scholarly journals Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Diffusion Tensor ◽  
Imaging Biomarkers ◽  
Normal Vector ◽  
Higher Sensitivity

Abstract Background: This study aims to investigate feasible gray matter microstructural biomarker with higher sensitivity for early Alzheimer’s disease (AD) detection. We propose diffusion tensor imaging (DTI) measure, ‘radiality’, for early AD biomarker. It is a dot product between cortical surface normal vector and primary diffusion direction, which reflects the fiber orientation within the cortical column. Methods: We gathered neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database: 78 cognitive normal, 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. Then, we evaluated cortical thickness (CTh), mean diffusivity (MD), amount of amyloid and tau accumulations using positron emission tomography (PET), which are conventional AD magnetic resonance (MR) imaging biomarkers. Radiality was projected on gray matter surface to compare and validate the changes along stages with other neuroimage biomarkers. Results: Results showed decreased radiality primarily in entorhinal, insula, frontal and temporal cortex as disease progresses onward. Especially, radiality could delineate the difference between cognitive normal and EMCI group while other biomarkers could not. We looked into the relationship between the radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed high association with conventional biomarkers. Additional ROI analysis exhibits dynamics of AD related changes as stages onward. Conclusion: Radiality in cortical gray matter showed AD specific changes and relevance with other conventional AD biomarkers with higher sensitivity. Besides, it could show group differences in early AD changes from EMCI which show advantage for early diagnosis than using conventional biomarkers. We provide the evidence of structure changes with cognitive impairment and suggest radiality as a sensitive biomarker for early AD.

scholarly journals Disruption of gray matter microstructure in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Diagnosis ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Imaging Biomarkers ◽  
Normal Vector ◽  
Higher Sensitivity

Abstract There have been several MR imaging biomarkers of Alzheimer’s disease (AD) for early diagnosis. Cortical mean diffusivity (MD) is one of them for the study of the cortical microstructural change in AD. However, several factors may overshadow the feasibility of MD as AD biomarker. Thus, current study investigated feasible gray matter microstructure biomarker with higher sensitivity for early AD detection. With the aim of facilitating the early detection of AD, the Alzheimer’s Disease Neuroimaging Initiative (ADNI) proposed two stages based on the memory performance: early mild cognitive impairment (EMCI) and late mild cognitive impairment (LMCI). We propose single shell DTI measure, ‘ radiality ’, for early AD biomarker. It is a dot product between cortical surface normal vector and primary diffusion direction, which presumably reflects the fiber orientation within the cortical column. Here, we gathered images from ADNI phase 2 & 3; 78 cognitive normal, 51 EMCI, 34 LMCI, and 39 AD patients. Then, we evaluated cortical thickness (CTh), MD, amount of amyloid and tau accumulations using PET, which are conventional AD biomarkers. Radiality was projected on gray matter surface to compare and validate the changes along other neuroimage biomarkers. Results showed decreased radiality primarily in entorhinal, insula, frontal and temporal cortex as disease progress onward. Especially, radiality could delineate the difference between cognitive normal and EMCI group while other biomarkers could not. We looked into the relationship between the radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed high association with conventional biomarkers. Additional ROI analysis exhibit dynamics of AD related changes as stages onward. In conclusion, radiality in cortical gray matter showed AD specific changes and relevance with other conventional AD biomarkers with higher sensitivity. Besides, it could show group differences in early AD changes from EMCI which show advantage for early diagnosis than using conventional biomarkers. We provide the evidence of structure changes with cognitive impairment and suggest radiality as a sensitive biomarker for early diagnose and progress monitor AD.

scholarly journals Disruption of gray matter microstructure in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Diagnosis ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Imaging Biomarkers ◽  
Normal Vector ◽  
Higher Sensitivity

Abstract There have been several MR imaging biomarkers of Alzheimer’s disease (AD) for early diagnosis. Cortical mean diffusivity (MD) is one of them for the study of the cortical microstructural change in AD. However, the feasibility of MD often remain in doubt as partial volume effects may overestimate the results. This study aims to investigate feasible gray matter microstructural biomarker with higher sensitivity for early AD detection. We propose diffusion tensor imaging (DTI) measure, ‘radiality’, for early AD biomarker. It is a dot product between cortical surface normal vector and primary diffusion direction, which reflects the fiber orientation within the cortical column. Here, we gathered neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database; 78 cognitive normal, 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. Then, we evaluated cortical thickness (CTh), MD, amount of amyloid and tau accumulations using positron emission tomography (PET), which are conventional AD biomarkers. Radiality was projected on gray matter surface to compare and validate the changes along other neuroimage biomarkers. Results showed decreased radiality primarily in entorhinal, insula, frontal and temporal cortex as disease progress onward. Especially, radiality could delineate the difference between cognitive normal and EMCI group while other biomarkers could not. We looked into the relationship between the radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed high association with conventional biomarkers. Additional ROI analysis exhibits dynamics of AD related changes as stages onward. In conclusion, radiality in cortical gray matter showed AD specific changes and relevance with other conventional AD biomarkers with higher sensitivity. Besides, it could show group differences in early AD changes from EMCI which show advantage for early diagnosis than using conventional biomarkers. We provide the evidence of structure changes with cognitive impairment and suggest radiality as a sensitive biomarker for early AD.

