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postgraduate thesis: Comparision between volumetric and DKI parametric analyses of hippocampus for correlations with MMSE scores in patients with Alzheimer's disease

TitleComparision between volumetric and DKI parametric analyses of hippocampus for correlations with MMSE scores in patients with Alzheimer's disease
Authors
Issue Date2013
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Au, C. A. [歐浚林]. (2013). Comparision between volumetric and DKI parametric analyses of hippocampus for correlations with MMSE scores in patients with Alzheimer's disease. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5091297
AbstractVolumetric analysis (VA) in magnetic resonance imaging (MRI) has provided great comprehension of the neuroanatomical changes associated to normal cognition and progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD), the most common form of dementia. However, the use of VA has primarily focused in gray matter changes; the emergence of diffusion tensor imaging (DTI) has allowed a better understanding of the microstructural changes in both white and gray matters in MCI and AD patients, with numerous studies showing DTI to be more sensitive than VA in discriminating between MCI to AD. Diffusion kurtosis imaging (DKI), an extension of DTI, is speculated to be more sensitive in detecting changes due to differences in mathematical modeling, as it accounts for non-Gaussian diffusion in the brain. Studies using DKI suggested kurtosis parameters—axial, radial, and mean kurtoses—are able to provide further microstructural details in additional information to tensor and diffusion parameters, namely axial, radial, and mean diffusivities, and fractional anisotropy. In this study, DKI is compared to DTI and VA in an attempt to evaluate the sensitivities of each technique. DKI of all four cerebral lobes and VA of the hippocampus were performed in 30 patients, 18 diagnosed with AD and 12 with MCI. Mann-Whitney U test was performed to determine differences between MCI and AD, and correlations between diffusion parameters and hippocampal volume to mini-mental state examination (MMSE) scores as a biomarker of cognitive function were tested using Pearson’s R correlation test. MMSE scores were statistically different between sexes (p = 0.025) and between MCI and AD groups (p = 0.048), as well as positively correlated with age (p = 0.004). A marginal trend was observed in the hippocampal volume between MCI and AD (p = 0.077), and did not significantly correlate with MMSE. Several diffusivity and kurtosis parameters were significantly different between MCI and AD groups in the white and gray matters of the parietal and occipital lobes. Only tensor parameters had significant negative correlations with MMSE scores in within-group analyses of the two lobes. Correlational tests of white and gray matters of all four lobes to MMSE scores revealed more significant correlations between tensor parameters than kurtosis parameters. Findings from the present study provide further evidence that diffusion MRI is a more sensitive technique than VA in the discrimination between MCI and AD. Results from this study also corroborate with another DKI study exploring diffusivity in neuroanatomical regions predominately composed of white matter in AD progression. While DKI provides additional information on the microstructural changes of white matter and gray matter during disease progression in the brain, whether DKI is superior to DTI requires further research. Diffusion MRI appears to be more advantageous when comparing cognitive function on a continuum like MMSE scores than segregated groups.
DegreeMaster of Medical Sciences
SubjectHippocampus (Brain) - Imaging
Diffusion tensor imaging
Dept/ProgramDiagnostic Radiology
Persistent Identifierhttp://hdl.handle.net/10722/193547

 

DC FieldValueLanguage
dc.contributor.authorAu, Chun-lam, Antony-
dc.contributor.author歐浚林-
dc.date.accessioned2014-01-13T23:10:37Z-
dc.date.available2014-01-13T23:10:37Z-
dc.date.issued2013-
dc.identifier.citationAu, C. A. [歐浚林]. (2013). Comparision between volumetric and DKI parametric analyses of hippocampus for correlations with MMSE scores in patients with Alzheimer's disease. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5091297-
dc.identifier.urihttp://hdl.handle.net/10722/193547-
dc.description.abstractVolumetric analysis (VA) in magnetic resonance imaging (MRI) has provided great comprehension of the neuroanatomical changes associated to normal cognition and progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD), the most common form of dementia. However, the use of VA has primarily focused in gray matter changes; the emergence of diffusion tensor imaging (DTI) has allowed a better understanding of the microstructural changes in both white and gray matters in MCI and AD patients, with numerous studies showing DTI to be more sensitive than VA in discriminating between MCI to AD. Diffusion kurtosis imaging (DKI), an extension of DTI, is speculated to be more sensitive in detecting changes due to differences in mathematical modeling, as it accounts for non-Gaussian diffusion in the brain. Studies using DKI suggested kurtosis parameters—axial, radial, and mean kurtoses—are able to provide further microstructural details in additional information to tensor and diffusion parameters, namely axial, radial, and mean diffusivities, and fractional anisotropy. In this study, DKI is compared to DTI and VA in an attempt to evaluate the sensitivities of each technique. DKI of all four cerebral lobes and VA of the hippocampus were performed in 30 patients, 18 diagnosed with AD and 12 with MCI. Mann-Whitney U test was performed to determine differences between MCI and AD, and correlations between diffusion parameters and hippocampal volume to mini-mental state examination (MMSE) scores as a biomarker of cognitive function were tested using Pearson’s R correlation test. MMSE scores were statistically different between sexes (p = 0.025) and between MCI and AD groups (p = 0.048), as well as positively correlated with age (p = 0.004). A marginal trend was observed in the hippocampal volume between MCI and AD (p = 0.077), and did not significantly correlate with MMSE. Several diffusivity and kurtosis parameters were significantly different between MCI and AD groups in the white and gray matters of the parietal and occipital lobes. Only tensor parameters had significant negative correlations with MMSE scores in within-group analyses of the two lobes. Correlational tests of white and gray matters of all four lobes to MMSE scores revealed more significant correlations between tensor parameters than kurtosis parameters. Findings from the present study provide further evidence that diffusion MRI is a more sensitive technique than VA in the discrimination between MCI and AD. Results from this study also corroborate with another DKI study exploring diffusivity in neuroanatomical regions predominately composed of white matter in AD progression. While DKI provides additional information on the microstructural changes of white matter and gray matter during disease progression in the brain, whether DKI is superior to DTI requires further research. Diffusion MRI appears to be more advantageous when comparing cognitive function on a continuum like MMSE scores than segregated groups.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.subject.lcshHippocampus (Brain) - Imaging-
dc.subject.lcshDiffusion tensor imaging-
dc.titleComparision between volumetric and DKI parametric analyses of hippocampus for correlations with MMSE scores in patients with Alzheimer's disease-
dc.typePG_Thesis-
dc.identifier.hkulb5091297-
dc.description.thesisnameMaster of Medical Sciences-
dc.description.thesislevelMaster-
dc.description.thesisdisciplineDiagnostic Radiology-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b5091297-
dc.date.hkucongregation2013-

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