Total MRI Small Vessel Disease Burden Correlates with Cognitive Performance, Cortical Atrophy, and Network Measures in a Memory Clinic Population

Accurate reconstruction of the inner and outer cortical surfaces of the human cerebrum is a critical objective for a wide variety of neuroimaging analysis purposes, including visualization, morphometry, and brain mapping. The Anatomic Segmentation using Proximity (ASP) algorithm, previously developed by our group, provides a topology-preserving cortical surface deformation method that has been extensively used for the aforementioned purposes. However, constraints in the algorithm to ensure topology preservation occasionally produce incorrect thickness measurements due to a restriction in the range of allowable distances between the gray and white matter surfaces. This problem is particularly prominent in pediatric brain images with tightly folded gyri. This paper presents a novel method for improving the conventional ASP algorithm by making use of partial volume information through probabilistic classification in order to allow for topology preservation across a less restricted range of cortical thickness values. The new algorithm also corrects the classification of the insular cortex by masking out subcortical tissues. For 70 pediatric brains, validation experiments for the modified algorithm, Constrained Laplacian ASP (CLASP), were performed by three methods: (i) volume matching between surface-masked gray matter (GM) and conventional tissue-classified GM, (ii) surface matching between simulated and CLASP-extracted surfaces, and (iii) repeatability of the surface reconstruction among 16 MRI scans of the same subject. In the volume-based evaluation, the volume enclosed by the CLASP WM and GM surfaces matched the classified GM volume 13% more accurately than using conventional ASP. In the surface-based evaluation, using synthesized thick cortex, the average difference between simulated and extracted surfaces was 4.6 +/- 1.4 mm for conventional ASP and 0.5 +/- 0.4 mm for CLASP. In a repeatability study, CLASP produced a 30% lower RMS error for the GM surface and a 8% lower RMS error for the WM surface compared with ASP.

The Seoul Neuropsychological Screening Battery (SNSB) is one of the standardized neuropsychological test batteries widely used in Korea. However, it may be a bit too lengthy for patients with decreased attention span; and it does not provide the score of global cognitive function (GCF), which is useful for monitoring patients longitudinally. We sought to validate a dementia version of SNSB (SNSB-D) that was shorter than the original SNSB and contained only scorable tests with a GCF score of 300. We administered SNSB-D to patients with mild cognitive impairment (MCI) (n=43) and Alzheimer's disease (AD) (n=93), and normal controls (NC) (n=77). MCI and AD groups had GCF scores significantly different from NC group, and GCF scores were able to distinguish patients with Clinical Dementia Rating of 0.5 and 1. Test-retest reliability was high, with a correlation coefficient of 0.918 for AD, 0.999 for MCI, and 0.960 for NC. The GCF score significantly correlated with the Mini-Mental State Examination (MMSE). Through ROC-curve analysis, GCF scores were found to yield more accurate diagnoses than the MMSE. The SNSB-D is a valid, reliable tool for assessing the overall cognitive function, and can be used to monitor cognitive changes in patients with dementia.