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Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI

PURPOSE: The purpose of this study was to determine an optimal saturation‐recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject. METHODS: We scanned 18 subjects (mean age = 59 ± ...

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Autores principales: Fan, Lexiaozi, Hong, Kyungpyo, Hsu, Li‐Yueh, Carr, James C., Allen, Bradley D., Lee, Daniel C., Kim, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321550/
https://www.ncbi.nlm.nih.gov/pubmed/35377476
http://dx.doi.org/10.1002/mrm.29240
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author Fan, Lexiaozi
Hong, Kyungpyo
Hsu, Li‐Yueh
Carr, James C.
Allen, Bradley D.
Lee, Daniel C.
Kim, Daniel
author_facet Fan, Lexiaozi
Hong, Kyungpyo
Hsu, Li‐Yueh
Carr, James C.
Allen, Bradley D.
Lee, Daniel C.
Kim, Daniel
author_sort Fan, Lexiaozi
collection PubMed
description PURPOSE: The purpose of this study was to determine an optimal saturation‐recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject. METHODS: We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress‐rest perfusion data using a 5‐fold accelerated pulse sequence with radial k‐space sampling and applied k‐space weighted image contrast (KWIC) filters on the same k‐space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal‐total‐variation and temporal‐principal‐component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton‐density‐weighted‐image, signal‐to‐T(1) conversion using a Bloch equation, T(1)‐to‐gadolinium‐concentration conversion assuming fast water exchange, T(2)* correction to the AIF, and gadolinium‐concentration to myocardial blood flow (MBF) conversion based on a Fermi model. RESULTS: Among five TS values, the shortest TS (10 ms) produced significantly (P < 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL g(−1) min(−1)) than 12.8 ms (11.24 mM, 0.89 mL g(−1) min(−1)), 15.6 ms (9.56 mM, 1.05 mL g(−1) min(−1)), 18.4 ms (8.55 mM, 1.17 mL g(−1) min(−1)), and 21.2 ms (7.95 mM, 1.27 mL g(−1) min(−1)). Similarly, shorter TS reduced underestimation of AIF (or overestimation of MBF) for both during stress and at rest, but this effect was canceled in myocardial‐perfusion‐reserve (MPR). CONCLUSION: This study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8‐21.2 ms).
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spelling pubmed-93215502022-07-30 Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI Fan, Lexiaozi Hong, Kyungpyo Hsu, Li‐Yueh Carr, James C. Allen, Bradley D. Lee, Daniel C. Kim, Daniel Magn Reson Med Technical Notes–Imaging Methodology PURPOSE: The purpose of this study was to determine an optimal saturation‐recovery time (TS) for minimizing the underestimation of arterial input function (AIF) in quantitative cardiac perfusion MRI without multiple gadolinium injections per subject. METHODS: We scanned 18 subjects (mean age = 59 ± 14 years, 9/9 males/females) to acquire resting perfusion data and 1 additional subject (age = 38 years, male) to obtain stress‐rest perfusion data using a 5‐fold accelerated pulse sequence with radial k‐space sampling and applied k‐space weighted image contrast (KWIC) filters on the same k‐space data to retrospectively reconstruct five AIF images with effective TS ranging from 10 to 21.2 ms (2.8 ms steps). Undersampled images were reconstructed using a compressed sensing framework with temporal‐total‐variation and temporal‐principal‐component as 2 orthogonal sparsifying transforms. The image processing steps included, same motion correction across five different AIF images, signal normalization by the proton‐density‐weighted‐image, signal‐to‐T(1) conversion using a Bloch equation, T(1)‐to‐gadolinium‐concentration conversion assuming fast water exchange, T(2)* correction to the AIF, and gadolinium‐concentration to myocardial blood flow (MBF) conversion based on a Fermi model. RESULTS: Among five TS values, the shortest TS (10 ms) produced significantly (P < 0.05) higher peak AIF and lower resting MBF (13.73 mM, 0.73 mL g(−1) min(−1)) than 12.8 ms (11.24 mM, 0.89 mL g(−1) min(−1)), 15.6 ms (9.56 mM, 1.05 mL g(−1) min(−1)), 18.4 ms (8.55 mM, 1.17 mL g(−1) min(−1)), and 21.2 ms (7.95 mM, 1.27 mL g(−1) min(−1)). Similarly, shorter TS reduced underestimation of AIF (or overestimation of MBF) for both during stress and at rest, but this effect was canceled in myocardial‐perfusion‐reserve (MPR). CONCLUSION: This study demonstrates that TS of 10 ms reduces the underestimation of AIF and, hence, the overestimation of MBF compared with longer TS values (12.8‐21.2 ms). John Wiley and Sons Inc. 2022-04-04 2022-08 /pmc/articles/PMC9321550/ /pubmed/35377476 http://dx.doi.org/10.1002/mrm.29240 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 Technical Notes–Imaging Methodology
Fan, Lexiaozi
Hong, Kyungpyo
Hsu, Li‐Yueh
Carr, James C.
Allen, Bradley D.
Lee, Daniel C.
Kim, Daniel
Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title_full Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title_fullStr Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title_full_unstemmed Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title_short Optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion MRI
title_sort optimal saturation recovery time for minimizing the underestimation of arterial input function in quantitative cardiac perfusion mri
topic Technical Notes–Imaging Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321550/
https://www.ncbi.nlm.nih.gov/pubmed/35377476
http://dx.doi.org/10.1002/mrm.29240
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