Hongkai Wang1, Ziyu Tan1, Qiang Zheng2, Jing Yu3. 1. Department of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China. 2. Nuclear Medicine Division, Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, 116023, China. Oliver951101@outlook.com. 3. Nuclear Medicine Division, Second Affiliated Hospital, Dalian Medical University, Dalian, Liaoning, 116023, China.
Abstract
PURPOSE: Recent researches have demonstrated the value of using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. PROCEDURES: For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. RESULTS: We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. CONCLUSION: Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [18F]FDG-PET images and facilitates future study on human subjects.
PURPOSE: Recent researches have demonstrated the value of using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. PROCEDURES: For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. RESULTS: We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. CONCLUSION: Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [18F]FDG-PET images and facilitates future study on human subjects.
Authors: Betty M Tijms; Alle Meije Wink; Willem de Haan; Wiesje M van der Flier; Cornelis J Stam; Philip Scheltens; Frederik Barkhof Journal: Neurobiol Aging Date: 2013-03-28 Impact factor: 4.673