgorzata Manka, Robert Fuetterer, Maximilian Kozerke, Sebastian |
author_facet | Hoh, Tobias Vishnevskiy, Valery Polacin, Malgorzata Manka, Robert Fuetterer, Maximilian Kozerke, Sebastian |
author_sort | Hoh, Tobias |
collection | PubMed |
description | PURPOSE: To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for reference. METHODS: Data were acquired using a 3D Cartesian pseudo‐spiral in‐out k‐t undersampling scheme (R = 10) and reconstructed using MI‐LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion‐compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame‐by‐frame CS using wavelets as sparsifying transform ([Formula: see text] ‐wavelet). Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In‐vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model. RESULTS: Improved uniformity of MBF maps with reduced local variations was achieved with MI‐LLR. For rest and stress, intra‐volunteer variation of absolute and relative MBF was lower in MI‐LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus [Formula: see text] ‐wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra‐subject MBF variation was reduced significantly with MI‐LLR. CONCLUSION: The combination of pseudo‐spiral Cartesian undersampling and dual‐stage MI‐LLR reconstruction improves free‐breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition. |
format | Online Article Text |
id | pubmed-9544898 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95448982022-10-14 Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging Hoh, Tobias Vishnevskiy, Valery Polacin, Malgorzata Manka, Robert Fuetterer, Maximilian Kozerke, Sebastian Magn Reson Med Research Articles–Imaging Methodology PURPOSE: To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for reference. METHODS: Data were acquired using a 3D Cartesian pseudo‐spiral in‐out k‐t undersampling scheme (R = 10) and reconstructed using MI‐LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion‐compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame‐by‐frame CS using wavelets as sparsifying transform ([Formula: see text] ‐wavelet). Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In‐vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model. RESULTS: Improved uniformity of MBF maps with reduced local variations was achieved with MI‐LLR. For rest and stress, intra‐volunteer variation of absolute and relative MBF was lower in MI‐LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus [Formula: see text] ‐wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra‐subject MBF variation was reduced significantly with MI‐LLR. CONCLUSION: The combination of pseudo‐spiral Cartesian undersampling and dual‐stage MI‐LLR reconstruction improves free‐breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition. John Wiley and Sons Inc. 2022-06-17 2022-10 /pmc/articles/PMC9544898/ /pubmed/35713206 http://dx.doi.org/10.1002/mrm.29295 Text en © 2022 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Research Articles–Imaging Methodology Hoh, Tobias Vishnevskiy, Valery Polacin, Malgorzata Manka, Robert Fuetterer, Maximilian Kozerke, Sebastian Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title | Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title_full | Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title_fullStr | Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title_full_unstemmed | Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title_short | Free‐breathing motion‐informed locally low‐rank quantitative 3D myocardial perfusion imaging |
title_sort | free‐breathing motion‐informed locally low‐rank quantitative 3d myocardial perfusion imaging |
topic | Research Articles–Imaging Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544898/ https://www.ncbi.nlm.nih.gov/pubmed/35713206 http://dx.doi.org/10.1002/mrm.29295 |
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