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Imaging Diagnosis of Central Nervous System Damage in Patients with T2DM.
Zhang, Weiting; Zhao, Weina; Wang, Jialiang; Xu, Qing; Li, Siou; Yin, Changhao.
Afiliação
  • Zhang W; Department of Endocrinology, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China.
  • Zhao W; Department of Neurology, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China.
  • Wang J; Development of Pharmacy, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China.
  • Xu Q; Department of Neurology, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China.
  • Li S; Department of Endocrinology, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China. Electronic address: lisiou7916@sina.com.
  • Yin C; Department of Neurology, Mudanjiang Medical University, Affiliated Hongqi Hospital, Heilongjiang, 157011, China; Heilongjiang Key Laboratory of Ischemic Stroke Prevention and Treatment, Heilongjiang, 157011, China. Electronic address: yinchanghao7916@sina.com.
Neurosci Lett ; 733: 135092, 2020 08 10.
Article em En | MEDLINE | ID: mdl-32454146
ABSTRACT
This paper uses resting-state functional magnetic resonance imaging (rs-FMRI) to construct a whole-brain binary functional network through a complex brain network analysis theory based on graph theory to explore the functional network of patients with type 2 diabetes (T2DM). Changes in topological properties and their potential relationships with fasting blood glucose (FBG), glycated haemoglobin (HbAlc), and cognitive function scale, and further explore the diagnostic value of rs-FMRI technology for central nervous system damage in T2DM patients, for clinical diagnosis and treatment Provide objective radiological evidence. In the range of sparsity (Sp) of 0.05 to 0.50 and a step size of 0.01, compared with the random network, the resting brain functional networks in the T2DM group and the HC group have larger clustering coefficients and similar shortest paths. Length and small world index greater than 1, that is, both groups of resting brain functional networks have small world characteristics. The MoCA score of the T2DM group was positively correlated with the node degree (r = 0.400, p = 0.043) and the node efficiency (r = 0.452, p = 0.021) of the right straight back. FBG is positively correlated with the node degree of the left occipital gyrus (r = 0.422, p = 0.023); HbAlc is related to the node degree of the left occipital gyrus (r = 0.372, p = 0.043) and the node degree of the left occipital gyrus (r = 0.382, p = 0.037) was positively correlated with the node intermediary (r = 0.388, p = 0.034) at the back of the right cingulate gyrus. The topological properties of the resting brain function network of T2DM patients with negative MRI findings have changed compared with normal people, indicating that T2DM is an important factor leading to brain function damage, further explaining the rs-fMRI technology and complex brain networks based on graph theory Analysis theory can be used as an effective method to study the changes of brain function in T2DM patients.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Diabetes Mellitus Tipo 2 Tipo de estudo: Diagnostic_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Diabetes Mellitus Tipo 2 Tipo de estudo: Diagnostic_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article