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Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆

This study adapted a statistical probabilistic anatomical map of the brain for single photon emission computed tomography images of depressive end-stage renal disease patients. This research aimed to investigate the relationship between symptom clusters, disease severity, and cerebral blood flow. Tw...

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Autores principales: Kim, Heeyoung, Kim, In Joo, Kim, Seong-Jang, Song, Sang Heon, Pak, Kyoungjune, Kim, Keunyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4281418/
https://www.ncbi.nlm.nih.gov/pubmed/25558229
http://dx.doi.org/10.3969/j.issn.1673-5374.2012.27.010
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author Kim, Heeyoung
Kim, In Joo
Kim, Seong-Jang
Song, Sang Heon
Pak, Kyoungjune
Kim, Keunyoung
author_facet Kim, Heeyoung
Kim, In Joo
Kim, Seong-Jang
Song, Sang Heon
Pak, Kyoungjune
Kim, Keunyoung
author_sort Kim, Heeyoung
collection PubMed
description This study adapted a statistical probabilistic anatomical map of the brain for single photon emission computed tomography images of depressive end-stage renal disease patients. This research aimed to investigate the relationship between symptom clusters, disease severity, and cerebral blood flow. Twenty-seven patients (16 males, 11 females) with stages 4 and 5 end-stage renal disease were enrolled, along with 25 healthy controls. All patients underwent depressive mood assessment and brain single photon emission computed tomography. The statistical probabilistic anatomical map images were used to calculate the brain single photon emission computed tomography counts. Asymmetric index was acquired and Pearson correlation analysis was performed to analyze the correlation between symptom factors, severity, and regional cerebral blood flow. The depression factors of the Hamilton Depression Rating Scale showed a negative correlation with cerebral blood flow in the left amygdale. The insomnia factor showed negative correlations with cerebral blood flow in the left amygdala, right superior frontal gyrus, right middle frontal gyrus, and left middle frontal gyrus. The anxiety factor showed a positive correlation with cerebral glucose metabolism in the cerebellar vermis and a negative correlation with cerebral glucose metabolism in the left globus pallidus, right inferior frontal gyrus, both temporal poles, and left parahippocampus. The overall depression severity (total scores of Hamilton Depression Rating Scale) was negatively correlated with the statistical probabilistic anatomical map results in the left amygdala and right inferior frontal gyrus. In conclusion, our results demonstrated that the disease severity and extent of cerebral blood flow quantified by a probabilistic brain atlas was related to various brain areas in terms of the overall severity and symptom factors in end-stage renal disease patients.
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spelling pubmed-42814182015-01-02 Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆ Kim, Heeyoung Kim, In Joo Kim, Seong-Jang Song, Sang Heon Pak, Kyoungjune Kim, Keunyoung Neural Regen Res Techniques and Methods: Emerging Technology in Neural Regeneration This study adapted a statistical probabilistic anatomical map of the brain for single photon emission computed tomography images of depressive end-stage renal disease patients. This research aimed to investigate the relationship between symptom clusters, disease severity, and cerebral blood flow. Twenty-seven patients (16 males, 11 females) with stages 4 and 5 end-stage renal disease were enrolled, along with 25 healthy controls. All patients underwent depressive mood assessment and brain single photon emission computed tomography. The statistical probabilistic anatomical map images were used to calculate the brain single photon emission computed tomography counts. Asymmetric index was acquired and Pearson correlation analysis was performed to analyze the correlation between symptom factors, severity, and regional cerebral blood flow. The depression factors of the Hamilton Depression Rating Scale showed a negative correlation with cerebral blood flow in the left amygdale. The insomnia factor showed negative correlations with cerebral blood flow in the left amygdala, right superior frontal gyrus, right middle frontal gyrus, and left middle frontal gyrus. The anxiety factor showed a positive correlation with cerebral glucose metabolism in the cerebellar vermis and a negative correlation with cerebral glucose metabolism in the left globus pallidus, right inferior frontal gyrus, both temporal poles, and left parahippocampus. The overall depression severity (total scores of Hamilton Depression Rating Scale) was negatively correlated with the statistical probabilistic anatomical map results in the left amygdala and right inferior frontal gyrus. In conclusion, our results demonstrated that the disease severity and extent of cerebral blood flow quantified by a probabilistic brain atlas was related to various brain areas in terms of the overall severity and symptom factors in end-stage renal disease patients. Medknow Publications & Media Pvt Ltd 2012-09-25 /pmc/articles/PMC4281418/ /pubmed/25558229 http://dx.doi.org/10.3969/j.issn.1673-5374.2012.27.010 Text en Copyright: © Neural Regeneration Research http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Techniques and Methods: Emerging Technology in Neural Regeneration
Kim, Heeyoung
Kim, In Joo
Kim, Seong-Jang
Song, Sang Heon
Pak, Kyoungjune
Kim, Keunyoung
Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title_full Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title_fullStr Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title_full_unstemmed Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title_short Quantification of Tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: Correlation with disease severity and symptom factors☆
title_sort quantification of tc-99m-ethyl cysteinate dimer brain single photon emission computed tomography images using statistical probabilistic brain atlas in depressive end-stage renal disease patients: correlation with disease severity and symptom factors☆
topic Techniques and Methods: Emerging Technology in Neural Regeneration
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4281418/
https://www.ncbi.nlm.nih.gov/pubmed/25558229
http://dx.doi.org/10.3969/j.issn.1673-5374.2012.27.010
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