Abstract
Background: An anatomical covariance analysis (ACA) enables to elucidate inter-regional connections on a group basis, but little is known about the connections among white matter structures or among gray and white matter structures. Effect of including multiple magnetic resonance imaging (MRI) modalities into ACA framework in detecting white-to-white or gray-to-white connections is yet to be investigated. New method: Proposed extended anatomical covariance analysis (eACA), analyzes correlations among gray and white matter structures (multi-structural) in various types of imaging modalities (T1-weighted images, T2 maps obtained from dual-echo sequences, and diffusion tensor images (DTI)). To demonstrate the capability to detect a disruption of the correlation network affected by pathology, we applied the eACA to two groups of cognitively-normal elderly individuals, one with (PiB+) and one without (PiB-) amyloid deposition in their brains. Results: The volume of each anatomical structure was symmetric and functionally related structures formed a cluster. The pseudo-T2 value was highly homogeneous across the entire cortex in the PiB- group, while a number of physiological correlations were altered in the PiB + group. The DTI demonstrated unique correlation network among structures within the same phylogenetic portions of the brain that were altered in the PiB + group. Comparison with Existing Method: The proposed eACA expands the concept of existing ACA to the connections among the white matter structures. The extension to other image modalities expands the way in which connectivity may be detected. Conclusion: The eACA has potential to evaluate alterations of the anatomical network related to pathological processes.
| Original language | English (US) |
|---|---|
| Article number | e02074 |
| Journal | Heliyon |
| Volume | 5 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 1 2019 |
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Keywords
- Amyloid
- Anatomical covariance
- Correlation network
- Diffusion tensor imaging
- Magnetic resonance imaging
- Neuroscience
- Positron emission tomography
- T2 relaxation
ASJC Scopus subject areas
- General
Cite this
Extended multimodal whole-brain anatomical covariance analysis : detection of disrupted correlation networks related to amyloid deposition. / Ye, Chenfei; Albert, Marilyn; Brown, Timothy; Bilgel, M.; Hsu, Johnny; Ma, Ting; Caffo, B.; Miller, Michael I.; Mori, Susumu; Oishi, Kenichi.
In: Heliyon, Vol. 5, No. 7, e02074, 01.07.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Extended multimodal whole-brain anatomical covariance analysis
T2 - detection of disrupted correlation networks related to amyloid deposition
AU - Ye, Chenfei
AU - Albert, Marilyn
AU - Brown, Timothy
AU - Bilgel, M.
AU - Hsu, Johnny
AU - Ma, Ting
AU - Caffo, B.
AU - Miller, Michael I.
AU - Mori, Susumu
AU - Oishi, Kenichi
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Background: An anatomical covariance analysis (ACA) enables to elucidate inter-regional connections on a group basis, but little is known about the connections among white matter structures or among gray and white matter structures. Effect of including multiple magnetic resonance imaging (MRI) modalities into ACA framework in detecting white-to-white or gray-to-white connections is yet to be investigated. New method: Proposed extended anatomical covariance analysis (eACA), analyzes correlations among gray and white matter structures (multi-structural) in various types of imaging modalities (T1-weighted images, T2 maps obtained from dual-echo sequences, and diffusion tensor images (DTI)). To demonstrate the capability to detect a disruption of the correlation network affected by pathology, we applied the eACA to two groups of cognitively-normal elderly individuals, one with (PiB+) and one without (PiB-) amyloid deposition in their brains. Results: The volume of each anatomical structure was symmetric and functionally related structures formed a cluster. The pseudo-T2 value was highly homogeneous across the entire cortex in the PiB- group, while a number of physiological correlations were altered in the PiB + group. The DTI demonstrated unique correlation network among structures within the same phylogenetic portions of the brain that were altered in the PiB + group. Comparison with Existing Method: The proposed eACA expands the concept of existing ACA to the connections among the white matter structures. The extension to other image modalities expands the way in which connectivity may be detected. Conclusion: The eACA has potential to evaluate alterations of the anatomical network related to pathological processes.
AB - Background: An anatomical covariance analysis (ACA) enables to elucidate inter-regional connections on a group basis, but little is known about the connections among white matter structures or among gray and white matter structures. Effect of including multiple magnetic resonance imaging (MRI) modalities into ACA framework in detecting white-to-white or gray-to-white connections is yet to be investigated. New method: Proposed extended anatomical covariance analysis (eACA), analyzes correlations among gray and white matter structures (multi-structural) in various types of imaging modalities (T1-weighted images, T2 maps obtained from dual-echo sequences, and diffusion tensor images (DTI)). To demonstrate the capability to detect a disruption of the correlation network affected by pathology, we applied the eACA to two groups of cognitively-normal elderly individuals, one with (PiB+) and one without (PiB-) amyloid deposition in their brains. Results: The volume of each anatomical structure was symmetric and functionally related structures formed a cluster. The pseudo-T2 value was highly homogeneous across the entire cortex in the PiB- group, while a number of physiological correlations were altered in the PiB + group. The DTI demonstrated unique correlation network among structures within the same phylogenetic portions of the brain that were altered in the PiB + group. Comparison with Existing Method: The proposed eACA expands the concept of existing ACA to the connections among the white matter structures. The extension to other image modalities expands the way in which connectivity may be detected. Conclusion: The eACA has potential to evaluate alterations of the anatomical network related to pathological processes.
KW - Amyloid
KW - Anatomical covariance
KW - Correlation network
KW - Diffusion tensor imaging
KW - Magnetic resonance imaging
KW - Neuroscience
KW - Positron emission tomography
KW - T2 relaxation
UR - http://www.scopus.com/inward/record.url?scp=85069576482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069576482&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2019.e02074
DO - 10.1016/j.heliyon.2019.e02074
M3 - Article
C2 - 31372540
AN - SCOPUS:85069576482
VL - 5
JO - Heliyon
JF - Heliyon
SN - 2405-8440
IS - 7
M1 - e02074
ER -