Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/327129
Type: Artigo
Title: Mri Texture Analysis Reveals Deep Gray Nuclei Damage In Amyotrophic Lateral Sclerosis
Author: de Albuquerque
Milena; Anjos
Lara G. V.; Tavares de Andrade
Helen Maia; de Oliveira
Marcia S.; Castellano
Gabriela; Ribeiro de Rezende
Thiago Junqueira; Nucci
Anamarli; Franca Junior
Marcondes Cavalcante
Abstract: Amyotrophic Lateral Sclerosis (ALS) is characterized by extensive corticospinal damage, but extrapyramidal involvement is suggested in pathological studies. Texture analysis (TA) is an image processing technique that evaluates the distribution of gray levels between pixels in a given region of interest (ROI). It provides quantitative data and has been employed in several neurodegenerative disorders. Here, we used TA to investigate possible deep gray nuclei (DGN) abnormalities in a cohort of ALS patients. METHODSThirty-two ALS patients and 32 healthy controls underwent MRI in a 3T scanner. The T1 volumetric sequence was used for DGN segmentation and extraction of 11 texture parameters using the MaZda software. Statistical analyses were performed using the Mann-Whitney non-parametric test, with a significance level set at = 0.025 (FDR-corrected) for TA. RESULTSPatients had significantly higher values for the parameter correlation (CO) in both thalami and in the right caudate nucleus compared to healthy controls. Also, the parameter Inverse Difference Moment or Homogeneity (IDM) presented significantly smaller values in the ALS group in both thalami. CONCLUSIONSTA of T1 weighted images revealed DGN alterations in patients with ALS, namely in the thalami and caudate nuclei.
Subject: Mri
Texture Analysis
Als
Basal Ganglia
Roi
Editor: Wiley-Blackwell
Hoboken
Citation: Journal Of Neuroimaging. Wiley-blackwell, v. 26, p. 201 - 206, 2016.
Rights: fechado
Identifier DOI: 10.1111/jon.12262
Address: http://onlinelibrary-wiley-com.ez88.periodicos.capes.gov.br/doi/10.1111/jon.12262/abstract
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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