scholarly journals Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Diagnosis ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Imaging Biomarkers ◽  
Normal Vector ◽  
Higher Sensitivity

Abstract There have been several magnetic resonance (MR) imaging biomarkers of Alzheimer’s disease (AD) for early diagnosis. Cortical mean diffusivity (MD) is one of them for the study of the cortical microstructural change in AD. However, the feasibility of MD often remains in doubt as partial volume effects may overestimate the results. This study aims to investigate feasible gray matter microstructural biomarker with higher sensitivity for early AD detection. We propose diffusion tensor imaging (DTI) measure, ‘radiality’, for early AD biomarker. It is a dot product between cortical surface normal vector and primary diffusion direction, which reflects the fiber orientation within the cortical column. Here, we gathered neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database: 78 cognitive normal, 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. Then, we evaluated cortical thickness (CTh), MD, amount of amyloid and tau accumulations using positron emission tomography (PET), which are conventional AD biomarkers. Radiality was projected on gray matter surface to compare and validate the changes along other neuroimage biomarkers. Results showed decreased radiality primarily in entorhinal, insula, frontal and temporal cortex as disease progresses onward. Especially, radiality could delineate the difference between cognitive normal and EMCI group while other biomarkers could not. We looked into the relationship between the radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed high association with conventional biomarkers. Additional ROI analysis exhibits dynamics of AD related changes as stages onward. In conclusion, radiality in cortical gray matter showed AD specific changes and relevance with other conventional AD biomarkers with higher sensitivity. Besides, it could show group differences in early AD changes from EMCI which show advantage for early diagnosis than using conventional biomarkers. We provide the evidence of structure changes with cognitive impairment and suggest radiality as a sensitive biomarker for early AD.

scholarly journals Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong ◽  
Alzheimer's Disease Neuroimaging Initiative
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
High Sensitivity ◽  
Normal Vector

Abstract Background This study aimed to investigate feasible gray matter microstructural biomarkers with high sensitivity for early Alzheimer’s disease (AD) detection. We propose a diffusion tensor imaging (DTI) measure, “radiality”, as an early AD biomarker. It is the dot product of the normal vector of the cortical surface and primary diffusion direction, which reflects the fiber orientation within the cortical column. Methods We analyzed neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, including images from 78 cognitively normal (CN), 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. We then evaluated the cortical thickness (CTh), mean diffusivity (MD), which are conventional AD magnetic resonance imaging (MRI) biomarkers, and the amount of accumulated amyloid and tau using positron emission tomography (PET). Radiality was projected on the gray matter surface to compare and validate the changes with different stages alongside other neuroimage biomarkers.Results The results revealed decreased radiality primarily in the entorhinal, insula, frontal, and temporal cortex with further progression of disease. In particular, radiality could delineate the difference between the CN and EMCI groups, while the other biomarkers could not. We examined the relationship between radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed a high association with conventional biomarkers. Additional ROI analysis revealed the dynamics of AD-related changes as stages onward.Conclusion Radiality in cortical gray matter showed AD-specific changes and relevance with other conventional AD biomarkers with high sensitivity. Moreover, radiality could identify the group differences seen in EMCI, representative of changes in early AD, which supports its superiority in early diagnosis compared to that possible with conventional biomarkers. We provide evidence of structural changes with cognitive impairment and suggest radiality as a sensitive biomarker for identifying early AD.

scholarly journals Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation

2020 ◽  
Author(s):  
Peter Lee ◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
High Sensitivity ◽  
Normal Vector

Abstract Background: This study aimed to investigate feasible gray matter microstructural biomarkers with high sensitivity for early Alzheimer’s disease (AD) detection. We propose a diffusion tensor imaging (DTI) measure, “radiality”, as an early AD biomarker. It is the dot product of the normal vector of the cortical surface and primary diffusion direction, which reflects the fiber orientation within the cortical column. Methods: We analyzed neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, including images from 78 cognitively normal (CN), 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. We then evaluated the cortical thickness (CTh), mean diffusivity (MD), which are conventional AD magnetic resonance imaging (MRI) biomarkers, and the amount of accumulated amyloid and tau using positron emission tomography (PET). Radiality was projected on the gray matter surface to compare and validate the changes with different stages alongside other neuroimage biomarkers.Results: The results revealed decreased radiality primarily in the entorhinal, insula, frontal, and temporal cortex with further progression of disease. In particular, radiality could delineate the difference between the CN and EMCI groups, while the other biomarkers could not. We examined the relationship between radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed a high association with conventional biomarkers. Additional ROI analysis revealed the dynamics of AD-related changes as stages onward.Conclusion: Radiality in cortical gray matter showed AD-specific changes and relevance with other conventional AD biomarkers with high sensitivity. Moreover, radiality could identify the group differences seen in EMCI, representative of changes in early AD, which supports its superiority in early diagnosis compared to that possible with conventional biomarkers. We provide evidence of structural changes with cognitive impairment and suggest radiality as a sensitive biomarker for identifying early AD.

