RT Journal Article
T1 Complexity Analysis of Cortical Surface Detects Changes in Future Alzheimer's Disease Converters
A1 Ruiz de Miras, Juan
A1 Costumero, Victor
A1 Belloch, Vicente
A1 Escudero, Joaquin
A1 Avila, Cesar
A1 Sepulcre, Jorge
K1 Alzheimer's disease
K1 mild cognitive impairment
K1 spherical harmonics
K1 fractal dimension
K1 thickness
K1 gyrification index
K1 Fractal dimension analysis
K1 Mild cognitive impairment
K1 Mini-mental-state
K1 Thickness analysis
K1 Cerebral-cortex
K1 White-matter
K1 Accurate
K1 Segmentation
K1 Algorithm
K1 Diagnosis
AB Alzheimer's disease (AD) is a neurological disorder that creates neurodegenerative changes at several structural and functional levels in human brain tissue. The fractal dimension (FD) is a quantitative parameter that characterizes the morphometric variability of the human brain. In this study, we investigate spherical harmonic-based FD (SHFD), thickness, and local gyrification index (LGI) to assess whether they identify cortical surface abnormalities toward the conversion to AD. We study 33 AD patients, 122 mild cognitive impairment (MCI) patients (50 MCI converters and 29 MCI nonconverters), and 32 healthy controls (HC). SHFD, thickness, and LGI methodology allowed us to perform not only global level but also local level assessments in each cortical surface vertex. First, we found that global SHFD decreased in AD and future MCI converters compared to HC, and in MCI converters compared to MCI nonconverters. Second, we found that local white matter SHFD was reduced in AD compared to HC and MCI mainly in medial temporal lobe. Third, local white-matter SHFD was significantly reduced in MCI converters compared to MCI nonconverters in distributed areas, including the medial frontal lobe. Thickness and LGI metrics presented a reduction in AD compared to HC. Thickness was significantly reduced in MCI converters compared to healthy controls in entorhinal cortex and lateral temporal. In summary, SHFD was the only surface measure showing differences between MCI individuals that will convert or remain stable in the next 4 years. We suggest that SHFD may be an optimal complement to thickness loss analysis in monitoring longitudinal changes in preclinical and clinical stages of AD. (C) 2017 Wiley Periodicals, Inc.
PB Wiley
SN 1065-9471
YR 2017
FD 2017-12-01
LK http://hdl.handle.net/10668/18609
UL http://hdl.handle.net/10668/18609
LA en
DS RISalud
RD Apr 9, 2025