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Network Failure Quotient (NFQ) performance in ADNI‐2 and ADNI‐3: Robustness across scanner and protocol changes
Author(s) -
Gunter Jeffrey L.,
Weigand Stephen D.,
Wiste Heather J.,
Therneau Terry M.,
Botha Hugo,
Jack Clifford R.,
Jones David T.
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.043336
Subject(s) - computer science , protocol (science) , artificial intelligence , medicine , pathology , alternative medicine
Background The Network Failure Quotient (NFQ) metric summarizes functional MRI network integrity. We wanted to investigate the stability of the NFQ results across time, hardware, software and protocol changes during the last decade in ADNI Resting State (RS‐) fMRI. Method In ADNI‐2 (2009‐2016) RS‐fMRI was acquired on Philips scanners. In ADNI‐3 (2017‐present) RS‐fMRI is acquired on GE, Philips, and Siemens systems with “Basic” and “Advanced” variants based on the availability of simultaneous multi‐slice (SMS, multi‐band) imaging. (Table 1.) Resting state images were preprocessed by performing slice timing correction, trimming volumes from the first 10 seconds of acquired data, despiking and within‐series alignment. Simultaneous bandpass and regression was performed using spatial registration parameters and their first temporal derivatives, mean WM signal, mean CSF signal and global signal. Dual regression via GIFT was applied creating regional time courses. The NFQ is calculated as NFQ=(pDMN_to_vDMN + pDMN_to_adDMN) / (pDMN +vDMN) where pDMN_to_vDMN and pDMN_to_adDMN are correlations between time courses in the posterior DMN, ventral DMN and anterior‐dorsal DMN. pDMN and vDMN are the within‐region correlations. NFQ values from 1447 scans of 739 individual study participants (Table 1) were analyzed using linear mixed effects models to account for age, clinical diagnosis, vendor, and time trends. Result Box plots of NFQ values by diagnosis within ADNI‐phase and protocol are shown in Figure 2 and suggest important differences among clinical diagnoses and between ADNI‐2 and ADNI‐3. The mixed model analysis indicates that a 10‐year increase in age is associated with a 0.05±0.01 (mean±SD) increase in NFQ; individuals with MCI average roughly 0.05±0.01 higher than unimpaired and individuals with dementia average 0.14±0.02 higher. Differences by vendor for ADNI‐2 and ADNI‐3 are summarized in Figures 2 and 3 with effect sizes on par with these clinical factors. Mean NFQ for Phillips ADNI‐2 were highest (0.54±0.02); somewhat lower were Philips ADNI‐3 (0.51±0.02) and Siemens ADNI‐3 advanced (0.49±0.03); Siemens ADNI‐3 basic (0.40±0.02) and GE ADNI‐3 were the lowest (0.38±0.02). Conclusion NFQ values consistently increase with impairment. Vendor‐specific differences are observed and vendor changes over the life of a study introduce variability on the scale of disease‐related changes in NFQ.