Beta-amyloid Plaque Microstructure by High-resolution QSM and dMRI
Poster No:
1301
Submission Type:
Abstract Submission
Authors:
Jie Chen1, Rui Hu1, Hongbo Wu1, Saira Tabassam1, Nian Wang2,3,1
Institutions:
1UT southwestern medical center, Dallas, TX, 2Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, 3Advanced Imaging Research Center,The University of Texas Southwestern Medical Center, Dallas, TX
First Author:
Co-Author(s):
Nian Wang
Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center|Advanced Imaging Research Center,The University of Texas Southwestern Medical Center|UT southwestern medical center
Dallas, TX|Dallas, TX|Dallas, TX
Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center|Advanced Imaging Research Center,The University of Texas Southwestern Medical Center|UT southwestern medical center
Dallas, TX|Dallas, TX|Dallas, TX
Introduction:
Alzheimer's disease (AD) is an age-associated neurodegenerative disease that is reaching epidemic proportions as a result of the aging of the world's population. Although the cause of AD is not fully understood, clinical and neuropathological studies have hypothesized that the formation of beta-amyloid (Aβ) plaques and neurofibrillary tangles (NFTs) are crucial to the pathogenesis of AD. Aβ accumulation is proposed to be an early toxic event in the pathogenesis of AD1. While the detailed molecular mechanisms and the spatial-temporal dynamics leading to neurodegeneration are still under investigation, the alteration of the pathological forms of Aβ remains the core biological hallmark of AD. It has been demonstrated that Aβ is diamagnetic detected by QSM. However, probing the microstructure of the individual plaques is still challenging due to their small size. To address the issue, we demonstrated that high-resolution QSM can detect the individual plaques through the whole cortex area; the tissue microstructure was then quantified by high-resolution dMRI.
Methods:
Imaging Experiments:
Animal experiments followed Institutional Animal Care and Use Committee guidelines. Five 5xFAD and five wild-type mice were used. MR images were acquired at 9.4T on a Bruker BioSpec system using 3D ME-GRE and 2D multi-shot EPI sequences. MGRE parameters: matrix = 440 × 342 × 206, FOV = 15.4 × 11.97 × 7.21 mm, resolution = 35 µm, flip angle = 50°, TE1/deltaTE/echoes = 3.40/3.85/10, TR = 150 ms, bandwidth = 200 kHz. EPI parameters: matrix = 308 × 240 × 144, FOV = 15.4 × 12.0 × 7.2 mm, resolution = 50 µm, TR = 150 ms, bandwidth = 200 kHz. The huaman dMRI was also applied at 125 µm isotropic resolution and MGRE at 50 µm isotropic resolution.
Susceptibility Mapping, dMRI Metrics and tractography: ME-GRE phases are unwrapped using a Laplacian-based method, followed by V-SHARP3 filtering and iLSQR QSM inversion. Diffusion MRI metrics were calculated with MRTrix3. Detection maps are generated from QSM and DWI (Fig. 1). Using these detection maps and DWI cortex labels, plaque/non-plaque maps, their ratio, and statistical maps for DTI are derived (Fig. 2).
Animal experiments followed Institutional Animal Care and Use Committee guidelines. Five 5xFAD and five wild-type mice were used. MR images were acquired at 9.4T on a Bruker BioSpec system using 3D ME-GRE and 2D multi-shot EPI sequences. MGRE parameters: matrix = 440 × 342 × 206, FOV = 15.4 × 11.97 × 7.21 mm, resolution = 35 µm, flip angle = 50°, TE1/deltaTE/echoes = 3.40/3.85/10, TR = 150 ms, bandwidth = 200 kHz. EPI parameters: matrix = 308 × 240 × 144, FOV = 15.4 × 12.0 × 7.2 mm, resolution = 50 µm, TR = 150 ms, bandwidth = 200 kHz. The huaman dMRI was also applied at 125 µm isotropic resolution and MGRE at 50 µm isotropic resolution.
Susceptibility Mapping, dMRI Metrics and tractography: ME-GRE phases are unwrapped using a Laplacian-based method, followed by V-SHARP3 filtering and iLSQR QSM inversion. Diffusion MRI metrics were calculated with MRTrix3. Detection maps are generated from QSM and DWI (Fig. 1). Using these detection maps and DWI cortex labels, plaque/non-plaque maps, their ratio, and statistical maps for DTI are derived (Fig. 2).
·(a) Beta-Amyloid plaque detection in QSM for human and mouse models. (b) DWI preprocessing and transformation of detection map in QSM into DWI.
Results:
Visual inspection reveals in both mouse and human models that AD, RD, and MD values are lower in the plaque region compared to the non-plaque region, while FA values are higher in the plaque region, Figure 2 (a). Furthermore, one-way ANOVA statistical tests for most ROIs between plaque and non-plaque regions demonstrate significant differences with p<0.001. Statistical tests indicate substantial differences in AD and FA between plaque and non-plaque regions across the entire cortex in the five 5xFAD mice. However, RD and MD did not exhibit statistically significant differences. AD, RD, and MD reveal statistically significant differences in the human model, but FA does not. Consistent results were demonstrated in human AD samples (Figure 2 (b)).
·The distribution of beta-amyloid plaques in the cortical of 5xFAD and human.
Conclusions:
In this study, we demonstrated that high-resolution QSM can detect individual beta-amyloid plaques across the entire brain in both mouse and human AD specimens. The dramatic differences in tissue microstructure between plaque and non-plaque regions highlight the potential of high-resolution MRI for advancing Alzheimer's disease research.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Diffusion MRI Modeling and Analysis 1
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Computational Neuroscience
Cortex
MRI
1|2Indicates the priority used for review
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