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Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI

Hyperintensities within the bilateral globus pallidus on T1-weighted magnetic resonance images were present in some liver cirrhosis patients with hepatic encephalopathy. The symptoms of covert hepatic encephalopathy are similar to those of mild dementia. We aimed to develop a new diagnostic index in...

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Autores principales: Tamai, Yasuyuki, Iwasa, Motoh, Yoshida, Yuichi, Nomoto, Jun, Kato, Takahiro, Asuke, Hiroe, Eguchi, Akiko, Takei, Yoshiyuki, Nakagawa, Hayato
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317893/
https://www.ncbi.nlm.nih.gov/pubmed/35885492
http://dx.doi.org/10.3390/diagnostics12071584
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author Tamai, Yasuyuki
Iwasa, Motoh
Yoshida, Yuichi
Nomoto, Jun
Kato, Takahiro
Asuke, Hiroe
Eguchi, Akiko
Takei, Yoshiyuki
Nakagawa, Hayato
author_facet Tamai, Yasuyuki
Iwasa, Motoh
Yoshida, Yuichi
Nomoto, Jun
Kato, Takahiro
Asuke, Hiroe
Eguchi, Akiko
Takei, Yoshiyuki
Nakagawa, Hayato
author_sort Tamai, Yasuyuki
collection PubMed
description Hyperintensities within the bilateral globus pallidus on T1-weighted magnetic resonance images were present in some liver cirrhosis patients with hepatic encephalopathy. The symptoms of covert hepatic encephalopathy are similar to those of mild dementia. We aimed to develop a new diagnostic index in which to distinguish hepatic encephalopathy from dementia. The globus pallidus signal hyperintensity was quantified using three-dimensional images. In addition, the new index value distribution was evaluated in a cohort of dementia patients. Signal intensity of globus pallidus significantly increased in liver cirrhosis patients with hepatic encephalopathy compared to those without hepatic encephalopathy (p < 0.05), healthy subjects (p < 0.05) or dementia patients (p < 0.001). Only 12.5% of liver cirrhosis patients without hepatic encephalopathy and 2% of dementia patients exceeded the new index cut-off value of 0.994, which predicts hepatic encephalopathy. One dementia patient in our evaluation had a history of liver cancer treatment and was assumed to have concomitant hepatic encephalopathy. The automatic assessment of signal intensity in globus pallidus is useful for distinguishing liver cirrhosis patients with hepatic encephalopathy from healthy subjects and liver cirrhosis patients without hepatic encephalopathy. Our image analyses exclude possible cases of hepatic encephalopathy from patients with neurocognitive impairment, including dementia.
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spelling pubmed-93178932022-07-27 Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI Tamai, Yasuyuki Iwasa, Motoh Yoshida, Yuichi Nomoto, Jun Kato, Takahiro Asuke, Hiroe Eguchi, Akiko Takei, Yoshiyuki Nakagawa, Hayato Diagnostics (Basel) Article Hyperintensities within the bilateral globus pallidus on T1-weighted magnetic resonance images were present in some liver cirrhosis patients with hepatic encephalopathy. The symptoms of covert hepatic encephalopathy are similar to those of mild dementia. We aimed to develop a new diagnostic index in which to distinguish hepatic encephalopathy from dementia. The globus pallidus signal hyperintensity was quantified using three-dimensional images. In addition, the new index value distribution was evaluated in a cohort of dementia patients. Signal intensity of globus pallidus significantly increased in liver cirrhosis patients with hepatic encephalopathy compared to those without hepatic encephalopathy (p < 0.05), healthy subjects (p < 0.05) or dementia patients (p < 0.001). Only 12.5% of liver cirrhosis patients without hepatic encephalopathy and 2% of dementia patients exceeded the new index cut-off value of 0.994, which predicts hepatic encephalopathy. One dementia patient in our evaluation had a history of liver cancer treatment and was assumed to have concomitant hepatic encephalopathy. The automatic assessment of signal intensity in globus pallidus is useful for distinguishing liver cirrhosis patients with hepatic encephalopathy from healthy subjects and liver cirrhosis patients without hepatic encephalopathy. Our image analyses exclude possible cases of hepatic encephalopathy from patients with neurocognitive impairment, including dementia. MDPI 2022-06-29 /pmc/articles/PMC9317893/ /pubmed/35885492 http://dx.doi.org/10.3390/diagnostics12071584 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tamai, Yasuyuki
Iwasa, Motoh
Yoshida, Yuichi
Nomoto, Jun
Kato, Takahiro
Asuke, Hiroe
Eguchi, Akiko
Takei, Yoshiyuki
Nakagawa, Hayato
Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title_full Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title_fullStr Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title_full_unstemmed Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title_short Development of a New Index to Distinguish Hepatic Encephalopathy through Automated Quantification of Globus Pallidal Signal Intensity Using MRI
title_sort development of a new index to distinguish hepatic encephalopathy through automated quantification of globus pallidal signal intensity using mri
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317893/
https://www.ncbi.nlm.nih.gov/pubmed/35885492
http://dx.doi.org/10.3390/diagnostics12071584
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