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Classifying cognitive impairment based on the spatial heterogeneity of cerebral blood flow images
Author(s) -
Shirzadi Zahra,
Stefanovic Bojana,
Mutsaerts Henri J.M.M.,
Masellis Mario,
MacIntosh Bradley J.
Publication year - 2019
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.26650
Subject(s) - intraclass correlation , cerebral blood flow , temporal lobe , medicine , neuroimaging , population , alzheimer's disease , nuclear medicine , cardiology , logistic regression , psychology , audiology , neuroscience , disease , psychometrics , developmental psychology , environmental health , epilepsy
Background The spatial coefficient of variation (sCoV) of arterial spin‐labeled (ASL) MRI can index cerebral blood flow spatial heterogeneity. This metric reflects delayed blood delivery—seen as a hyperintense ASL signal juxtaposed by hypointense regions. Purpose To investigate the use of ASL‐sCoV in the classification of cognitively unimpaired (CU), mild cognitive impairment (MCI), and Alzheimer's disease (AD) cohorts. Study Type Prospective/cohort. Population Baseline ASL images from AD neuroimaging initiative dataset in three groups of CU, MCI, and AD ( N = 258). Field Strength/Sequence Pulsed ASL (PICORE QT2) images were acquired on 3 T Siemens systems (TE/TR = 12/3400 msec, TI1/2 = 700/1900 msec). Assessment ASL‐sCoV was calculated in temporal, parietal, occipital, and frontal lobes as well as whole gray matter. Statistical Tests The primary analysis used an analysis of covariance to investigate sCoV and cognitive group (CU, MCI, AD) associations. We also evaluated the repeatability of sCoV by calculating within‐subject agreement in a subgroup of CU participants with a repeat ASL. The secondary analyses assessed ventricular volume, amyloid burden, glucose uptake, ASL‐sCoV, and regional CBF as cognitive group classifiers using logistic regression models and receiver operating characteristic analyses. Results We found that global and temporal lobe sCoV differed between cognitive groups ( P = 0.006). Post‐hoc tests showed that temporal lobe sCoV was lower in CU than in MCI (Cohen's d = –0.36) or AD (Cohen's d = –1.36). We found that sCoV was moderately repeatable in CU (intersession intraclass correlation = 0.50; intrasession intraclass correlation = 0.88). Subsequent logistic regression analyses revealed that temporal lobe sCoV and amyloid uptake classified CU vs. MCI ( P < 0.01; accuracy = 78%). Temporal lobe sCoV, amyloid, and glucose uptake classified CU vs. AD ( P < 0.01; accuracy = 97%); glucose uptake significantly classified MCI vs. AD ( P < 0.01; accuracy = 85%). Data Conclusion We showed that ASL spatial heterogeneity can be used alongside AD neuroimaging markers to distinguish cognitive groups, in particular, cognitively unimpaired from cognitively impaired individuals. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:858–867.