Voxel-based morphometry to discriminate early Alzheimer's disease from controls

Hirata, Yoko; Matsuda, Hiroshi; Nemoto, Kiyotaka; Ohnishi, Takashi; Hirao, Kentaro; Yamashita, Fumio; Asada, Takashi; Iwabuchi, Satoshi; Samejima, Hisanori

doi:10.1016/j.neulet.2005.03.038

Cited by 311 publications

(269 citation statements)

References 18 publications

Supporting

Mentioning

250

Contrasting

Unclassified

Order By: Relevance

“…The classification process was performed based on Disease State Index methodology. Hirata et al [41] developed software based on the voxel-based specific region analysis for AD, which can automatically analyse 3D MRI data as a series of segmentation, anatomical standardisation and smoothing using a software and Z -score analysis. Li et al [42] employed a SVM for characterisation of the hippocampal volume changes in AD and differentiation of AD patients from healthy control subjects.…”

Section: Dementia Alzheimer's and Parkinson Diseases Diagnosismentioning

confidence: 99%

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

2016

View full text Add to dashboard Cite

Section: Dementia Alzheimer's and Parkinson Diseases Diagnosismentioning

confidence: 99%

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

2016

View full text Add to dashboard Cite

“…Brain atrophy was one of the potential confounding factors for associating WML with gait (Seidler et al 2010). Therefore, we evaluated brain atrophy using validated software, the voxel-based, specific regional analysis system for advance Alzheimer's disease (Hirata et al 2005;Matsuda et al 2012). …”

Section: Mrimentioning

confidence: 99%

Effects of white matter lesions on trunk stability during dual-task walking among older adults with mild cognitive impairment

Doi¹,

Shimada

Makizako

et al. 2015

AGE

View full text Add to dashboard Cite

The linkage between gait and cognition has been shown in cases of white matter lesion (WML) that affect gait in older adults. Dual-task walking is believed to be cognitively demanding and to alter trunk movement, and gait impairment in people with mild cognitive impairment (MCI) is highlighted under this condition. However, the association between dual-task walking and structural changes in the brain, particularly with WML, in people with MCI is still unclear. The aim of this study was to examine the association between trunk stability during dual-task walking and WML in 560 older adults with MCI. We measured magnetic resonance imaging (MRI) and gait variables. Gait variables included harmonic ratio in vertical, mediolateral, and anteroposterior directions, analyzed using a tri-axial accelerometer attached to the lower trunk. Walking conditions were normal walking and dual-task walking (counting backwards while walking) conditions. Demographical data and brain atrophy were measured as covariates. Subjects were classified into non-severe WML (n=451, mean age=73.2 years) and severe WML (n=109, mean age=75.9 years) groups. Linear mixedeffects model analysis controlled for covariates showed dual-task-related changes in all harmonic ratios associated with WML (p<0.05). Even after adjustment for executive function, harmonic ratio in the mediolateral direction was significantly associated with WML (p<0.05). Our findings revealed that WMLs were associated with trunk stability in dual-task walking. Further studies are required to investigate the neural basis for deficits in gait ability among MCI subjects.

show abstract

“…In the first step, an affine transformation was applied as a global registration. The affine transformation is given by 11 12 13 21 22 23…”

Section: Measurement Of Functional Image Featuresmentioning

confidence: 99%

“…The affine transformation matrix consisting of 11 to 32 was obtained by using a least squaresmethod based on a singular value decomposition so that the feature points in the moving and reference images corresponded with each other. For determination of the affine transformation, the minimum and maximum coordinates of the binary images of the moving images and T2-weighted images were selected as four sets of corresponding feature points.…”

Section: Measurement Of Functional Image Featuresmentioning

confidence: 99%

“…AD is associated with morphological and functional changes, i.e., the atrophy of gray matter in the cerebral cortex, and the decrease of cerebral blood flow (CBF) in specific cerebral regions which can be evaluated with magnetic resonance imaging (MRI) and nuclear medicine examinations obtained by positron-emission tomography (PET) or single-photon emission computed tomography (SPECT) [6][7][8][9][10][11][12][13]. However, the examinations by PET and SPECT are more expensive and invasive than those using MRI.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Computer-aided differential diagnosis system for Alzheimer’s disease based on machine learning with functional and morphological image features in magnetic resonance imaging

Yamashita¹,

Arimura²,

Yamada³

et al. 2013

JBiSE

View full text Add to dashboard Cite

Alzheimer's disease (AD) is a dementing disorder and one of the major public health problems in countries with greater longevity. The cerebral cortical thickness and cerebral blood flow (CBF), which are considered as morphological and functional image features, respectively, could be decreased in specific cerebral regions of patients with dementia of Alzheimer type. Therefore, the aim of this study was to develop a computer-aided classification system for AD patients based on machine learning with the morphological and functional image features derived from a magnetic resonance (MR) imaging system. The cortical thicknesses in ten cerebral regions were derived as morphological features by using gradient vector trajectories in fuzzy membership images. Functional CBF maps were measured with an arterial spin labeling technique, and ten regional CBF values were obtained by registration between the CBF map and Talairach atlas using an affine transformation and a free form deformation. We applied two systems based on an arterial neural network (

show abstract

Voxel-based morphometry to discriminate early Alzheimer's disease from controls

Cited by 311 publications

References 18 publications

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

Effects of white matter lesions on trunk stability during dual-task walking among older adults with mild cognitive impairment

Computer-aided differential diagnosis system for Alzheimer’s disease based on machine learning with functional and morphological image features in magnetic resonance imaging

Contact Info

Product

Resources

About