Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.
10.3348/kjr.2017.18.6.983
- Author:
Ji Eun PARK
1
;
Bumwoo PARK
;
Sang Joon KIM
;
Ho Sung KIM
;
Choong Gon CHOI
;
Seung Chai JUNG
;
Joo Young OH
;
Jae Hong LEE
;
Jee Hoon ROH
;
Woo Hyun SHIM
Author Information
1. Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505, Korea. sjkimjb@amc.seoul.kr
- Publication Type:Original Article
- Keywords:
Magnetic resonance imaging;
Brain;
Alzheimer's disease;
Resting-state functional MRI;
Biomarker
- MeSH:
Alzheimer Disease*;
Biomarkers;
Brain;
Cerebrum;
Humans;
Magnetic Resonance Imaging;
Neuroimaging*;
Parietal Lobe;
Retrospective Studies;
Support Vector Machine;
Temporal Lobe
- From:Korean Journal of Radiology
2017;18(6):983-991
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVE: To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. MATERIALS AND METHODS: Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. RESULTS: Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal (p < 0.001) and supramarginal gyrus (p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). CONCLUSION: Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.
