ID | 113041 |
Title Alternative | Hepatectomy using EOB-MRI
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Author |
Yamada, Shinichiro
Tokushima University
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Shimada, Mitsuo
Tokushima University
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Morine, Yuji
Tokushima University
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Ikemoto, Tetsuya
Tokushima University
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Saitou, Yu
Tokushima University
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Takasu, Chie
Tokushima University
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Yoshikawa, Masato
Tokushima University
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Content Type |
Journal Article
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Description | Background and aim
Dynamic magnetic resonance imaging with gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (EOB-MRI) can be used not only to detect liver tumors but also to estimate liver function. The aim of this study was to establish a new EOB-MRI-based formula to determine the resection limit in patients undergoing hepatectomy. Methods Twenty-eight patients with a normal liver (NL group) and five with an unresectable cirrhotic liver (UL group) who underwent EOB-MRI were included. Standardized liver function (SLF) was calculated based on the signal intensity (SI), the volume of each subsegment (S1–S8), and body surface area. A formula defining the resection limit was devised based on the difference in the SLF values of patients in the NL and UL groups. The formula was validated in 50 patients who underwent EOB-MRI and hepatectomy. Results The average SLF value in the NL and UL groups was 2038 and 962 FV/m2, respectively. The difference (1076 FV/m2) was consistent with a 70% in resection volume. Thus, the resection limit for hepatectomy was calculated as a proportion of 70%: 70×(SLF−962)/1076 (%). The one patient who underwent hepatectomy over the resection limit died due to liver failure. In other 49 patients, in whom the resection volume was less than the resection limit, procedures were safely performed. Conclusions Our formula for resection limit based on EOB-MRI can improve the safety of hepatectomy. |
Journal Title |
PLOS ONE
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ISSN | 19326203
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Publisher | PLOS
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Volume | 14
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Issue | 1
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Start Page | e0210579
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Published Date | 2019-01-25
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Rights | © 2019 Yamada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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language |
eng
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departments |
University Hospital
Medical Sciences
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