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Research article
Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation
Yong Jeong
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5907-3787
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Neurology.
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.
Keywords
Alzheimer’s disease, Early diagnosis, Diffusion tensor imaging, Microstructure, Biomarkers
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CURRENT STATUS: Published
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Posted 22 Sep, 2020
No comments provided
Editorial decision: Minor revision
On 11 Sep, 2020
Editor assigned
On 13 Jul, 2020
Submission checks complete
On 12 Jul, 2020
Editor invited
On 12 Jul, 2020
No comments provided
Editorial decision: Minor revision
On 02 Jul, 2020
Review #1 received
Received 02 Jul, 2020
Reviewers invited
Invitations sent on 10 Jun, 2020
Reviewer #1 agreed
On 10 Jun, 2020
Editor assigned
On 09 Jun, 2020
Submission checks complete
On 08 Jun, 2020
Editor invited
On 08 Jun, 2020
No comments provided
Review #2 received
Received 26 May, 2020
Editorial decision: Minor revision
On 26 May, 2020
Review #1 received
Received 21 May, 2020
Reviewer #1 agreed
On 26 Apr, 2020
Reviewer #2 agreed
On 26 Apr, 2020
Reviewers invited
Invitations sent on 23 Apr, 2020
Editor assigned
On 16 Apr, 2020
Submission checks complete
On 15 Apr, 2020
Editor invited
On 15 Apr, 2020
No comments provided
Editorial decision: Revise before sending to peer reviewers
On 09 Apr, 2020
Editor assigned
On 31 Mar, 2020
Submission checks complete
On 30 Mar, 2020
Editor invited
On 30 Mar, 2020
No comments provided
Editorial decision: Revise before sending to peer reviewers
On 17 Mar, 2020
Editor assigned
On 27 Feb, 2020
Submission checks complete
On 26 Feb, 2020
Editor invited
On 26 Feb, 2020
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This preprint is under consideration at BMC Neurology. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation
Yong Jeong
Corresponding Author
ORCiD: https://orcid.org/0000-0002-5907-3787
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 6
Posted 22 Sep, 2020
No comments provided
Editorial decision: Minor revision
On 11 Sep, 2020
Editor assigned
On 13 Jul, 2020
Submission checks complete
On 12 Jul, 2020
Editor invited
On 12 Jul, 2020
No comments provided
Editorial decision: Minor revision
On 02 Jul, 2020
Review #1 received
Received 02 Jul, 2020
Reviewers invited
Invitations sent on 10 Jun, 2020
Reviewer #1 agreed
On 10 Jun, 2020
Editor assigned
On 09 Jun, 2020
Submission checks complete
On 08 Jun, 2020
Editor invited
On 08 Jun, 2020
No comments provided
Review #2 received
Received 26 May, 2020
Editorial decision: Minor revision
On 26 May, 2020
Review #1 received
Received 21 May, 2020
Reviewer #1 agreed
On 26 Apr, 2020
Reviewer #2 agreed
On 26 Apr, 2020
Reviewers invited
Invitations sent on 23 Apr, 2020
Editor assigned
On 16 Apr, 2020
Submission checks complete
On 15 Apr, 2020
Editor invited
On 15 Apr, 2020
No comments provided
Editorial decision: Revise before sending to peer reviewers
On 09 Apr, 2020
Editor assigned
On 31 Mar, 2020
Submission checks complete
On 30 Mar, 2020
Editor invited
On 30 Mar, 2020
No comments provided
Editorial decision: Revise before sending to peer reviewers
On 17 Mar, 2020
Editor assigned
On 27 Feb, 2020
Submission checks complete
On 26 Feb, 2020
Editor invited
On 26 Feb, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at BMC Neurology.
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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6