Cargando…
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 ± ...
Autores principales: | , , , , , , |
---|---|
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 |
_version_ | 1784756075410489344 |
---|---|
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). |
format | Online Article Text |
id | pubmed-9321550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT fanlexiaozi optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT hongkyungpyo optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT hsuliyueh optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT carrjamesc optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT allenbradleyd optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT leedanielc optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri AT kimdaniel optimalsaturationrecoverytimeforminimizingtheunderestimationofarterialinputfunctioninquantitativecardiacperfusionmri |