Gassenmaier, S.* ; Kähm, K.* ; Walter, S.S.* ; Machann, J. ; Nikolaou, K.* ; Bongers, M.N.*
Quantification of liver and muscular fat using contrast-enhanced Dual Source Dual Energy Computed Tomography compared to an established multi-echo Dixon MRI sequence.
Eur. J. Radiol. 142:109845 (2021)
PURPOSE: To investigate the feasibility of liver fat quantification in contrast-enhanced dual source dual energy computed tomography (DECT) using multi-echo Dixon magnetic resonance imaging (MRI) as reference standard. METHOD: Patients who underwent MRI of the liver including a multi-echo Dixon sequence for estimation of proton density fat fraction in 2017 as well as contrast-enhanced DECT imaging of the abdomen were included in this retrospective, monocentric IRB approved study. Furthermore, patients with a hepatic fat amount >5% who were examined in 2018 with MRI and DECT were included. The final study group consisted of 81 patients with 90 pairs of examinations. Analysis of parameter maps was performed manually using congruent regions of interest which were placed in the liver parenchyma, in the erector spinae muscles, and psoas major muscles. RESULTS: Mean patient age was 61 ± 13 years. Median time between MRI and DECT was 48 days. MRI liver fat quantification resulted in a median of 3.8% (IQR: 2.2-8.2%) compared to 1.8% (IQR: 0-6.3%) in DECT (p < 0.001), with a Spearman correlation of 0.73. Bland-Altman analysis resulted in a systematic underestimation of liver fat in DECT, with a mean difference of -1.7%. Fat quantification in the erector spinae muscles (p = 0.257) and the psoas major muscles (p = 0.208) was not significantly different in DECT compared to MRI. CONCLUSIONS: Liver and muscular fat quantification in portal-venous phase DECT is feasible with good to excellent correlation compared to a multi-echo Dixon MRI sequence analysis. While there is an underestimation of the liver fat content in DECT, there are no significant differences between DECT and MRI fat quantification of the erector spinae and psoas major muscles.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Typ der Hochschulschrift
Herausgeber
Schlagwörter
Dect ; Liver ; Magnetic Resonance Imaging ; Multidetector Computed Tomography; Multimaterial Decomposition Algorithm; American Association; Ct; Diagnosis; Management
Keywords plus
Sprache
englisch
Veröffentlichungsjahr
2021
Prepublished im Jahr
HGF-Berichtsjahr
2021
ISSN (print) / ISBN
0720-048X
e-ISSN
0720-048X
ISBN
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Konferenztitel
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Band: 142,
Heft: ,
Seiten: ,
Artikelnummer: 109845
Supplement: ,
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Verlag
Elsevier
Verlagsort
Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland
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0000-00-00
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Prüfer
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0000-00-00
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0000-00-00
Anmelder/Inhaber
weitere Inhaber
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Begutachtungsstatus
Peer reviewed
POF Topic(s)
90000 - German Center for Diabetes Research
Forschungsfeld(er)
Helmholtz Diabetes Center
PSP-Element(e)
G-502400-001
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Copyright
Erfassungsdatum
2021-08-04