정상 노화군과 경도인지장애 환자군의 18F-FDG-PET과 11C-PIB-PET 영상을 이용한 뇌 연결망 분석
Brain Connectivity Analysis using 18F-FDG-PET and 11C-PIB-PET Images of Normal Aging and Mild Cognitive Impairment Participants
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Recent research on mild cognitive impairment (MCI) has shown that cognitive and memory decline inthis disease is accompanied by disruptive changes in the brain functional network. However, there have been nograph-theoretical studies using 11C-PIB PET data of the Alzheimer’s Disease or mild cognitive impairment. In thisstudy, we acquired 18F-FDG PET and 11C-PIB PET images of twenty-four normal aging control participants and thirtyindividuals with MCI from ADNI (Alzheimer’s Disease Neuroimaging Initiative) database. Brain networks were constructedby thresholding binary correlation matrices using graph theoretical approaches. Both normal control andMCI group showed small-world property in 11C-PIB PET images as well as 18F-FDG PET images. 11C-PIB PETimages showed significant difference between NC (normal control) and MCI over large range of sparsity values. Thisresult will enable us to further analyze the brain using established graph-theoretical approaches for 11C-PIB PET images.
Abstract
Recent research on mild cognitive impairment (MCI) has shown that cognitive and memory decline inthis disease is accompanied by disruptive changes in the brain functional network. However, there have been nograph-theoretical studies using 11C-PIB PET data of the Alzheimer’s Disease or mild cognitive impairment. In thisstudy, we acquired 18F-FDG PET and 11C-PIB PET images of twenty-four normal aging control participants and thirtyindividuals with MCI from ADNI (Alzheimer’s Disease Neuroimaging Initiative) database. Brain networks were constructedby thresholding binary correlation matrices using graph theoretical approaches. Both normal control andMCI group showed small-world property in 11C-PIB PET images as well as 18F-FDG PET images. 11C-PIB PETimages showed significant difference between NC (normal control) and MCI over large range of sparsity values. Thisresult will enable us to further analyze the brain using established graph-theoretical approaches for 11C-PIB PET images.
참고문헌 (17)
- Nationwide Study on the Prevalence of Dementia in Korean Elders, "Ministy for Health, Welfare and Family Affairs", Ministy for Health, Welfare and Family Affairs, ~ (2008)
- E. Braak., "Neuropathology of Alzheimer’s disease : what is new since A. Alzheimer?", Eur. Arch. Psychiatry Clin. Neurosci., 249(Suppl), pp.14~22 (1999)
- M. D. Greicius., "Default-mode network activity distinguishes Alzheimer’s disease from healthy aging : evidence from functional MRI", Proc. Natl. Acad. Sci. U. S. A, 101(13), pp.4637~4642 (2004)
- D. Y. Lee., "Regional pattern of white matter microstructural changes in normal aging, MCI, and AD", Neurology, 73(21), pp.1722~1728 (2009)
- D. Watts., "Collective dynamics of ‘smallworld’networks", Nature, 393, pp.440~442 (1998)
- E. Bullmore., "Complex brain networks : graph theoretical analysis of structural and functional systems", Nat. Rev. Neurosci, 10(3), pp.186~198 (2009)
- Y. He., "Graph theoretical modeling of brain connectivity", Curr. Opin. Neurol, 23(4), pp.341~350 (2010)
- Y. He., "Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer’s Disease", J. Neurosci, 28(18), pp.4756~4766 (2008)
- M. Rubinov., "Complex network measures of brain connectivity : uses and interpretations", Neuroimage, 52(3), pp.1059~1069 (2010)
- J. Wang., "Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease", Biol Psychiatry, 73(5), pp.472~481 (2013)
- W. Zhu., "Changing topological patterns in normal aging using largescale structural networks", Neurobiol. Aging, 33(5), pp.899~913 (2012)
- 엄민희, "한국 아동 집단의 구조 뇌연결지도", Investigative Magnetic Resonance Imaging, 15(2), pp.110~122 (2011), 대한자기공명의과학회
- M. Jueptner., "Review : does measurement of regional cerebral blood flow reflect synaptic activity?-Implications for PET and fMRI", Neuroimage, 2(2), pp.148~156 (1995)
- E. Seo., "Whole-brain functional networks in cognitively normal, mild cognitive impairment, and Alzheimer’s disease", PLoS One, 8(1), pp.e53922~ (2013)
- J. Sepulcre., "In vivo characterization of the early states of the amyloid-beta network", Brain, 136(Pt 7), pp.2239~2252 (2013)
- J. Morris, "The Clinical Dementia Rating(CDR) : current version and scoring rules", Neurology, 43(11), pp.2412~2414 (1993)
- M. Folstein., "‘Mini-mental state’ : a practical method for grading the cognitive state of patients for the clinician", J. Psychiatr. Res, 12, pp.189~198 (1975)