scholarly journals Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation

BMC Neurology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Peter Lee ◽  
◽  
Hang-Rai Kim ◽  
Yong Jeong
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Gray Matter ◽  
Fiber Orientation ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
High Sensitivity ◽  
Normal Vector

Abstract Background This study aimed to investigate feasible gray matter microstructural biomarkers with high sensitivity for early Alzheimer’s disease (AD) detection. We propose a diffusion tensor imaging (DTI) measure, “radiality”, as an early AD biomarker. It is the dot product of the normal vector of the cortical surface and primary diffusion direction, which reflects the fiber orientation within the cortical column. Methods We analyzed neuroimages from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database, including images from 78 cognitively normal (CN), 50 early mild cognitive impairment (EMCI), 34 late mild cognitive impairment (LMCI), and 39 AD patients. We then evaluated the cortical thickness (CTh), mean diffusivity (MD), which are conventional AD magnetic resonance imaging (MRI) biomarkers, and the amount of accumulated amyloid and tau using positron emission tomography (PET). Radiality was projected on the gray matter surface to compare and validate the changes with different stages alongside other neuroimage biomarkers. Results The results revealed decreased radiality primarily in the entorhinal, insula, frontal, and temporal cortex with further progression of disease. In particular, radiality could delineate the difference between the CN and EMCI groups, while the other biomarkers could not. We examined the relationship between radiality and other biomarkers to validate its pathological evidence in AD. Overall, radiality showed a high association with conventional biomarkers. Additional ROI analysis revealed the dynamics of AD-related changes as stages onward. Conclusion Radiality in cortical gray matter showed AD-specific changes and relevance with other conventional AD biomarkers with high sensitivity. Moreover, radiality could identify the group differences seen in EMCI, representative of changes in early AD, which supports its superiority in early diagnosis compared to that possible with conventional biomarkers. We provide evidence of structural changes with cognitive impairment and suggest radiality as a sensitive biomarker for identifying early AD.

Using Fractional Anisotropy Imaging to Detect Mild Cognitive Impairment and Alzheimer’s Disease among Mexican Americans and Non-Hispanic Whites: A HABLE Study

2021 ◽  
pp. 1-8
Author(s):  
James R. Hall ◽  
Leigh A. Johnson ◽  
Fan Zhang ◽  
Melissa Petersen ◽  
Arthur W. Toga ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Fractional Anisotropy ◽  
Mexican Americans ◽  
Diffusion Tensor ◽  
Characteristic Curve ◽  
Aging Brain ◽  
Community Based

<b><i>Introduction:</i></b> Alzheimer’s disease (AD) is the most frequently occurring neurodegenerative disease; however, little work has been conducted examining biomarkers of AD among Mexican Americans. Here, we examined diffusion tensor MRI marker profiles for detecting mild cognitive impairment (MCI) and dementia in a multi-ethnic cohort. <b><i>Methods:</i></b> 3T MRI measures of fractional anisotropy (FA) were examined among 1,636 participants of the ongoing community-based Health &amp; Aging Brain among Latino Elders (HABLE) community-based study (Mexican American <i>n</i> = 851; non-Hispanic white <i>n</i> = 785). <b><i>Results:</i></b> The FA profile was highly accurate in detecting both MCI (area under the receiver operating characteristic curve [AUC] = 0.99) and dementia (AUC = 0.98). However, the FA profile varied significantly not only between diagnostic groups but also between Mexican Americans and non-Hispanic whites. <b><i>Conclusion:</i></b> Findings suggest that diffusion tensor imaging markers may have a role in the neurodiagnostic process for detecting MCI and dementia among diverse populations.

scholarly journals Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease

2017 ◽  
Author(s):  
J. Rasero ◽  
C. Alonso-Montes ◽  
I. Diez ◽  
L. Olabarrieta-Landa ◽  
L. Remaki ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Disease Severity ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Stage Ii ◽  
Group Level ◽  
The Brain

AbstractAlzheimer’s disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer's Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1=36, healthy control subjects, Control), G2 (N2=36, early mild cognitive impairment, EMCI), G3 (N3=36, late mild cognitive impairment, LMCI) and G4 (N4=36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I 3(Control vs EMCI), stage II (Control vs LMCI) and stage III (Control vs AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were three-fold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks,including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas possibly involved in such a degenerative process. Further studies applying the same strategy to longitudinal data are needed to fully confirm this scenario.

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