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Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting

The recently developed magnetic resonance imaging (MRI) proton density fat fraction (PDFF) allows measurement of the fat in all segments of hepatic tissue. However, it is time consuming and inconvenient to measure each segment repeatedly. Moreover, volume of each segment also should be adjusted with...

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Autores principales: Lee, Hyeyoung, Jun, Dae Won, Kang, Bo-Kyeong, Nam, Eunwoo, Chang, Misoo, Kim, Mimi, Song, Soonyoung, Yoon, Byung Chul, Lee, Hang Lak, Lee, Oh Young, Choi, Ho Soon, Lee, Kang Nyeong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571698/
https://www.ncbi.nlm.nih.gov/pubmed/28816961
http://dx.doi.org/10.1097/MD.0000000000007778
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author Lee, Hyeyoung
Jun, Dae Won
Kang, Bo-Kyeong
Nam, Eunwoo
Chang, Misoo
Kim, Mimi
Song, Soonyoung
Yoon, Byung Chul
Lee, Hang Lak
Lee, Oh Young
Choi, Ho Soon
Lee, Kang Nyeong
author_facet Lee, Hyeyoung
Jun, Dae Won
Kang, Bo-Kyeong
Nam, Eunwoo
Chang, Misoo
Kim, Mimi
Song, Soonyoung
Yoon, Byung Chul
Lee, Hang Lak
Lee, Oh Young
Choi, Ho Soon
Lee, Kang Nyeong
author_sort Lee, Hyeyoung
collection PubMed
description The recently developed magnetic resonance imaging (MRI) proton density fat fraction (PDFF) allows measurement of the fat in all segments of hepatic tissue. However, it is time consuming and inconvenient to measure each segment repeatedly. Moreover, volume of each segment also should be adjusted with arithmetic mean of the selected segments when total amount of liver fat is estimated. Therefore, we try to develop a clinically-relevant and applicable method of estimating hepatic fat in PDFF image. A total of 164 adults were enrolled. We addressed the measurement frequency and segment selection to determine the optimal method of measuring intrahepatic fat. Total hepatic fat was estimated by the weighted mean of each segment reflecting their respective segmental volumes. We designed 2 models. In Model 1, we determined the segment order by which the mean was closest to the whole weighted mean. In Model 2, we determined the segment order by which the arithmetic mean of the selected segments was closest to the whole weighted mean. Fat fraction (FF) was most important risk factor of hepatic heterogeneity in multivariable analysis (β = 0.534, P < .001). In severe fatty liver (FF > 22.1%), intrahepatic fat variability was 2.47% (1.16–6.26%). The arithmetic mean total intrahepatic FF was 12.66%. But the weighted mean that applied to each segmental volume was 12.90%. In Model 1, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. However, when we added segment 8, the mean of segments 4, 5, and 8 was significantly different from the estimated total hepatic fat amount (P = .0021). In Model 2, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. There was a significant reduction in variability between segment 4 and segments 4 and 5 (P < .0001). Averaging the mean hepatic FF of segments 4 and 5 was the most reasonable method for estimating total intrahepatic fat in practice.
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spelling pubmed-55716982017-09-07 Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting Lee, Hyeyoung Jun, Dae Won Kang, Bo-Kyeong Nam, Eunwoo Chang, Misoo Kim, Mimi Song, Soonyoung Yoon, Byung Chul Lee, Hang Lak Lee, Oh Young Choi, Ho Soon Lee, Kang Nyeong Medicine (Baltimore) 4500 The recently developed magnetic resonance imaging (MRI) proton density fat fraction (PDFF) allows measurement of the fat in all segments of hepatic tissue. However, it is time consuming and inconvenient to measure each segment repeatedly. Moreover, volume of each segment also should be adjusted with arithmetic mean of the selected segments when total amount of liver fat is estimated. Therefore, we try to develop a clinically-relevant and applicable method of estimating hepatic fat in PDFF image. A total of 164 adults were enrolled. We addressed the measurement frequency and segment selection to determine the optimal method of measuring intrahepatic fat. Total hepatic fat was estimated by the weighted mean of each segment reflecting their respective segmental volumes. We designed 2 models. In Model 1, we determined the segment order by which the mean was closest to the whole weighted mean. In Model 2, we determined the segment order by which the arithmetic mean of the selected segments was closest to the whole weighted mean. Fat fraction (FF) was most important risk factor of hepatic heterogeneity in multivariable analysis (β = 0.534, P < .001). In severe fatty liver (FF > 22.1%), intrahepatic fat variability was 2.47% (1.16–6.26%). The arithmetic mean total intrahepatic FF was 12.66%. But the weighted mean that applied to each segmental volume was 12.90%. In Model 1, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. However, when we added segment 8, the mean of segments 4, 5, and 8 was significantly different from the estimated total hepatic fat amount (P = .0021). In Model 2, arithmetic mean of segments 4 and 5 was closest to the total estimated hepatic fat amount. There was a significant reduction in variability between segment 4 and segments 4 and 5 (P < .0001). Averaging the mean hepatic FF of segments 4 and 5 was the most reasonable method for estimating total intrahepatic fat in practice. Wolters Kluwer Health 2017-08-18 /pmc/articles/PMC5571698/ /pubmed/28816961 http://dx.doi.org/10.1097/MD.0000000000007778 Text en Copyright © 2017 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0
spellingShingle 4500
Lee, Hyeyoung
Jun, Dae Won
Kang, Bo-Kyeong
Nam, Eunwoo
Chang, Misoo
Kim, Mimi
Song, Soonyoung
Yoon, Byung Chul
Lee, Hang Lak
Lee, Oh Young
Choi, Ho Soon
Lee, Kang Nyeong
Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title_full Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title_fullStr Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title_full_unstemmed Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title_short Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting
title_sort estimating of hepatic fat amount using mri proton density fat fraction in a real practice setting
topic 4500
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5571698/
https://www.ncbi.nlm.nih.gov/pubmed/28816961
http://dx.doi.org/10.1097/MD.0000000000007778
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