MRI markers for mild cognitive impairment: comparisons between white matter integrity and gray matter volume measurements

Abstract

The aim of the study was to evaluate the value of assessing white matter integrity using diffusion tensor imaging (DTI) for classification of mild cognitive impairment (MCI) and prediction of cognitive impairments in comparison to brain atrophy measurements using structural MRI. Fifty-one patients with MCI and 66 cognitive normal controls (CN) underwent DTI and T1-weighted structural MRI. DTI measures included fractional anisotropy (FA) and radial diffusivity (DR) from 20 predetermined regions-of-interest (ROIs) in the commissural, limbic and association tracts, which are thought to be involved in Alzheimer's disease; measures of regional gray matter (GM) volume included 21 ROIs in medial temporal lobe, parietal cortex, and subcortical regions. Significant group differences between MCI and CN were detected by each MRI modality: In particular, reduced FA was found in splenium, left isthmus cingulum and fornix; increased DR was found in splenium, left isthmus cingulum and bilateral uncinate fasciculi; reduced GM volume was found in bilateral hippocampi, left entorhinal cortex, right amygdala and bilateral thalamus; and thinner cortex was found in the left entorhinal cortex. Group classifications based on FA or DR was significant and better than classifications based on GM volume. Using either DR or FA together with GM volume improved classification accuracy. Furthermore, all three measures, FA, DR and GM volume were similarly accurate in predicting cognitive performance in MCI patients. Taken together, the results imply that DTI measures are as accurate as measures of GM volume in detecting brain alterations that are associated with cognitive impairment. Furthermore, a combination of DTI and structural MRI measurements improves classification accuracy.

Figure 1. GM and WM parcellations.

A. Automated parcellation of 21 cortical and subcortical ROIs for GM measurement, performed by Freesurfer software. B. Automated parcellation of 20 deep WM ROIs for DTI measurement, performed by SPM8.

Figure 2. Mean differences of the DTI and GM measures between MCI and control.

A. Mean differences and standard errors of regional DTI and GM measures, expressed as Z-scores, between MCI patients and controls for each ROI. Abbreviations:CC  =  corpus callosum; Post. CG  =  posterior cingulum; Isth. CG  =  isthmus cingulum; FX-ST  =  fornix (cres) and stria terminalis; IFO  =  inferior fronto-occipital fasciculus; SLF  =  superior longitudinal fasciculus; ILF  =  inferior longitudinal fasciculus. B. Mean differences and standard errors of regional DTI and MRI measures between aMCI, naMCI group and controls for each ROI. DTI and GM measures in ROIs with significant heterogeneities between aMCI and naMCI groups were labeled as “#”.

Figure 3. The correlations between DTI and GM volumes in MCI patients.

The p value maps of the Pearson's correlation between DTI values and GM volumes. The green and warmer colors indicate significant correlations.

Figure 4. Classification accuracies based on DTI and GM volume measures.

Receiver operator characteristic curves of classifications of MCI and control subjects based on DTI and GM volume measures used separately or together.

Figure 5. Accuracies of predicting cognitive scores based on DTI and GM volume measures.

Distribution of root mean square errors in predicting MMSE and CVLT based on FA, DR or GM volume measures.