Exploratory analysis of MRI imaging from the Cleveland ADRC Neuroimaging Core (NIC)
Poster No:
85
Submission Type:
Abstract Submission
Authors:
Jian Lin1, Ajay Nemani1, Ken Sakaie1, Wanyong Shin1, Mark Lowe1
Institutions:
1The Cleveland Clinic, Cleveland, OH
First Author:
Co-Author(s):
Introduction:
The NIH/NIA supports a network of 33 Alzheimer's Disease Research Centers (ADRC) to promote translation of research to improve patient care. The NIC of the CADRC has developed a panel of advanced MRI methods to explore their use in the context of AD and related dementias. We provide a preliminary exploratory analysis of this ongoing study.
Methods:
Subjects were recruited from the community for annual evaluation. All imaging was performed on a Siemens Prisma 3T MRI with a standard 32 channel head coil (Siemens Healthineers, Erlangen, Germany). Imaging included anatomical, resting state functional MRI (rsfMRI) and diffusion MRI (dMRI) based on the ADNI3 advanced protocol1. Additional scans including arterial spin labeling (ASL), multiecho gradient echo (MGE), myelin water imaging (MWI) using ViSTa2, dynamic contrast enhancement (DCE) and quantitative T1/T2 from magnetic resonance fingerprinting (MRF)3. MGE is used to generate susceptibility-weighted images (SWI) and quantitative susceptibility maps (QSM)4. dMRI is used to calculate both diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) maps. Further details about the imaging and purpose of each scan are provided in Table 1. Due to concerns related to patient comfort and compliance, scans are acquired in two separate sessions, allowing subjects to take a break between sessions. 62 subjects participated in session 1 (conventional T1 and T2-weighted, rsfMRI, dMRI, ASL) and 66 subjects in session 2 (quantitative T1/T2, QSM, MWI). Outcome measures consist of average values from within brain parcels defined by FreeSurfer5 that were co-registered to native image space.
We performed large scale, mass univariate exploratory analysis across the summary measures to elucidate systematic differences among subjects who were diagnosed by consensus as cognitively normal (CN), with mild cognitive impairment (MCI), or AD. One-way analysis of variance (ANOVA) was calculated for each FreeSurfer ROI and measure. Control for multiple comparison correction was implemented using Tukey's range test at the group level and Bonferroni's correction at the ROI and measure levels.
We performed large scale, mass univariate exploratory analysis across the summary measures to elucidate systematic differences among subjects who were diagnosed by consensus as cognitively normal (CN), with mild cognitive impairment (MCI), or AD. One-way analysis of variance (ANOVA) was calculated for each FreeSurfer ROI and measure. Control for multiple comparison correction was implemented using Tukey's range test at the group level and Bonferroni's correction at the ROI and measure levels.
·Table 1: Summary of MRI acquisitions
Results:
Session 1 analysis explored seven measures across diffusion (mean diffusivity (MD), transverse diffusivity (TD), longitudinal diffusivity (LD), fractional anisotropy (FA)), connectivity (fractional amplitude of low frequency fluctuations (fALFF) and excess positive global connectivity (GC)6), and perfusion (cerebral blood flow (CBF)) over 187 FreeSurfer ROIs. Of these, 301/3927 of comparisons survived correction for multiple comparisons. The 10 most significant group differences (p<0.05, corrected) are shown in table 2. Session 2 examined four quantitative measures, including quantitative T1 and T2 relaxation, tissue susceptibility, and myelin water fraction. None of the 2322 comparisons survived correction for multiple comparisons. Nonetheless, the 10 most significant group differences (p<0.05, uncorrected) are shown in table 3.
·Table 2: Ten most significant group differences across all session 1 summary measures (p<0.05, corrected)
Conclusions:
We present a preliminary exploratory analysis of the comprehensive imaging acquired by the CADRC-NIC. These results provide a context for further targeted analysis of qualitative and quantitative features in the context of progressive AD neurodegeneration. Group differences in quantitative summary measures were less pronounced than traditional qualitative measures. However, disease-related quantitative changes are more likely to be specific to specific regions and may be more amenable to targeted hypotheses.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Neuroinformatics and Data Sharing:
Databasing and Data Sharing 2
Keywords:
Degenerative Disease
Open Data
1|2Indicates the priority used for review
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2) Oh, S. Direct visualization of short transverse relaxation time component (ViSTa). Neuroimage 2013; 83:485-492
3) Ma, D. Development of high-resolution 3D MR fingerprinting for detection and characterization of epileptic lesions. J Magn Reson Imaging 2019; 49:1333-1346.
4) Li, L. Magnetic susceptibility quantification for arbitrarily shaped objects in inhomogeneous fields. Magn Reson Med 2001; 46:907-91.
5) Fischl, B. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 2002; 33.
6) Beall E. A new model-based intrinsic connectivity measure: global functional connectivity. Proc 23rd ISMRM. 2014; #3046