Methods

Introduction

The accurate detection and diagnose of

Alzheimer’s disease (AD) is quite challenge. It

is generally accepted that sensitive

biomarkers derived from in vivo neuroimaging

data could improve the early identification of

AD. In this study, we employed a

morphometric analysis in the hippocampus

and lateral ventricle. We applied our brain

surface morphometry pipeline to analyze brain

MRIs obtained from the well-characterized

Arizona APOE cohort of presymptomatic

individuals. We hypothesized that our surface

multivariate statistics may identify subtle

shape difference on both hippocampus and

lateral ventricle. The results showed

significant regional differences between stable

and declining participants. Our results may

help improve the sensitivity and accuracy of

hippocampal and ventricular morphometry for

preclinical AD research.

Cognitive Decline Affects The Morphometric Properties Of Hippocampus And Lateral Ventricle

Wen Zhang1, Jie Shi1, Cynthia Stonnington2, Robert J. Bauer III3, Boris A. Gutman4, Kewei Chen3, Paul M. Thompson4, Eric M. Reiman3, Richard J. Caselli5, Yalin Wang1

1School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA. 2Dept. of Psychiatry and Psychology, Mayo Clinic Arizona, Scottsdale,AZ. 3Banner Alzheimer’s Institute, Phoenix, AZ, USA. 4Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Marina del Rey, CA.5Department of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, USA .

wzhan139@asu.edu

References1. M. Jenkinson, et al., “FSL,” Neuroimage, vol. 62, no. 2, pp. 782–790, Aug

2012.

2. Zhang W, et al., "Morphometric Analysis of Hippocampus and Lateral Ventricle

Reveals Regional Difference Between Cognitively Stable and Declining

Persons", ISBI. 2016

3. Wang, Y. et al, 2011. Surface-based TBM Boosts Power to Detect Disease

Effects on the Brain: An N=804 ADNI Study. NeuroImage, 56(4):1993-2010.

4. Reiman, E.M., Linking brain imaging and genomics in the study of Alzheimer's

disease and aging. Ann NY Acad Sci, 2007. 1097: p. 94-113.

Methods

1. Segmentation of Hippocampus and Lateral Ventricle. The hippocampus was

segmented from T1 images by using FSL software package [1]. For ventricular

segmentation, in this research, we used a novel pipeline that computed a group-wised

ventricular template and used it to accurately segment continuous ventricular structures [2].

2. Surface Multivariate Tensor-based Morphometry. Based on segmented binary

volume masks, we extracted hippocampal and ventricular boundaries with a topology

preserving level-set method and constructed triangular surface meshes with marching

cubes algorithm. Later, the surfaces were further smoothed using a two step mesh

smoothing method, ”progressive meshes'' and Loop subdivision, which has been proved to

be feature-preserving meanwhile effectively reduce the noise and partial volume effect.

Figure 2 illustrates the reconstructed surface samples of our method.

3. Group Difference Study. The Hotellling's T2 test was performed to evaluate the

morphometric variations of hippocampal and ventricular surfaces between declining

controls and stable control group on each vertex [3].

DiscussionIn this study, we identified that strong difference on

the left sides of both hippocampus and lateral

ventricle. It may suggest that the cognitive decline

related to brain atrophy started from left side and

subsequently extend to the right. Overall, the

experimental results showed a strong indication that

hippocampal and ventricular morphometry may be

useful as imaging biomarkers to predict impending

cognitive decline in asymptomatic, cognitively

unimpaired subjects.

Experiments

Figure 2. Illustration of the

reconstruction samples of

this experiment. We

overlaid the segmented

ventricular and hippocam-

pal volume masks on the

original T1 image and

showed the surface

reconstruction meshes

based on the volume

masks. L stands for the left

side and R means the right

side.

We computed the surface morphometric difference of hippocampus and lateral ventricle

between stable and declining individuals. 18 subjects with presymptomatic imaging studies

developed to aMCI or AD on average of 2 years, after their last imaging visits. 35 subjects

matched for sex and age who remained cognitively unimpaired for at least 4 years were

selected as the comparison, stable group. Their baseline high-resolution T1 MRI scans were

used in this study [4]. We used the Mahalanobis distance to measure the difference between

the mean morphometry feature vectors between these two groups. P-map computed by

Hotelling's T2 test were shown in Figure 3. The statistical results were corrected for multiple

comparisons with permutation test. With p<0.05 as the threshold, the global significance

levels on hippocampus and lateral ventricle reached the significant level on both sides

(hippocampus, left p=0.0135, right p=0.0367; ventricle, left p=0.0131, right p=0.0461).

Figure 3. Statistical Result of Group Difference on

Hippocampus and Lateral Ventricle. The middle

color bar indicated the range of p values. L stands

for the left side while R means the right side.

AcknowledgementThis research was supported by NIH (R21AG043760,

R21AG049216, R01AG031581, P30AG19610, U54 EB020403), NSF

(DMS-1413417 and IIS-1421165).

Figure 1. Ventricle Segmentation Pipeline.

The order of processing is followed by A-B-

C-D.