Studying ventricular abnormalities in mild cognitive impairment with hyperbolic Ricci flow and tensor-based morphometry

• Published in: NeuroImage (Orlando, Fla.) Vol. 104; pp. 1 - 20
• Main Authors: Shi, Jie, Stonnington, Cynthia M., Thompson, Paul M., Chen, Kewei, Gutman, Boris, Reschke, Cole, Baxter, Leslie C., Reiman, Eric M., Caselli, Richard J., Wang, Yalin
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.2015; Elsevier Limited
• Subjects: Aged; Aged, 80 and over; Aging; Algorithms; Alzheimer Disease - pathology; Alzheimer Disease - psychology; Alzheimer's disease; Bioengineering; Biomarkers; Brain research; Cerebral Ventricles - diagnostic imaging; Cerebral Ventricles - pathology; Cognitive ability; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - pathology; Cognitive Dysfunction - psychology; Diffusion Tensor Imaging; Female; Fluorodeoxyglucose F18; Humans; Hyperbolic Ricci flow; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Medical imaging; Medical research; Mild cognitive impairment; Models, Neurological; Morphology; Neuropsychological Tests; Pharmaceutical industry; Positron-Emission Tomography; Radiopharmaceuticals; Software; Tensor-based morphometry; Tensor-based morphometry; Mild cognitive impairment; Alzheimer's disease; Hyperbolic Ricci flow
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2014.09.062

Mild Cognitive Impairment (MCI) is a transitional stage between normal aging and dementia and people with MCI are at high risk of progression to dementia. MCI is attracting increasing attention, as it offers an opportunity to target the disease process during an early symptomatic stage. Structural magnetic resonance imaging (MRI) measures have been the mainstay of Alzheimer's disease (AD) imaging research, however, ventricular morphometry analysis remains challenging because of its complicated topological structure. Here we describe a novel ventricular morphometry system based on the hyperbolic Ricci flow method and tensor-based morphometry (TBM) statistics. Unlike prior ventricular surface parameterization methods, hyperbolic conformal parameterization is angle-preserving and does not have any singularities. Our system generates a one-to-one diffeomorphic mapping between ventricular surfaces with consistent boundary matching conditions. The TBM statistics encode a great deal of surface deformation information that could be inaccessible or overlooked by other methods. We applied our system to the baseline MRI scans of a set of MCI subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI: 71 MCI converters vs. 62 MCI stable). Although the combined ventricular area and volume features did not differ between the two groups, our fine-grained surface analysis revealed significant differences in the ventricular regions close to the temporal lobe and posterior cingulate, structures that are affected early in AD. Significant correlations were also detected between ventricular morphometry, neuropsychological measures, and a previously described imaging index based on fluorodeoxyglucose positron emission tomography (FDG-PET) scans. This novel ventricular morphometry method may offer a new and more sensitive approach to study preclinical and early symptomatic stage AD. •A global conformal parameterization without singularities for branching surfaces•A geodesic curve lifting method for consistent boundary conditions across subjects•Surface TBM shows better group difference between MCI converter and stable groups.•Ventricular morphology changes are consistent with other AD progression measurements.•An automated, robust and generalizable ventricular morphometry system