Dataset Information

Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): a fractal dimension study.

ABSTRACT: Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disorder. Current diagnosis time is about 12-months due to lack of objective methods. Previous brain white matter voxel based morphometry (VBM) studies in ALS reported inconsistent results. Fractal dimension (FD) has successfully been used to quantify brain WM shape complexity in various neurological disorders and aging, but not yet studied in ALS. Therefore, we investigated WM morphometric changes using FD analyses in ALS patients with different clinical phenotypes. We hypothesized that FD would better capture clinical features of the WM morphometry in different ALS phenotypes than VBM analysis. High resolution MRI T1-weighted images were acquired in controls (n = 11), and ALS patients (n = 89). ALS patients were assigned into four subgroups based on their clinical phenotypes.VBM analysis was carried out using SPM8. FD values were estimated for brain WM skeleton, surface and general structure in both controls and ALS patients using our previously published algorithm. No significant VBM WM changes were observed between controls and ALS patients and among the ALS subgroups. In contrast, significant (p<0.05) FD reductions in skeleton and general structure were observed between ALS with dementia and other ALS subgroups. No significant differences in any of the FD measures were observed between control and ALS patients. FD correlated significantly with revised ALS functional rating scale (ALSFRS-R) score a clinical measure of function. Results suggest that brain WM shape complexity is more sensitive to ALS disease process when compared to volumetric VBM analysis and FD changes are dependent on the ALS phenotype. Correlation between FD and clinical measures suggests that FD could potentially serve as a biomarker of ALS pathophysiology, especially after confirmation by longitudinal studies.

SUBMITTER: Rajagopalan V

PROVIDER: S-EPMC3767806 | biostudies-other | 2013

REPOSITORIES: biostudies-other

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Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): a fractal dimension study.

Rajagopalan Venkateswaran V Liu Zao Z Allexandre Didier D Zhang Luduan L Wang Xiao-Feng XF Pioro Erik P EP Yue Guang H GH

PloS one 20130909 9

Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disorder. Current diagnosis time is about 12-months due to lack of objective methods. Previous brain white matter voxel based morphometry (VBM) studies in ALS reported inconsistent results. Fractal dimension (FD) has successfully been used to quantify brain WM shape complexity in various neurological disorders and aging, but not yet studied in ALS. Therefore, we investigated WM morphometric changes using FD analyses in ...[more]

PMID: 24040000

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Project description:Primary lateral sclerosis is a sporadic disorder characterized by slowly progressive corticospinal dysfunction. Primary lateral sclerosis differs from amyotrophic lateral sclerosis by its lack of lower motor neuron signs and long survival. Few pathological studies have been carried out on patients with primary lateral sclerosis, and the relationship between primary lateral sclerosis and amyotrophic lateral sclerosis remains uncertain. To detect in vivo structural differences between the two disorders, diffusion tensor imaging of white matter tracts was carried out in 19 patients with primary lateral sclerosis, 18 patients with amyotrophic lateral sclerosis and 19 age-matched controls. Fibre tracking was used to reconstruct the intracranial portion of the corticospinal tract and three regions of the corpus callosum: the genu, splenium and callosal fibres connecting the motor cortices. Both patient groups had reduced fractional anisotropy, a measure associated with axonal organization, and increased mean diffusivity of the reconstructed corticospinal and callosal motor fibres compared with controls, without changes in the genu or splenium. Voxelwise comparison of the whole brain white matter using tract-based spatial statistics confirmed the differences between patients and controls in the diffusion properties of the corticospinal tracts and motor fibres of the callosum. This analysis further revealed differences in the regional distribution of white matter alterations between the patient groups. In patients with amyotrophic lateral sclerosis, the greatest reduction in fractional anisotropy occurred in the distal portions of the intracranial corticospinal tract, consistent with a distal axonal degeneration. In patients with primary lateral sclerosis, the greatest loss of fractional anisotropy and mean diffusivity occurred in the subcortical white matter underlying the motor cortex, with reduced volume, suggesting tissue loss. Clinical measures of upper motor neuron dysfunction correlated with reductions in fractional anisotropy in the corticospinal tract in patients with amyotrophic lateral sclerosis and increased mean diffusivity and volume loss of the corticospinal tract in patients with primary lateral sclerosis. Changes in the diffusion properties of the motor fibres of the corpus callosum were strongly correlated with changes in corticospinal fibres in patients, but not in controls. These findings indicate that degeneration is not selective for corticospinal neurons, but affects callosal neurons within the motor cortex in motor neuron disorders.

Project description:Motor imagery is based on the volitional modulation of sensorimotor rhythms (SMRs); however, the sensorimotor processes in patients with amyotrophic lateral sclerosis (ALS) are impaired, leading to degenerated motor imagery ability. Thus, motor imagery classification in ALS patients has been considered challenging in the brain-computer interface (BCI) community. In this study, we address this critical issue by introducing the Grassberger-Procaccia and Higuchi's methods to estimate the fractal dimensions (GPFD and HFD, respectively) of the electroencephalography (EEG) signals from ALS patients. Moreover, a Fisher's criterion-based channel selection strategy is proposed to automatically determine the best patient-dependent channel configuration from 30 EEG recording sites. An EEG data collection paradigm is designed to collect the EEG signal of resting state and the imagination of three movements, including right hand grasping (RH), left hand grasping (LH), and left foot stepping (LF). Five late-stage ALS patients without receiving any SMR training participated in this study. Experimental results show that the proposed GPFD feature is not only superior to the previously-used SMR features (mu and beta band powers of EEG from sensorimotor cortex) but also better than HFD. The accuracies achieved by the SMR features are not satisfactory (all lower than 80%) in all binary classification tasks, including RH imagery vs. resting, LH imagery vs. resting, and LF imagery vs. resting. For the discrimination between RH imagery and resting, the average accuracies of GPFD in 30-channel (without channel selection) and top-five-channel configurations are 95.25% and 93.50%, respectively. When using only one channel (the best channel among the 30), a high accuracy of 91.00% can still be achieved by the GPFD feature and a linear discriminant analysis (LDA) classifier. The results also demonstrate that the proposed Fisher's criterion-based channel selection is capable of removing a large amount of redundant and noisy EEG channels. The proposed GPFD feature extraction combined with the channel selection strategy can be used as the basis for further developing high-accuracy and high-usability motor imagery BCI systems from which the patients with ALS can really benefit.

Dataset Information

Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): a fractal dimension study.

Publications

Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): a fractal dimension study.

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