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1 result(s) for "Heeyoung Kim In Joo Kim Seong-Jang Kim Sang Heon Song Kyoungjune Pak Keunyoung Kim"
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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. 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 pailidus, 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.