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Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma

INTRODUCTION: To evaluate the effectiveness of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging (MRI) to discriminate between symptomatic and asymptomatic myeloma in lumbar bone marrow without visible focal lesions. MATERIAL...

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Autores principales: Takasu, Miyuki, Kaichi, Yoko, Tani, Chihiro, Date, Shuji, Akiyama, Yuji, Kuroda, Yoshiaki, Sakai, Akira, Awai, Kazuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338220/
https://www.ncbi.nlm.nih.gov/pubmed/25706753
http://dx.doi.org/10.1371/journal.pone.0116842
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author Takasu, Miyuki
Kaichi, Yoko
Tani, Chihiro
Date, Shuji
Akiyama, Yuji
Kuroda, Yoshiaki
Sakai, Akira
Awai, Kazuo
author_facet Takasu, Miyuki
Kaichi, Yoko
Tani, Chihiro
Date, Shuji
Akiyama, Yuji
Kuroda, Yoshiaki
Sakai, Akira
Awai, Kazuo
author_sort Takasu, Miyuki
collection PubMed
description INTRODUCTION: To evaluate the effectiveness of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging (MRI) to discriminate between symptomatic and asymptomatic myeloma in lumbar bone marrow without visible focal lesions. MATERIALS AND METHODS: The lumbar spine was examined with 3-T MRI in 11 patients with asymptomatic myeloma and 24 patients with symptomatic myeloma. The fat-signal fraction was calculated from the ratio of the signal intensity in the fat image divided by the signal intensity of the corresponding ROI in the in-phase IDEAL image. The t test was used to compare the asymptomatic and symptomatic groups. ROC curves were constructed to determine the ability of variables to discriminate between symptomatic and asymptomatic myeloma. RESULTS: Univariate analysis showed that β2-microglobulin and bone marrow plasma cell percent (BMPC%) were significantly higher and fat-signal fraction was significantly lower with symptomatic myeloma than with asymptomatic myeloma. Areas under the curve were 0.847 for β(2);-microglobulin, 0.834 for fat-signal fraction, and 0.759 for BMPC%. CONCLUSION: The fat-signal fraction as a biomarker for multiple myeloma enables discrimination of symptomatic myeloma from asymptomatic myeloma. The fat-signal fraction offers superior sensitivity and specificity to BMPC% of biopsy specimens.
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spelling pubmed-43382202015-03-04 Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma Takasu, Miyuki Kaichi, Yoko Tani, Chihiro Date, Shuji Akiyama, Yuji Kuroda, Yoshiaki Sakai, Akira Awai, Kazuo PLoS One Research Article INTRODUCTION: To evaluate the effectiveness of iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) magnetic resonance imaging (MRI) to discriminate between symptomatic and asymptomatic myeloma in lumbar bone marrow without visible focal lesions. MATERIALS AND METHODS: The lumbar spine was examined with 3-T MRI in 11 patients with asymptomatic myeloma and 24 patients with symptomatic myeloma. The fat-signal fraction was calculated from the ratio of the signal intensity in the fat image divided by the signal intensity of the corresponding ROI in the in-phase IDEAL image. The t test was used to compare the asymptomatic and symptomatic groups. ROC curves were constructed to determine the ability of variables to discriminate between symptomatic and asymptomatic myeloma. RESULTS: Univariate analysis showed that β2-microglobulin and bone marrow plasma cell percent (BMPC%) were significantly higher and fat-signal fraction was significantly lower with symptomatic myeloma than with asymptomatic myeloma. Areas under the curve were 0.847 for β(2);-microglobulin, 0.834 for fat-signal fraction, and 0.759 for BMPC%. CONCLUSION: The fat-signal fraction as a biomarker for multiple myeloma enables discrimination of symptomatic myeloma from asymptomatic myeloma. The fat-signal fraction offers superior sensitivity and specificity to BMPC% of biopsy specimens. Public Library of Science 2015-02-23 /pmc/articles/PMC4338220/ /pubmed/25706753 http://dx.doi.org/10.1371/journal.pone.0116842 Text en © 2015 Takasu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Takasu, Miyuki
Kaichi, Yoko
Tani, Chihiro
Date, Shuji
Akiyama, Yuji
Kuroda, Yoshiaki
Sakai, Akira
Awai, Kazuo
Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title_full Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title_fullStr Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title_full_unstemmed Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title_short Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation (IDEAL) Magnetic Resonance Imaging as a Biomarker for Symptomatic Multiple Myeloma
title_sort iterative decomposition of water and fat with echo asymmetry and least-squares estimation (ideal) magnetic resonance imaging as a biomarker for symptomatic multiple myeloma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4338220/
https://www.ncbi.nlm.nih.gov/pubmed/25706753
http://dx.doi.org/10.1371/journal.pone.0116842
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