Yuan-Yuan Qin1,2, Mu-Wei Li2, Shun Zhang1, Yan Zhang1, Ling-Yun Zhao1, Hao Lei3, Kenichi Oishi4, Wen-Zhen Zhu5. 1. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China. 2. The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 217D Traylor Building, 720 Rutland Avenue, Baltimore, MD, 21205, USA. 3. Wuhan Center for Magnetic Resonance, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan, China. 4. The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 217D Traylor Building, 720 Rutland Avenue, Baltimore, MD, 21205, USA. koishi@mri.jhu.edu. 5. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan, 430030, China. zhuwenzhen@hotmail.com.
Abstract
INTRODUCTION: Diffusion tensor imaging (DTI) has been applied to characterize the pathological features of Alzheimer's disease (AD) in a mouse model, although little is known about whether these features are structure specific. Voxel-based analysis (VBA) and atlas-based analysis (ABA) are good complementary tools for whole-brain DTI analysis. The purpose of this study was to identify the spatial localization of disease-related pathology in an AD mouse model. METHODS: VBA and ABA quantification were used for the whole-brain DTI analysis of nine APP/PS1 mice and wild-type (WT) controls. Multiple scalar measurements, including fractional anisotropy (FA), trace, axial diffusivity (DA), and radial diffusivity (DR), were investigated to capture the various types of pathology. The accuracy of the image transformation applied for VBA and ABA was evaluated by comparing manual and atlas-based structure delineation using kappa statistics. Following the MR examination, the brains of the animals were analyzed for microscopy. RESULTS: Extensive anatomical alterations were identified in APP/PS1 mice, in both the gray matter areas (neocortex, hippocampus, caudate putamen, thalamus, hypothalamus, claustrum, amygdala, and piriform cortex) and the white matter areas (corpus callosum/external capsule, cingulum, septum, internal capsule, fimbria, and optic tract), evidenced by an increase in FA or DA, or both, compared to WT mice (p < 0.05, corrected). The average kappa value between manual and atlas-based structure delineation was approximately 0.8, and there was no significant difference between APP/PS1 and WT mice (p > 0.05). The histopathological changes in the gray matter areas were confirmed by microscopy studies. DTI did, however, demonstrate significant changes in white matter areas, where the difference was not apparent by qualitative observation of a single-slice histological specimen. CONCLUSION: This study demonstrated the structure-specific nature of pathological changes in APP/PS1 mouse, and also showed the feasibility of applying whole-brain analysis methods to the investigation of an AD mouse model.
INTRODUCTION: Diffusion tensor imaging (DTI) has been applied to characterize the pathological features of Alzheimer's disease (AD) in a mouse model, although little is known about whether these features are structure specific. Voxel-based analysis (VBA) and atlas-based analysis (ABA) are good complementary tools for whole-brain DTI analysis. The purpose of this study was to identify the spatial localization of disease-related pathology in an ADmouse model. METHODS:VBA and ABA quantification were used for the whole-brain DTI analysis of nine APP/PS1mice and wild-type (WT) controls. Multiple scalar measurements, including fractional anisotropy (FA), trace, axial diffusivity (DA), and radial diffusivity (DR), were investigated to capture the various types of pathology. The accuracy of the image transformation applied for VBA and ABA was evaluated by comparing manual and atlas-based structure delineation using kappa statistics. Following the MR examination, the brains of the animals were analyzed for microscopy. RESULTS: Extensive anatomical alterations were identified in APP/PS1mice, in both the gray matter areas (neocortex, hippocampus, caudate putamen, thalamus, hypothalamus, claustrum, amygdala, and piriform cortex) and the white matter areas (corpus callosum/external capsule, cingulum, septum, internal capsule, fimbria, and optic tract), evidenced by an increase in FA or DA, or both, compared to WT mice (p < 0.05, corrected). The average kappa value between manual and atlas-based structure delineation was approximately 0.8, and there was no significant difference between APP/PS1 and WT mice (p > 0.05). The histopathological changes in the gray matter areas were confirmed by microscopy studies. DTI did, however, demonstrate significant changes in white matter areas, where the difference was not apparent by qualitative observation of a single-slice histological specimen. CONCLUSION: This study demonstrated the structure-specific nature of pathological changes in APP/PS1mouse, and also showed the feasibility of applying whole-brain analysis methods to the investigation of an ADmouse model.
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