Classifying cognitive impairment based on the spatial heterogeneity of cerebral blood flow images.

Abstract

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. To investigate the use of ASL-sCoV in the classification of cognitively unimpaired (CU), mild cognitive impairment (MCI), and Alzheimer's disease (AD) cohorts. Prospective/cohort. Baseline ASL images from AD neuroimaging initiative dataset in three groups of CU, MCI, and AD (N = 258). Pulsed ASL (PICORE QT2) images were acquired on 3 T Siemens systems (TE/TR = 12/3400 msec, TI1/2 = 700/1900 msec). ASL-sCoV was calculated in temporal, parietal, occipital, and frontal lobes as well as whole gray matter. 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. 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%). 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. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:858-867.